_variables.yml

# AUTO-GENERATED FILE - DO NOT EDIT
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# Run: python scripts/generate-everything-parameters-variables-calculations-references.py
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# Metadata variables:
#   {{< var total_parameter_count >}} - Number of parameters
#   {{< var total_latex_equation_count >}} - Number of LaTeX equations
#   {{< var total_citation_count >}} - Number of citations
#

"adaptable_trial_cost_per_patient": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-adaptable_trial_cost_per_patient\" class=\"parameter-link\" data-source-ref=\"pragmatic-trials-cost-advantage\" data-source-type=\"external\" data-confidence=\"medium\" title=\"Cost per patient in ADAPTABLE trial ($14M PCORI grant / 15,076 patients). Note: This is the direct grant cost; true cost including in-kind may be 10-40% higher. | ~ Medium confidence | 95% CI: [$929, $1.4K] | Dist: Lognormal | Unit: USD/patient | Click to view details, calculation & sources\">$929 (95% CI: $929-$1.4K)</a>"
"adaptable_trial_cost_per_patient_cite": "@pragmatic-trials-cost-advantage"
"adaptable_trial_patients": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-adaptable_trial_patients\" class=\"parameter-link\" data-source-ref=\"pragmatic-trials-cost-advantage\" data-source-type=\"definition\" data-confidence=\"high\" title=\"Patients enrolled in ADAPTABLE trial (PCORnet 2016-2019). Enrolled across 40 clinical sites. Precise count from trial completion records. | ✓ High confidence | Unit: patients | Click to view details, calculation & sources\">15.1 thousand patients</a>"
"adaptable_trial_patients_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-adaptable_trial_patients\" class=\"parameter-link\" data-source-ref=\"pragmatic-trials-cost-advantage\" data-source-type=\"definition\" data-confidence=\"high\" title=\"Patients enrolled in ADAPTABLE trial (PCORnet 2016-2019). Enrolled across 40 clinical sites. Precise count from trial completion records. | ✓ High confidence | Unit: patients | Click to view details, calculation & sources\">15.1 thousand</a>"
"adaptable_trial_total_cost": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-adaptable_trial_total_cost\" class=\"parameter-link\" data-source-ref=\"pragmatic-trials-cost-advantage\" data-source-type=\"external\" data-confidence=\"medium\" title=\"PCORI grant for ADAPTABLE trial (2016-2019). Note: Direct funding only; total costs including site overhead and in-kind contributions from health systems may be higher. | ~ Medium confidence | 95% CI: [$14M, $20M] | Dist: Lognormal | Unit: USD | Click to view details, calculation & sources\">$14M (95% CI: $14M-$20M)</a>"
"adaptable_trial_total_cost_cite": "@pragmatic-trials-cost-advantage"
"additional_drugs_from_cost_elimination": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-additional_drugs_from_cost_elimination\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Additional drug approvals per year when Phase 2/3 cost barrier eliminated. Assumes valley-of-death compounds (abandoned due to cost) would have similar success rate to funded compounds. | Calculated from 2 inputs | ~ Medium confidence | Formula: CURRENT_APPROVALS × VALLEY_OF_DEATH_PCT | Unit: drugs/year | Click to view details, calculation & sources\">20 drugs/year (95% CI: 18 drugs/year-22.6 drugs/year)</a>"
"additional_drugs_from_cost_elimination_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-additional_drugs_from_cost_elimination\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Additional drug approvals per year when Phase 2/3 cost barrier eliminated. Assumes valley-of-death compounds (abandoned due to cost) would have similar success rate to funded compounds. | Calculated from 2 inputs | ~ Medium confidence | Formula: CURRENT_APPROVALS × VALLEY_OF_DEATH_PCT | Unit: drugs/year | Click to view details, calculation & sources\">20 (95% CI: 18-22.6)</a>"
"additional_drugs_from_cost_elimination_latex": "$$\n\\begin{gathered}\nDrugs_{new} \\\\\n= Drugs_{ann,curr} \\times Attrition_{valley} \\\\\n= 50 \\times 40\\% \\\\\n= 20\n\\end{gathered}\n$$"
"allocation_decision_spread": "<span class=\"parameter-definition\" title=\"Return spread between the best and worst major asset-class sectors (biotech vs. coal, growth vs. value, emerging vs. declining). The accuracy advantage of crowds over experts is multiplied by this spread to estimate the allocation alpha from wishocratic decision-making. | Unit: percent | Core definition\">8% (95% CI: 5%-12%)</span>"
"annual_terrorism_death_risk_denominator": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-annual_terrorism_death_risk_denominator\" class=\"parameter-link\" data-source-ref=\"chance-of-dying-from-terrorism-1-in-30m\" data-source-type=\"external\" data-confidence=\"high\" title=\"Annual probability of being killed by terrorism expressed as '1 in X'. An American's annual odds of dying in a terrorist attack are approximately 1 in 30 million. | ✓ High confidence | Dist: Fixed | Unit: people | Click to view details, calculation & sources\">30 million people</a>"
"annual_terrorism_death_risk_denominator_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-annual_terrorism_death_risk_denominator\" class=\"parameter-link\" data-source-ref=\"chance-of-dying-from-terrorism-1-in-30m\" data-source-type=\"external\" data-confidence=\"high\" title=\"Annual probability of being killed by terrorism expressed as '1 in X'. An American's annual odds of dying in a terrorist attack are approximately 1 in 30 million. | ✓ High confidence | Dist: Fixed | Unit: people | Click to view details, calculation & sources\">30 million</a>"
"annual_terrorism_death_risk_denominator_cite": "@chance-of-dying-from-terrorism-1-in-30m"
"annual_working_hours": "<span class=\"parameter-definition\" title=\"Standard annual working hours globally. Approximately 40 hours/week x 50 weeks. ILO estimates range from 1,800-2,200 across countries; 2,000 is conventional. | Unit: hours/year | Core definition\">2 thousand hours/year</span>"
"annual_working_hours_nounit": "<span class=\"parameter-definition\" title=\"Standard annual working hours globally. Approximately 40 hours/week x 50 weeks. ILO estimates range from 1,800-2,200 across countries; 2,000 is conventional. | Unit: hours/year | Core definition\">2 thousand</span>"
"antidepressant_trial_exclusion_rate": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-antidepressant_trial_exclusion_rate\" class=\"parameter-link\" data-source-ref=\"antidepressant-trial-exclusion-rates\" data-source-type=\"external\" data-confidence=\"high\" title=\"Mean exclusion rate in antidepressant trials (86.1% of real-world patients excluded) | ✓ High confidence | Unit: percentage | Click to view details, calculation & sources\">86.1%</a>"
"antidepressant_trial_exclusion_rate_cite": "@antidepressant-trial-exclusion-rates"
"approved_drug_disease_pairings": "<span class=\"parameter-definition\" title=\"Unique approved drug-disease pairings (FDA-approved uses, midpoint of 1,500-2,000 range) | Unit: pairings | Core definition\">1.75 thousand pairings (95% CI: 1.5 thousand pairings-2 thousand pairings)</span>"
"approved_drug_disease_pairings_nounit": "<span class=\"parameter-definition\" title=\"Unique approved drug-disease pairings (FDA-approved uses, midpoint of 1,500-2,000 range) | Unit: pairings | Core definition\">1.75 thousand (95% CI: 1.5 thousand-2 thousand)</span>"
"average_market_return_pct": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-average_market_return_pct\" class=\"parameter-link\" data-source-ref=\"warren-buffett-career-average-return-20-pct\" data-source-type=\"external\" data-confidence=\"high\" title=\"Average annual stock market return (10%) | ✓ High confidence | Unit: rate | Click to view details, calculation & sources\">10%</a>"
"average_market_return_pct_cite": "@warren-buffett-career-average-return-20-pct"
"avg_life_extension_per_beneficiary": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-avg_life_extension_per_beneficiary\" class=\"parameter-link\" data-source-ref=\"lichtenberg-life-years-saved-2019\" data-source-type=\"definition\" data-confidence=\"low\" title=\"Average years of life extension per person saved by pharmaceutical interventions. Assumption used to convert life-years saved to approximate lives saved. Based on Lichtenberg's methodology where life-years are calculated from Years of Life Lost (YLL) reductions. | ? Low confidence | 95% CI: [8 years, 18 years] | Dist: Triangular | Unit: years | Click to view details, calculation & sources\">12 years (95% CI: 8 years-18 years)</a>"
"avg_life_extension_per_beneficiary_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-avg_life_extension_per_beneficiary\" class=\"parameter-link\" data-source-ref=\"lichtenberg-life-years-saved-2019\" data-source-type=\"definition\" data-confidence=\"low\" title=\"Average years of life extension per person saved by pharmaceutical interventions. Assumption used to convert life-years saved to approximate lives saved. Based on Lichtenberg's methodology where life-years are calculated from Years of Life Lost (YLL) reductions. | ? Low confidence | 95% CI: [8 years, 18 years] | Dist: Triangular | Unit: years | Click to view details, calculation & sources\">12 (95% CI: 8-18)</a>"
"baseline_lives_saved_annual": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-baseline_lives_saved_annual\" class=\"parameter-link\" data-source-ref=\"who-global-health-estimates-2024\" data-source-type=\"external\" data-peer-reviewed=\"true\" data-confidence=\"medium\" title=\"Baseline annual lives saved by pharmaceuticals (conservative aggregate) | ~ Medium confidence | \U0001F4CA Peer-reviewed | Conservative estimate | Updated: 2024 | Unit: deaths/year | Click to view details, calculation & sources\">12 deaths/year</a>"
"baseline_lives_saved_annual_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-baseline_lives_saved_annual\" class=\"parameter-link\" data-source-ref=\"who-global-health-estimates-2024\" data-source-type=\"external\" data-peer-reviewed=\"true\" data-confidence=\"medium\" title=\"Baseline annual lives saved by pharmaceuticals (conservative aggregate) | ~ Medium confidence | \U0001F4CA Peer-reviewed | Conservative estimate | Updated: 2024 | Unit: deaths/year | Click to view details, calculation & sources\">12</a>"
"baseline_lives_saved_annual_cite": "@who-global-health-estimates-2024"
"bed_nets_cost_per_daly": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-bed_nets_cost_per_daly\" class=\"parameter-link\" data-source-ref=\"givewell-cost-per-life-saved\" data-source-type=\"external\" data-peer-reviewed=\"true\" data-confidence=\"high\" title=\"GiveWell cost per DALY for insecticide-treated bed nets (midpoint estimate, range $78-100). DALYs (Disability-Adjusted Life Years) measure disease burden by combining years of life lost and years lived with disability. Bed nets prevent malaria deaths and are considered a gold standard benchmark for cost-effective global health interventions - if an intervention costs less per DALY than bed nets, it's exceptionally cost-effective. GiveWell synthesizes peer-reviewed academic research with transparent, rigorous methodology and extensive external expert review. | ✓ High confidence | \U0001F4CA Peer-reviewed | 95% CI: [$78, $100] | Dist: Normal | Unit: USD/DALY | Click to view details, calculation & sources\">$89 (95% CI: $78-$100)</a>"
"bed_nets_cost_per_daly_cite": "@givewell-cost-per-life-saved"
"best_practice_life_expectancy_gain": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-best_practice_life_expectancy_gain\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Gap between current global life expectancy and the best life expectancy achieved by a major country today. Used as a non-arbitrary governance/public-health uplift benchmark rather than capping Wishonia at today's global average. | Calculated from 3 inputs | ✓ High confidence | Formula: max(SWITZERLAND_LIFE_EXPECTANCY, SINGAPORE_LIFE_EXPECTANCY) - GLOBAL_LIFE_EXPECTANCY_2024 | Unit: years | Click to view details, calculation & sources\">5.1 years (95% CI: 1.81 years-8.45 years)</a>"
"best_practice_life_expectancy_gain_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-best_practice_life_expectancy_gain\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Gap between current global life expectancy and the best life expectancy achieved by a major country today. Used as a non-arbitrary governance/public-health uplift benchmark rather than capping Wishonia at today's global average. | Calculated from 3 inputs | ✓ High confidence | Formula: max(SWITZERLAND_LIFE_EXPECTANCY, SINGAPORE_LIFE_EXPECTANCY) - GLOBAL_LIFE_EXPECTANCY_2024 | Unit: years | Click to view details, calculation & sources\">5.1 (95% CI: 1.81-8.45)</a>"
"best_practice_life_expectancy_gain_latex": "$$\n\\begin{gathered}\n\\Delta LE_{best} \\\\\n= \\max\\left(LE_{CH}, LE_{SG}\\right) - LE_{global}\n\\end{gathered}\n$$"
"campaign_celebrity_endorsement": "<span class=\"parameter-definition\" title=\"Celebrity and influencer endorsements | Unit: USD | Core definition\">$15M (95% CI: $10.5M-$19.5M)</span>"
"campaign_community_organizing": "<span class=\"parameter-definition\" title=\"Community organizing and ambassador program budget | Unit: USD | Core definition\">$30M (95% CI: $21M-$39M)</span>"
"campaign_contingency": "<span class=\"parameter-definition\" title=\"Contingency fund for unexpected costs | Unit: USD | Core definition\">$50M (95% CI: $30M-$80M)</span>"
"campaign_defense_conversion": "<span class=\"parameter-definition\" title=\"Defense industry conversion program | Unit: USD | Core definition\">$50M (95% CI: $40M-$70M)</span>"
"campaign_defense_lobbyist_budget": "<span class=\"parameter-definition\" title=\"Budget for co-opting defense industry lobbyists | Unit: USD | Core definition\">$50M (95% CI: $35M-$65M)</span>"
"campaign_healthcare_alignment": "<span class=\"parameter-definition\" title=\"Healthcare industry alignment and partnerships | Unit: USD | Core definition\">$35M (95% CI: $24.5M-$45.5M)</span>"
"campaign_infrastructure": "<span class=\"parameter-definition\" title=\"Campaign operational infrastructure | Unit: USD | Core definition\">$20M (95% CI: $14M-$26M)</span>"
"campaign_legal_ai_budget": "<span class=\"parameter-definition\" title=\"AI-assisted legal work budget | Unit: USD | Core definition\">$50M (95% CI: $35M-$65M)</span>"
"campaign_legal_defense": "<span class=\"parameter-definition\" title=\"Legal defense fund | Unit: USD | Core definition\">$20M (95% CI: $14M-$26M)</span>"
"campaign_legal_work": "<span class=\"parameter-definition\" title=\"Legal drafting and compliance work | Unit: USD | Core definition\">$60M (95% CI: $50M-$80M)</span>"
"campaign_lobbying_eu": "<span class=\"parameter-definition\" title=\"EU lobbying campaign budget | Unit: USD | Core definition\">$40M (95% CI: $28M-$52M)</span>"
"campaign_lobbying_g20_millions": "<span class=\"parameter-definition\" title=\"G20 countries lobbying budget | Unit: USD | Core definition\">$35M</span>"
"campaign_lobbying_us": "<span class=\"parameter-definition\" title=\"US lobbying campaign budget | Unit: USD | Core definition\">$50M (95% CI: $35M-$65M)</span>"
"campaign_media_budget_max": "<span class=\"parameter-definition\" title=\"Maximum mass media campaign budget | Unit: USD | Core definition\">$1B (95% CI: $700M-$1.3B)</span>"
"campaign_media_budget_min": "<span class=\"parameter-definition\" title=\"Minimum mass media campaign budget | Unit: USD | Core definition\">$500M (95% CI: $350M-$650M)</span>"
"campaign_opposition_research": "<span class=\"parameter-definition\" title=\"Opposition research and rapid response | Unit: USD | Core definition\">$25M (95% CI: $17.5M-$32.5M)</span>"
"campaign_phase1_budget": "<span class=\"parameter-definition\" title=\"Phase 1 campaign budget (Foundation, Year 1) | Unit: USD | Core definition\">$200M (95% CI: $140M-$260M)</span>"
"campaign_phase2_budget": "<span class=\"parameter-definition\" title=\"Phase 2 campaign budget (Scale & Momentum, Years 2-3) | Unit: USD | Core definition\">$500M (95% CI: $350M-$650M)</span>"
"campaign_pilot_programs": "<span class=\"parameter-definition\" title=\"Pilot program testing in small countries | Unit: USD | Core definition\">$30M (95% CI: $21M-$39M)</span>"
"campaign_platform_development": "<span class=\"parameter-definition\" title=\"Voting platform and technology development | Unit: USD | Core definition\">$35M (95% CI: $25M-$50M)</span>"
"campaign_regulatory_navigation": "<span class=\"parameter-definition\" title=\"Regulatory compliance and navigation | Unit: USD | Core definition\">$20M (95% CI: $14M-$26M)</span>"
"campaign_scaling_prep": "<span class=\"parameter-definition\" title=\"Scaling preparation and blueprints | Unit: USD | Core definition\">$30M (95% CI: $21M-$39M)</span>"
"campaign_staff_budget": "<span class=\"parameter-definition\" title=\"Campaign core team staff budget | Unit: USD | Core definition\">$40M (95% CI: $28M-$52M)</span>"
"campaign_super_pac_budget": "<span class=\"parameter-definition\" title=\"Super PAC campaign expenditures | Unit: USD | Core definition\">$30M (95% CI: $21M-$39M)</span>"
"campaign_tech_partnerships": "<span class=\"parameter-definition\" title=\"Tech industry partnerships and infrastructure | Unit: USD | Core definition\">$25M (95% CI: $17.5M-$32.5M)</span>"
"campaign_treaty_implementation": "<span class=\"parameter-definition\" title=\"Post-victory treaty implementation support | Unit: USD | Core definition\">$40M (95% CI: $30M-$55M)</span>"
"campaign_viral_content_budget": "<span class=\"parameter-definition\" title=\"Viral marketing content creation budget | Unit: USD | Core definition\">$40M (95% CI: $28M-$52M)</span>"
"caregiver_annual_value_total": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-caregiver_annual_value_total\" class=\"parameter-link\" data-source-ref=\"unpaid-caregiver-hours-economic-value\" data-source-type=\"external\" data-confidence=\"high\" title=\"Total annual value of unpaid caregiving in US | ✓ High confidence | Unit: USD/year | Click to view details, calculation & sources\">$600B</a>"
"caregiver_annual_value_total_cite": "@unpaid-caregiver-hours-economic-value"
"caregiver_cost_annual": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-caregiver_cost_annual\" class=\"parameter-link\" data-source-ref=\"unpaid-caregiver-hours-economic-value\" data-source-type=\"definition\" data-confidence=\"high\" title=\"Annual cost of unpaid caregiving (replacement cost method) | ✓ High confidence | Formula: HOURS_PER_MONTH × MONTHS_PER_YEAR × VALUE_PER_HOUR | Unit: USD/year | Click to view details, calculation & sources\">$6K</a>"
"caregiver_count_us": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-caregiver_count_us\" class=\"parameter-link\" data-source-ref=\"unpaid-caregiver-hours-economic-value\" data-source-type=\"external\" data-confidence=\"high\" title=\"Number of unpaid caregivers in US | ✓ High confidence | Unit: people | Click to view details, calculation & sources\">38 million people</a>"
"caregiver_count_us_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-caregiver_count_us\" class=\"parameter-link\" data-source-ref=\"unpaid-caregiver-hours-economic-value\" data-source-type=\"external\" data-confidence=\"high\" title=\"Number of unpaid caregivers in US | ✓ High confidence | Unit: people | Click to view details, calculation & sources\">38 million</a>"
"caregiver_count_us_cite": "@unpaid-caregiver-hours-economic-value"
"caregiver_hours_per_month": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-caregiver_hours_per_month\" class=\"parameter-link\" data-source-ref=\"unpaid-caregiver-hours-economic-value\" data-source-type=\"external\" data-confidence=\"high\" title=\"Average monthly hours of unpaid family caregiving in US | ✓ High confidence | Unit: hours/month | Click to view details, calculation & sources\">20 hours/month</a>"
"caregiver_hours_per_month_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-caregiver_hours_per_month\" class=\"parameter-link\" data-source-ref=\"unpaid-caregiver-hours-economic-value\" data-source-type=\"external\" data-confidence=\"high\" title=\"Average monthly hours of unpaid family caregiving in US | ✓ High confidence | Unit: hours/month | Click to view details, calculation & sources\">20</a>"
"caregiver_hours_per_month_cite": "@unpaid-caregiver-hours-economic-value"
"caregiver_value_per_hour_simple": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-caregiver_value_per_hour_simple\" class=\"parameter-link\" data-source-ref=\"unpaid-caregiver-hours-economic-value\" data-source-type=\"external\" data-confidence=\"high\" title=\"Estimated replacement cost per hour of caregiving | ✓ High confidence | Unit: USD/hour | Click to view details, calculation & sources\">$25</a>"
"caregiver_value_per_hour_simple_cite": "@unpaid-caregiver-hours-economic-value"
"cell_therapy_approaches": "<span class=\"parameter-definition\" title=\"Distinct cell therapy approaches (CAR-T variants, iPSCs, MSCs, organoids) | Unit: approaches | Core definition\">500 approaches (95% CI: 300 approaches-800 approaches)</span>"
"cell_therapy_approaches_nounit": "<span class=\"parameter-definition\" title=\"Distinct cell therapy approaches (CAR-T variants, iPSCs, MSCs, organoids) | Unit: approaches | Core definition\">500 (95% CI: 300-800)</span>"
"cell_therapy_disease_combinations": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-cell_therapy_disease_combinations\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Cell therapy approach-disease combinations | Calculated from 2 inputs | ✓ High confidence | Formula: CELL_APPROACHES × DISEASES | Unit: combinations | Click to view details, calculation & sources\">500 thousand combinations</a>"
"cell_therapy_disease_combinations_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-cell_therapy_disease_combinations\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Cell therapy approach-disease combinations | Calculated from 2 inputs | ✓ High confidence | Formula: CELL_APPROACHES × DISEASES | Unit: combinations | Click to view details, calculation & sources\">500 thousand</a>"
"cell_therapy_disease_combinations_latex": "$$\n\\begin{gathered}\nCombos_{cell} \\\\\n= N_{cell} \\times N_{diseases,trial} \\\\\n= 500 \\times 1{,}000 \\\\\n= 500{,}000\n\\end{gathered}\n$$"
"chain_dismiss_probability": "<span class=\"parameter-definition\" title=\"Probability someone dismisses the idea without engaging (the 'institutionalization rate') | Unit: rate | Core definition\">90% (95% CI: 80%-97%)</span>"
"chain_effective_r": "<span class=\"parameter-definition\" title=\"Effective reproduction number per cascade generation: fraction of viewers who share (5%) x average forwards per sharer (3). CI spans pessimistic (2% x 2 = 0.04) to optimistic (10% x 8 = 0.80). | Unit: ratio | Core definition\">0.15 (95% CI: 0.04-0.8)</span>"
"chain_engage_probability": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-chain_engage_probability\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Probability someone engages with the idea (1 - dismissal rate) | Calculated from 1 input | ✓ High confidence | Formula: 1 - CHAIN_DISMISS_PROBABILITY | Unit: rate | Click to view details, calculation & sources\">10% (95% CI: 3.91%-18.1%)</a>"
"chain_engage_probability_latex": "$$\nP_{engage} = 1 - P_{dismiss} = 1 - 90\\% = 10\\%\n$$"
"chain_expected_engaged_implementers": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-chain_expected_engaged_implementers\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Expected number of implementers who engage (orbit reached x engagement rate x implementer count) | Calculated from 5 inputs | ✓ High confidence | Formula: P_reach x CHAIN_ENGAGE_PROBABILITY x CHAIN_IMPLEMENTER_COUNT | Unit: people | Click to view details, calculation & sources\">3.48 people (95% CI: 0.0736 people-53.7 people)</a>"
"chain_expected_engaged_implementers_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-chain_expected_engaged_implementers\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Expected number of implementers who engage (orbit reached x engagement rate x implementer count) | Calculated from 5 inputs | ✓ High confidence | Formula: P_reach x CHAIN_ENGAGE_PROBABILITY x CHAIN_IMPLEMENTER_COUNT | Unit: people | Click to view details, calculation & sources\">3.48 (95% CI: 0.0736-53.7)</a>"
"chain_expected_engaged_implementers_latex": "$$\nE[N_{engaged}] = P_{reach} \\times P_{engage} \\times N_{impl}\n$$"
"chain_global_billionaire_count": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-chain_global_billionaire_count\" class=\"parameter-link\" data-source-ref=\"forbes-billionaires-2024\" data-source-type=\"external\" data-confidence=\"high\" title=\"Number of billionaires globally (Forbes 2024 count) | ✓ High confidence | Dist: Fixed | Unit: people | Click to view details, calculation & sources\">2.78 thousand people</a>"
"chain_global_billionaire_count_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-chain_global_billionaire_count\" class=\"parameter-link\" data-source-ref=\"forbes-billionaires-2024\" data-source-type=\"external\" data-confidence=\"high\" title=\"Number of billionaires globally (Forbes 2024 count) | ✓ High confidence | Dist: Fixed | Unit: people | Click to view details, calculation & sources\">2.78 thousand</a>"
"chain_global_billionaire_count_cite": "@forbes-billionaires-2024"
"chain_horizon_years": "<span class=\"parameter-definition\" title=\"Conservative upper bound for cascade propagation (social media cascades propagate in weeks; 3 years allows for slower channels and multiple cascade waves) | Unit: years | Core definition\">3 years</span>"
"chain_horizon_years_nounit": "<span class=\"parameter-definition\" title=\"Conservative upper bound for cascade propagation (social media cascades propagate in weeks; 3 years allows for slower channels and multiple cascade waves) | Unit: years | Core definition\">3</span>"
"chain_implementer_count": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-chain_implementer_count\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Total potential implementers (billionaires + world leaders) | Calculated from 2 inputs | ✓ High confidence | Formula: CHAIN_GLOBAL_BILLIONAIRE_COUNT + CHAIN_WORLD_LEADER_COUNT | Unit: people | Click to view details, calculation & sources\">2.98 thousand people</a>"
"chain_implementer_count_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-chain_implementer_count\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Total potential implementers (billionaires + world leaders) | Calculated from 2 inputs | ✓ High confidence | Formula: CHAIN_GLOBAL_BILLIONAIRE_COUNT + CHAIN_WORLD_LEADER_COUNT | Unit: people | Click to view details, calculation & sources\">2.98 thousand</a>"
"chain_implementer_count_latex": "$$\n\\begin{gathered}\nN_{impl} \\\\\n= N_{billionaire} + N_{leader} \\\\\n= 2{,}780 + 195 \\\\\n= 2{,}980\n\\end{gathered}\n$$"
"chain_implementer_orbit_size": "<span class=\"parameter-definition\" title=\"Information-orbit size per implementer: people whose recommendation would reach them (staff, advisors, active social media feeds, professional contacts). Lower bound: Dunbar's 150; upper: corporate C-suite intake funnel. | Unit: people | Core definition\">1 thousand people (95% CI: 150 people-5 thousand people)</span>"
"chain_implementer_orbit_size_nounit": "<span class=\"parameter-definition\" title=\"Information-orbit size per implementer: people whose recommendation would reach them (staff, advisors, active social media feeds, professional contacts). Lower bound: Dunbar's 150; upper: corporate C-suite intake funnel. | Unit: people | Core definition\">1 thousand (95% CI: 150-5 thousand)</span>"
"chain_initial_audience": "<span class=\"parameter-definition\" title=\"Conservative initial audience size (readers, website visitors, conference attendees) | Unit: people | Core definition\">50 thousand people (95% CI: 10 thousand people-500 thousand people)</span>"
"chain_initial_audience_nounit": "<span class=\"parameter-definition\" title=\"Conservative initial audience size (readers, website visitors, conference attendees) | Unit: people | Core definition\">50 thousand (95% CI: 10 thousand-500 thousand)</span>"
"chain_p_at_least_one_engages": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-chain_p_at_least_one_engages\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Probability at least one implementer engages (information diffusion only; dominant strategy proof handles action) | Calculated from 1 input | ✓ High confidence | Formula: 1 - CHAIN_P_NO_IMPLEMENTER_ENGAGES | Unit: percent | Click to view details, calculation & sources\">96.9% (95% CI: 7.09%-100%)</a>"
"chain_p_at_least_one_engages_latex": "$$\nP_{reach} = 1 - P_{none} = 1 - 3.08\\% = 96.9\\%\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nP_{none} \\\\\n= \\left(1 - P_{reach} \\cdot P_{engage}\\right)^{N_{impl}}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nP_{engage} = 1 - P_{dismiss} = 1 - 90\\% = 10\\%\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{impl} \\\\\n= N_{billionaire} + N_{leader} \\\\\n= 2{,}780 + 195 \\\\\n= 2{,}980\n\\end{gathered}\n$$"
"chain_p_encounter_direct_10yr": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-chain_p_encounter_direct_10yr\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Probability a given implementer's information orbit is reached by the content cascade | Calculated from 3 inputs | ✓ High confidence | Formula: 1 - (1 - CHAIN_IMPLEMENTER_ORBIT_SIZE / 5B)^(CHAIN_INITIAL_AUDIENCE x cascade_multiplier) | Unit: rate | Click to view details, calculation & sources\">1.17% (95% CI: 0.0312%-18.6%)</a>"
"chain_p_encounter_direct_10yr_latex": "$$\n\\begin{gathered}\nP_{reach} \\\\\n= 1 - \\left(1 - \\frac{O_{impl}}{N}\\right)^{N_0 \\cdot \\sum_{i=0}^{3} R_{eff}^i}\n\\end{gathered}\n$$"
"chain_p_no_implementer_engages": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-chain_p_no_implementer_engages\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Probability that NO implementer engages (all orbits missed or all dismiss) | Calculated from 5 inputs | ✓ High confidence | Formula: (1 - P_reach x CHAIN_ENGAGE_PROBABILITY)^CHAIN_IMPLEMENTER_COUNT | Unit: rate | Click to view details, calculation & sources\">3.08% (95% CI: 2.79e-22%-92.9%)</a>"
"chain_p_no_implementer_engages_latex": "$$\n\\begin{gathered}\nP_{none} \\\\\n= \\left(1 - P_{reach} \\cdot P_{engage}\\right)^{N_{impl}}\n\\end{gathered}\n$$"
"chain_world_leader_count": "<span class=\"parameter-definition\" title=\"Number of sovereign heads of state/government | Unit: countries | Core definition\">195 countries</span>"
"chain_world_leader_count_nounit": "<span class=\"parameter-definition\" title=\"Number of sovereign heads of state/government | Unit: countries | Core definition\">195</span>"
"childhood_vaccination_annual_benefit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-childhood_vaccination_annual_benefit\" class=\"parameter-link\" data-source-ref=\"childhood-vaccination-economic-benefits\" data-source-type=\"external\" data-confidence=\"high\" title=\"Estimated annual global economic benefit from childhood vaccination programs (measles, polio, etc.) | ✓ High confidence | Dist: Lognormal (SE: $4.5B) | Unit: USD/year | Click to view details, calculation & sources\">$15B (95% CI: $8.79B-$23.3B)</a>"
"childhood_vaccination_annual_benefit_cite": "@childhood-vaccination-economic-benefits"
"childhood_vaccination_cost_per_daly": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-childhood_vaccination_cost_per_daly\" class=\"parameter-link\" data-source-ref=\"childhood-vaccination-roi\" data-source-type=\"definition\" data-confidence=\"low\" title=\"Estimated cost per DALY for US childhood vaccination programs. Note: US cost-effectiveness studies primarily use cost per QALY (Quality-Adjusted Life Year) rather than cost per DALY. This estimate is derived from program costs and benefits for comparison purposes only. | ? Low confidence | Unit: USD/DALY | Click to view details, calculation & sources\">$30</a>"
"childhood_vaccination_roi": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-childhood_vaccination_roi\" class=\"parameter-link\" data-source-ref=\"childhood-vaccination-roi\" data-source-type=\"external\" data-confidence=\"high\" title=\"Return on investment from childhood vaccination programs | ✓ High confidence | Unit: ratio | Click to view details, calculation & sources\">13</a>"
"childhood_vaccination_roi_cite": "@childhood-vaccination-roi"
"chronic_disease_disability_weight": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-chronic_disease_disability_weight\" class=\"parameter-link\" data-source-ref=\"who-global-health-estimates-2024\" data-source-type=\"external\" data-peer-reviewed=\"true\" data-confidence=\"medium\" title=\"Disability weight for untreated chronic conditions (WHO Global Burden of Disease) | ~ Medium confidence | \U0001F4CA Peer-reviewed | Dist: Normal (SE: 0.07 weight) | Unit: weight | Click to view details, calculation & sources\">0.35 weight (95% CI: 0.233 weight-0.465 weight)</a>"
"chronic_disease_disability_weight_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-chronic_disease_disability_weight\" class=\"parameter-link\" data-source-ref=\"who-global-health-estimates-2024\" data-source-type=\"external\" data-peer-reviewed=\"true\" data-confidence=\"medium\" title=\"Disability weight for untreated chronic conditions (WHO Global Burden of Disease) | ~ Medium confidence | \U0001F4CA Peer-reviewed | Dist: Normal (SE: 0.07 weight) | Unit: weight | Click to view details, calculation & sources\">0.35 (95% CI: 0.233-0.465)</a>"
"chronic_disease_disability_weight_cite": "@who-global-health-estimates-2024"
"chronic_disease_treated_patients_annual": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-chronic_disease_treated_patients_annual\" class=\"parameter-link\" data-source-ref=\"iqvia-global-medicines-2024\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Estimated unique patients receiving chronic disease treatment annually. Derived from IQVIA days of therapy (1.28T) divided by 365 days divided by 2.5 average medications per patient times 70% post-1962 drugs. | Calculated from 1 input | ? Low confidence | Formula: GLOBAL_CHRONIC_THERAPY_DAYS ÷ 365 ÷ 2.5 × 0.70 | Unit: people | Click to view details, calculation & sources\">982 million people (95% CI: 827 million people-1.15 billion people)</a>"
"chronic_disease_treated_patients_annual_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-chronic_disease_treated_patients_annual\" class=\"parameter-link\" data-source-ref=\"iqvia-global-medicines-2024\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Estimated unique patients receiving chronic disease treatment annually. Derived from IQVIA days of therapy (1.28T) divided by 365 days divided by 2.5 average medications per patient times 70% post-1962 drugs. | Calculated from 1 input | ? Low confidence | Formula: GLOBAL_CHRONIC_THERAPY_DAYS ÷ 365 ÷ 2.5 × 0.70 | Unit: people | Click to view details, calculation & sources\">982 million (95% CI: 827 million-1.15 billion)</a>"
"chronic_disease_treated_patients_annual_latex": "$$\n\\begin{gathered}\nN_{treated} \\\\\n= DOT_{chronic} \\times 0.000767 \\\\\n= 1.28T \\times 0.000767 \\\\\n= 982M\n\\end{gathered}\n$$"
"clinical_trial_cost_per_approved_drug": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-clinical_trial_cost_per_approved_drug\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Annual clinical trial spending per approved drug (trials only, excluding other R&D costs like discovery, preclinical, manufacturing) | Calculated from 2 inputs | ✓ High confidence | Formula: TOTAL_TRIAL_SPENDING / NEW_DRUGS | Unit: USD | Click to view details, calculation & sources\">$1.2B (95% CI: $1.09B-$1.33B)</a>"
"clinical_trial_cost_per_approved_drug_latex": "$$\n\\begin{gathered}\nCost_{trial,drug} \\\\\n= \\frac{Spending_{trials}}{Drugs_{ann,curr}} \\\\\n= \\frac{\\$60B}{50} \\\\\n= \\$1.2B\n\\end{gathered}\n$$"
"clinical_trial_cost_per_participant_annual": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-clinical_trial_cost_per_participant_annual\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Average annual cost per clinical trial participant (total spending ÷ participants) | Calculated from 2 inputs | ✓ High confidence | Formula: TOTAL_SPENDING / PARTICIPANTS | Unit: USD | Click to view details, calculation & sources\">$31.6K (95% CI: $29.8K-$33.6K)</a>"
"clinical_trial_cost_per_participant_annual_latex": "$$\n\\begin{gathered}\nCost_{trial,pt,ann} \\\\\n= \\frac{Spending_{trials}}{Slots_{curr}} \\\\\n= \\frac{\\$60B}{1.9M} \\\\\n= \\$31.6K\n\\end{gathered}\n$$"
"combination_therapy_disease_space": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-combination_therapy_disease_space\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Total combination therapy space (pairwise drug combinations × diseases). Standard in oncology, HIV, cardiology. | Calculated from 2 inputs | ✓ High confidence | Formula: DRUG_PAIRS × DISEASES | Unit: combinations | Click to view details, calculation & sources\">45.1 billion combinations</a>"
"combination_therapy_disease_space_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-combination_therapy_disease_space\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Total combination therapy space (pairwise drug combinations × diseases). Standard in oncology, HIV, cardiology. | Calculated from 2 inputs | ✓ High confidence | Formula: DRUG_PAIRS × DISEASES | Unit: combinations | Click to view details, calculation & sources\">45.1 billion</a>"
"combination_therapy_disease_space_latex": "$$\n\\begin{gathered}\nSpace_{combo} \\\\\n= N_{combo} \\times N_{diseases,trial} \\\\\n= 45.1M \\times 1{,}000 \\\\\n= 45.1B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nN_{combo} = \\frac{N_{safe} \\cdot (N_{safe} - 1)}{2}\n$$"
"combination_therapy_pairs": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-combination_therapy_pairs\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Unique pairwise drug combinations from known safe compounds (n choose 2) | Calculated from 1 input | ✓ High confidence | Formula: SAFE_COMPOUNDS_COUNT × (SAFE_COMPOUNDS_COUNT - 1) ÷ 2 | Unit: combinations | Click to view details, calculation & sources\">45.1 million combinations</a>"
"combination_therapy_pairs_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-combination_therapy_pairs\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Unique pairwise drug combinations from known safe compounds (n choose 2) | Calculated from 1 input | ✓ High confidence | Formula: SAFE_COMPOUNDS_COUNT × (SAFE_COMPOUNDS_COUNT - 1) ÷ 2 | Unit: combinations | Click to view details, calculation & sources\">45.1 million</a>"
"combination_therapy_pairs_latex": "$$\nN_{combo} = \\frac{N_{safe} \\cdot (N_{safe} - 1)}{2}\n$$"
"concentrated_interest_sector_market_cap_usd": "<span class=\"parameter-definition\" title=\"Estimated combined market capitalization of concentrated interest opposition (defense, fossil fuel, etc.) | Unit: USD | Core definition\">$5T</span>"
"contribution_dalys_per_pct_point": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-contribution_dalys_per_pct_point\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"DALYs averted per percentage point of implementation probability shift. One percent of total DALYs from eliminating trial capacity bottleneck and efficacy lag. | Calculated from 1 input | ✓ High confidence | Formula: DFDA_TRIAL_CAPACITY_PLUS_EFFICACY_LAG_DALYS × 0.01 | Unit: DALYs | Click to view details, calculation & sources\">5.65 billion DALYs (95% CI: 3.61 billion DALYs-8.77 billion DALYs)</a>"
"contribution_dalys_per_pct_point_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-contribution_dalys_per_pct_point\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"DALYs averted per percentage point of implementation probability shift. One percent of total DALYs from eliminating trial capacity bottleneck and efficacy lag. | Calculated from 1 input | ✓ High confidence | Formula: DFDA_TRIAL_CAPACITY_PLUS_EFFICACY_LAG_DALYS × 0.01 | Unit: DALYs | Click to view details, calculation & sources\">5.65 billion (95% CI: 3.61 billion-8.77 billion)</a>"
"contribution_dalys_per_pct_point_latex": "$$\n\\begin{gathered}\nDALYs_{pp} \\\\\n= DALYs_{max} \\times 0.01 \\\\\n= 565B \\times 0.01 \\\\\n= 5.65B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDALYs_{max} \\\\\n= DALYs_{global,ann} \\times Pct_{avoid,DALY} \\times T_{accel,max} \\\\\n= 2.88B \\times 92.6\\% \\times 212 \\\\\n= 565B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nT_{accel,max} = T_{accel} + T_{lag} = 204 + 8.2 = 212\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{accel} \\\\\n= T_{first,SQ} \\times \\left(1 - \\frac{1}{k_{capacity}}\\right) \\\\\n= 222 \\times \\left(1 - \\frac{1}{12.3}\\right) \\\\\n= 204\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{first,SQ} \\\\\n= T_{queue,SQ} \\times 0.5 \\\\\n= 443 \\times 0.5 \\\\\n= 222\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{queue,SQ} \\\\\n= \\frac{N_{untreated}}{Treatments_{new,ann}} \\\\\n= \\frac{6{,}650}{15} \\\\\n= 443\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$"
"contribution_ev_per_pct_point_treaty": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-contribution_ev_per_pct_point_treaty\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Personal expected value per percentage point of implementation probability shift under Treaty Trajectory. One percent of the per-capita lifetime income gain. | Calculated from 1 input | ✓ High confidence | Formula: TREATY_TRAJECTORY_LIFETIME_INCOME_GAIN_PER_CAPITA × 0.01 | Unit: USD | Click to view details, calculation & sources\">$34.8K (95% CI: $10.5K-$98.2K)</a>"
"contribution_ev_per_pct_point_treaty_latex": "$$\n\\begin{gathered}\nEV_{pp,treaty} \\\\\n= \\Delta Y_{lifetime,treaty} \\times 0.01 \\\\\n= \\$3.48M \\times 0.01 \\\\\n= \\$34.8K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\Delta Y_{lifetime,treaty} \\\\\n= Y_{cum,treaty} - Y_{cum,earth} \\\\\n= \\$4.58M - \\$1.1M \\\\\n= \\$3.48M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nY_{cum,treaty} \\\\\n= \\bar{y}_0 \\cdot \\frac{(1+g_{pc,treaty})((1+g_{pc,treaty})^{20}-1)}{g_{pc,treaty}} \\\\\n+ \\bar{y}_{treaty,20} \\cdot \\frac{(1+g_{pc,base})((1+g_{pc,base})^{T_{remaining}-20}-1)}{g_{pc,base}}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{y}_{0} \\\\\n= \\frac{GDP_{global}}{Pop_{global}} \\\\\n= \\frac{\\$115T}{8B} \\\\\n= \\$14.4K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{y}_{treaty,20} \\\\\n= \\frac{GDP_{treaty,20}}{Pop_{2045}} \\\\\n= \\frac{\\$919T}{9.2B} \\\\\n= \\$99.9K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nGDP_{treaty,20} \\\\\n= GDP_{global} \\times (1 + g_{base} + g_{redirect,treaty,20} \\\\\n+ g_{peace,treaty,20} + g_{cyber,treaty,20} \\\\\n+ g_{health,treaty,20})^{20}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{redirect,treaty,20} \\\\\n= \\bar{s}_{treaty,20} \\times \\Delta g_{30\\%} \\times m_{spillover} \\times 1.67 \\\\\n= 5.8\\% \\times 5.5\\% \\times 2 \\times 1.67 \\\\\n= 1.06\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{peace,treaty,20} \\\\\n= \\left(\\frac{Benefit_{peace,soc}}{GDP_{global}}\\right) \\times \\left(\\frac{\\bar{s}_{treaty,20}}{Reduce_{treaty}}\\right) \\times \\varepsilon_{conflict}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nBenefit_{peace,soc} \\\\\n= Cost_{war,total} \\times Reduce_{treaty} \\\\\n= \\$11.4T \\times 1\\% \\\\\n= \\$114B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,total} \\\\\n= Cost_{war,direct} + Cost_{war,indirect} \\\\\n= \\$7.66T + \\$3.7T \\\\\n= \\$11.4T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,direct} \\\\\n= Loss_{life,conflict} + Damage_{infra,total} \\\\\n+ Disruption_{trade} + Spending_{mil} \\\\\n= \\$2.45T + \\$1.88T + \\$616B + \\$2.72T \\\\\n= \\$7.66T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{life,conflict} \\\\\n= Cost_{combat,human} + Cost_{state,human} \\\\\n+ Cost_{terror,human} \\\\\n= \\$2.34T + \\$27B + \\$83B \\\\\n= \\$2.45T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{combat,human} \\\\\n= Deaths_{combat} \\times VSL \\\\\n= 234{,}000 \\times \\$10M \\\\\n= \\$2.34T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{state,human} \\\\\n= Deaths_{state} \\times VSL \\\\\n= 2{,}700 \\times \\$10M \\\\\n= \\$27B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{terror,human} \\\\\n= Deaths_{terror} \\times VSL \\\\\n= 8{,}300 \\times \\$10M \\\\\n= \\$83B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDamage_{infra,total} \\\\\n= Damage_{comms} + Damage_{edu} + Damage_{energy} \\\\\n+ Damage_{health} + Damage_{transport} + Damage_{water} \\\\\n= \\$298B + \\$234B + \\$422B + \\$166B + \\$487B + \\$268B \\\\\n= \\$1.88T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDisruption_{trade} \\\\\n= Disruption_{currency} + Disruption_{energy} \\\\\n+ Disruption_{shipping} + Disruption_{supply} \\\\\n= \\$57.4B + \\$125B + \\$247B + \\$187B \\\\\n= \\$616B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,indirect} \\\\\n= Damage_{env} + Loss_{growth,mil} + Loss_{capital,conflict} \\\\\n+ Cost_{psych} + Cost_{refugee} + Cost_{vet} \\\\\n= \\$100B + \\$2.72T + \\$300B + \\$232B + \\$150B + \\$200B \\\\\n= \\$3.7T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{cyber,treaty,20} \\\\\n= \\left(\\frac{Cost_{cyber}}{GDP_{global}}\\right) \\times \\bar{s}_{treaty,20} \\times \\varepsilon_{conflict}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{health,treaty,20} \\\\\n= ((1 + f_{cure,20,treaty} \\times d_{disease} \\\\\n+ \\left(\\frac{Loss_{lag}}{GDP_{global}}\\right))^{\\frac{1}{20}}) - 1\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nf_{cure,20,treaty} \\\\\n= \\min\\left(1.0, Treatments_{new,ann} \\times (3 \\times min(k_{capacity} \\times 1, k_{capacity,max}) \\\\\n+ 4 \\times min(k_{capacity} \\times 2, k_{capacity,max}) \\\\\n+ 5 \\times min(k_{capacity} \\times 5, k_{capacity,max}) \\\\\n+ 8 \\times min(k_{capacity} \\times 10, k_{capacity,max})) / N_{untreated}\\right)\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity,max} \\\\\n= \\frac{N_{willing}}{Slots_{curr}} \\\\\n= \\frac{1.08B}{1.9M} \\\\\n= 566\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{willing} \\\\\n= N_{patients} \\times Pct_{willing} \\\\\n= 2.4B \\times 44.8\\% \\\\\n= 1.08B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{lag} \\\\\n= Deaths_{lag,total} \\times (LE_{global} - Age_{death,delay}) \\times Value_{QALY} \\\\\n= 102M \\times (79 - 62) \\times \\$150K \\\\\n= \\$259T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDeaths_{lag,total} \\\\\n= Lives_{saved,annual} \\times T_{lag} \\\\\n= 12.4M \\times 8.2 \\\\\n= 102M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLives_{saved,annual} \\\\\n= \\frac{LY_{saved,annual}}{T_{ext}} \\\\\n= \\frac{149M}{12} \\\\\n= 12.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{y}_{base,20} \\\\\n= \\frac{GDP_{base,20}}{Pop_{2045}} \\\\\n= \\frac{\\$188T}{9.2B} \\\\\n= \\$20.5K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nGDP_{base,20} = GDP_{global} \\times (1 + g_{base})^{20}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{remaining} \\\\\n= LE_{global} - Age_{median} \\\\\n= 79 - 30.5 \\\\\n= 48.5\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nY_{cum,earth} \\\\\n= \\bar{y}_0 \\cdot \\frac{(1+g_{pc,base})((1+g_{pc,base})^{T_{remaining}}-1)}{g_{pc,base}}\n\\end{gathered}\n$$"
"contribution_ev_per_pct_point_treaty_blend": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-contribution_ev_per_pct_point_treaty_blend\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Blended personal expected value per percentage point of implementation probability shift under Treaty Trajectory. | Calculated from 1 input | ✓ High confidence | Formula: TREATY_PERSONAL_UPSIDE_BLEND × 0.01 | Unit: USD | Click to view details, calculation & sources\">$67.4K (95% CI: $26.2K-$157K)</a>"
"contribution_ev_per_pct_point_treaty_blend_latex": "$$\n\\begin{gathered}\nEV_{pp,treaty,blend} \\\\\n= Upside_{blend,treaty} \\times 0.01 \\\\\n= \\$6.74M \\times 0.01 \\\\\n= \\$67.4K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nUpside_{blend,treaty} \\\\\n= \\Delta Y_{lifetime,treaty} + Value_{HALE,treaty} \\\\\n= \\$3.48M + \\$3.26M \\\\\n= \\$6.74M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\Delta Y_{lifetime,treaty} \\\\\n= Y_{cum,treaty} - Y_{cum,earth} \\\\\n= \\$4.58M - \\$1.1M \\\\\n= \\$3.48M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nY_{cum,treaty} \\\\\n= \\bar{y}_0 \\cdot \\frac{(1+g_{pc,treaty})((1+g_{pc,treaty})^{20}-1)}{g_{pc,treaty}} \\\\\n+ \\bar{y}_{treaty,20} \\cdot \\frac{(1+g_{pc,base})((1+g_{pc,base})^{T_{remaining}-20}-1)}{g_{pc,base}}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{y}_{0} \\\\\n= \\frac{GDP_{global}}{Pop_{global}} \\\\\n= \\frac{\\$115T}{8B} \\\\\n= \\$14.4K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{y}_{treaty,20} \\\\\n= \\frac{GDP_{treaty,20}}{Pop_{2045}} \\\\\n= \\frac{\\$919T}{9.2B} \\\\\n= \\$99.9K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nGDP_{treaty,20} \\\\\n= GDP_{global} \\times (1 + g_{base} + g_{redirect,treaty,20} \\\\\n+ g_{peace,treaty,20} + g_{cyber,treaty,20} \\\\\n+ g_{health,treaty,20})^{20}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{redirect,treaty,20} \\\\\n= \\bar{s}_{treaty,20} \\times \\Delta g_{30\\%} \\times m_{spillover} \\times 1.67 \\\\\n= 5.8\\% \\times 5.5\\% \\times 2 \\times 1.67 \\\\\n= 1.06\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{peace,treaty,20} \\\\\n= \\left(\\frac{Benefit_{peace,soc}}{GDP_{global}}\\right) \\times \\left(\\frac{\\bar{s}_{treaty,20}}{Reduce_{treaty}}\\right) \\times \\varepsilon_{conflict}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nBenefit_{peace,soc} \\\\\n= Cost_{war,total} \\times Reduce_{treaty} \\\\\n= \\$11.4T \\times 1\\% \\\\\n= \\$114B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,total} \\\\\n= Cost_{war,direct} + Cost_{war,indirect} \\\\\n= \\$7.66T + \\$3.7T \\\\\n= \\$11.4T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,direct} \\\\\n= Loss_{life,conflict} + Damage_{infra,total} \\\\\n+ Disruption_{trade} + Spending_{mil} \\\\\n= \\$2.45T + \\$1.88T + \\$616B + \\$2.72T \\\\\n= \\$7.66T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{life,conflict} \\\\\n= Cost_{combat,human} + Cost_{state,human} \\\\\n+ Cost_{terror,human} \\\\\n= \\$2.34T + \\$27B + \\$83B \\\\\n= \\$2.45T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDamage_{infra,total} \\\\\n= Damage_{comms} + Damage_{edu} + Damage_{energy} \\\\\n+ Damage_{health} + Damage_{transport} + Damage_{water} \\\\\n= \\$298B + \\$234B + \\$422B + \\$166B + \\$487B + \\$268B \\\\\n= \\$1.88T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDisruption_{trade} \\\\\n= Disruption_{currency} + Disruption_{energy} \\\\\n+ Disruption_{shipping} + Disruption_{supply} \\\\\n= \\$57.4B + \\$125B + \\$247B + \\$187B \\\\\n= \\$616B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,indirect} \\\\\n= Damage_{env} + Loss_{growth,mil} + Loss_{capital,conflict} \\\\\n+ Cost_{psych} + Cost_{refugee} + Cost_{vet} \\\\\n= \\$100B + \\$2.72T + \\$300B + \\$232B + \\$150B + \\$200B \\\\\n= \\$3.7T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{cyber,treaty,20} \\\\\n= \\left(\\frac{Cost_{cyber}}{GDP_{global}}\\right) \\times \\bar{s}_{treaty,20} \\times \\varepsilon_{conflict}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{health,treaty,20} \\\\\n= ((1 + f_{cure,20,treaty} \\times d_{disease} \\\\\n+ \\left(\\frac{Loss_{lag}}{GDP_{global}}\\right))^{\\frac{1}{20}}) - 1\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nf_{cure,20,treaty} \\\\\n= \\min\\left(1.0, Treatments_{new,ann} \\times (3 \\times min(k_{capacity} \\times 1, k_{capacity,max}) \\\\\n+ 4 \\times min(k_{capacity} \\times 2, k_{capacity,max}) \\\\\n+ 5 \\times min(k_{capacity} \\times 5, k_{capacity,max}) \\\\\n+ 8 \\times min(k_{capacity} \\times 10, k_{capacity,max})) / N_{untreated}\\right)\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity,max} \\\\\n= \\frac{N_{willing}}{Slots_{curr}} \\\\\n= \\frac{1.08B}{1.9M} \\\\\n= 566\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{willing} \\\\\n= N_{patients} \\times Pct_{willing} \\\\\n= 2.4B \\times 44.8\\% \\\\\n= 1.08B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{lag} \\\\\n= Deaths_{lag,total} \\times (LE_{global} - Age_{death,delay}) \\times Value_{QALY} \\\\\n= 102M \\times (79 - 62) \\times \\$150K \\\\\n= \\$259T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDeaths_{lag,total} \\\\\n= Lives_{saved,annual} \\times T_{lag} \\\\\n= 12.4M \\times 8.2 \\\\\n= 102M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLives_{saved,annual} \\\\\n= \\frac{LY_{saved,annual}}{T_{ext}} \\\\\n= \\frac{149M}{12} \\\\\n= 12.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{y}_{base,20} \\\\\n= \\frac{GDP_{base,20}}{Pop_{2045}} \\\\\n= \\frac{\\$188T}{9.2B} \\\\\n= \\$20.5K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nGDP_{base,20} = GDP_{global} \\times (1 + g_{base})^{20}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{remaining} \\\\\n= LE_{global} - Age_{median} \\\\\n= 79 - 30.5 \\\\\n= 48.5\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nY_{cum,earth} \\\\\n= \\bar{y}_0 \\cdot \\frac{(1+g_{pc,base})((1+g_{pc,base})^{T_{remaining}}-1)}{g_{pc,base}}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nValue_{HALE,treaty} \\\\\n= \\Delta HALE_{treaty,15} \\times Value_{QALY} \\\\\n= 21.7 \\times \\$150K \\\\\n= \\$3.26M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\Delta HALE_{treaty,15} \\\\\n= f_{cure,15,treaty} \\times \\Delta_{HALE} \\\\\n+ \\Delta HALE_{treaty,longevity,15}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nf_{cure,15,treaty} \\\\\n= \\min\\left(1.0, Treatments_{new,ann} \\times (3 \\times min(k_{capacity} \\times 1, k_{capacity,max}) \\\\\n+ 4 \\times min(k_{capacity} \\times 2, k_{capacity,max}) \\\\\n+ 5 \\times min(k_{capacity} \\times 5, k_{capacity,max}) \\\\\n+ 3 \\times min(k_{capacity} \\times 10, k_{capacity,max})) / N_{untreated}\\right)\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\Delta HALE_{treaty,longevity,15} \\\\\n= T_{extend} \\times \\rho_{HALE,15} \\times f_{cure,15,treaty} \\\\\n= 20 \\times 30\\% \\times 100\\% \\\\\n= 6\n\\end{gathered}\n$$"
"contribution_ev_per_pct_point_wishonia": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-contribution_ev_per_pct_point_wishonia\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Personal expected value per percentage point of implementation probability shift under Wishonia Trajectory. One percent of the per-capita lifetime income gain. | Calculated from 1 input | ✓ High confidence | Formula: WISHONIA_TRAJECTORY_LIFETIME_INCOME_GAIN_PER_CAPITA × 0.01 | Unit: USD | Click to view details, calculation & sources\">$472K (95% CI: $139K-$2.86M)</a>"
"contribution_ev_per_pct_point_wishonia_latex": "$$\n\\begin{gathered}\nEV_{pp,wish} \\\\\n= \\Delta Y_{lifetime,wish} \\times 0.01 \\\\\n= \\$47.2M \\times 0.01 \\\\\n= \\$472K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\Delta Y_{lifetime,wish} \\\\\n= Y_{cum,wish} - Y_{cum,earth} \\\\\n= \\$48.3M - \\$1.1M \\\\\n= \\$47.2M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nY_{cum,wish} \\\\\n= \\bar{y}_0 \\cdot \\frac{(1+g_{pc,wish})((1+g_{pc,wish})^{20}-1)}{g_{pc,wish}} \\\\\n+ \\bar{y}_{wish,20} \\cdot \\frac{(1+g_{pc,base})((1+g_{pc,base})^{T_{remaining}-20}-1)}{g_{pc,base}}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{y}_{0} \\\\\n= \\frac{GDP_{global}}{Pop_{global}} \\\\\n= \\frac{\\$115T}{8B} \\\\\n= \\$14.4K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{y}_{wish,20} \\\\\n= \\frac{GDP_{wish,20}}{Pop_{2045}} \\\\\n= \\frac{\\$10700T}{9.2B} \\\\\n= \\$1.16M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nGDP_{wish,20}=GDP_0(1+g_{ramp})^{3}(1+g_{full})^{17}\n$$\n\nwhere:\n\n$$\ns_{mil,max} = Cut_{WW2} = 87.6\\% = 87.6\\%\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCut_{WW2} \\\\\n= 1 - \\frac{Spending_{US,1947}}{Spending_{US,1945}} \\\\\n= 1 - \\frac{\\$176B}{\\$1.42T} \\\\\n= 87.6\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nf_{cure,20,wish} \\\\\n= \\min\\left(1.0, Treatments_{new,ann} \\times min(k_{capacity} \\times \\left(\\frac{s_{mil,max}}{0.01}\\right), k_{capacity,max}) \\times \\frac{20}{N_{untreated}}\\right)\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity,max} \\\\\n= \\frac{N_{willing}}{Slots_{curr}} \\\\\n= \\frac{1.08B}{1.9M} \\\\\n= 566\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{willing} \\\\\n= N_{patients} \\times Pct_{willing} \\\\\n= 2.4B \\times 44.8\\% \\\\\n= 1.08B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{y}_{base,20} \\\\\n= \\frac{GDP_{base,20}}{Pop_{2045}} \\\\\n= \\frac{\\$188T}{9.2B} \\\\\n= \\$20.5K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nGDP_{base,20} = GDP_{global} \\times (1 + g_{base})^{20}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{remaining} \\\\\n= LE_{global} - Age_{median} \\\\\n= 79 - 30.5 \\\\\n= 48.5\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nY_{cum,earth} \\\\\n= \\bar{y}_0 \\cdot \\frac{(1+g_{pc,base})((1+g_{pc,base})^{T_{remaining}}-1)}{g_{pc,base}}\n\\end{gathered}\n$$"
"contribution_ev_per_pct_point_wishonia_blend": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-contribution_ev_per_pct_point_wishonia_blend\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Blended personal expected value per percentage point of implementation probability shift under Wishonia Trajectory. | Calculated from 1 input | ✓ High confidence | Formula: WISHONIA_PERSONAL_UPSIDE_BLEND × 0.01 | Unit: USD | Click to view details, calculation & sources\">$512K (95% CI: $163K-$2.94M)</a>"
"contribution_ev_per_pct_point_wishonia_blend_latex": "$$\n\\begin{gathered}\nEV_{pp,wish,blend} \\\\\n= Upside_{blend,wish} \\times 0.01 \\\\\n= \\$51.2M \\times 0.01 \\\\\n= \\$512K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nUpside_{blend,wish} \\\\\n= \\Delta Y_{lifetime,wish} + Value_{HALE,wish} \\\\\n= \\$47.2M + \\$4.02M \\\\\n= \\$51.2M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\Delta Y_{lifetime,wish} \\\\\n= Y_{cum,wish} - Y_{cum,earth} \\\\\n= \\$48.3M - \\$1.1M \\\\\n= \\$47.2M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nY_{cum,wish} \\\\\n= \\bar{y}_0 \\cdot \\frac{(1+g_{pc,wish})((1+g_{pc,wish})^{20}-1)}{g_{pc,wish}} \\\\\n+ \\bar{y}_{wish,20} \\cdot \\frac{(1+g_{pc,base})((1+g_{pc,base})^{T_{remaining}-20}-1)}{g_{pc,base}}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{y}_{0} \\\\\n= \\frac{GDP_{global}}{Pop_{global}} \\\\\n= \\frac{\\$115T}{8B} \\\\\n= \\$14.4K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{y}_{wish,20} \\\\\n= \\frac{GDP_{wish,20}}{Pop_{2045}} \\\\\n= \\frac{\\$10700T}{9.2B} \\\\\n= \\$1.16M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nGDP_{wish,20}=GDP_0(1+g_{ramp})^{3}(1+g_{full})^{17}\n$$\n\nwhere:\n\n$$\ns_{mil,max} = Cut_{WW2} = 87.6\\% = 87.6\\%\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCut_{WW2} \\\\\n= 1 - \\frac{Spending_{US,1947}}{Spending_{US,1945}} \\\\\n= 1 - \\frac{\\$176B}{\\$1.42T} \\\\\n= 87.6\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nf_{cure,20,wish} \\\\\n= \\min\\left(1.0, Treatments_{new,ann} \\times min(k_{capacity} \\times \\left(\\frac{s_{mil,max}}{0.01}\\right), k_{capacity,max}) \\times \\frac{20}{N_{untreated}}\\right)\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity,max} \\\\\n= \\frac{N_{willing}}{Slots_{curr}} \\\\\n= \\frac{1.08B}{1.9M} \\\\\n= 566\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{willing} \\\\\n= N_{patients} \\times Pct_{willing} \\\\\n= 2.4B \\times 44.8\\% \\\\\n= 1.08B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{y}_{base,20} \\\\\n= \\frac{GDP_{base,20}}{Pop_{2045}} \\\\\n= \\frac{\\$188T}{9.2B} \\\\\n= \\$20.5K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nGDP_{base,20} = GDP_{global} \\times (1 + g_{base})^{20}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{remaining} \\\\\n= LE_{global} - Age_{median} \\\\\n= 79 - 30.5 \\\\\n= 48.5\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nY_{cum,earth} \\\\\n= \\bar{y}_0 \\cdot \\frac{(1+g_{pc,base})((1+g_{pc,base})^{T_{remaining}}-1)}{g_{pc,base}}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nValue_{HALE,wish} \\\\\n= \\Delta HALE_{wish,15} \\times Value_{QALY} \\\\\n= 26.8 \\times \\$150K \\\\\n= \\$4.02M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\Delta HALE_{wish,15} \\\\\n= f_{cure,15,wish} \\times \\Delta_{HALE} \\\\\n+ \\Delta HALE_{wish,extra,15}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nf_{cure,15,wish} \\\\\n= \\min\\left(1.0, Treatments_{new,ann} \\times min(k_{capacity} \\times \\left(\\frac{s_{mil,max}}{0.01}\\right), k_{capacity,max}) \\times \\frac{15}{N_{untreated}}\\right)\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\Delta HALE_{wish,extra,15} \\\\\n= f_{cure,15,wish} \\times (\\Delta LE_{best} \\\\\n+ T_{extend} \\times \\rho_{HALE,15})\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\Delta LE_{best} \\\\\n= \\max\\left(LE_{CH}, LE_{SG}\\right) - LE_{global}\n\\end{gathered}\n$$"
"contribution_lives_saved_per_pct_point": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-contribution_lives_saved_per_pct_point\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Lives saved per percentage point of implementation probability shift. One percent of total lives saved from eliminating trial capacity bottleneck and efficacy lag. | Calculated from 1 input | ✓ High confidence | Formula: DFDA_TRIAL_CAPACITY_PLUS_EFFICACY_LAG_LIVES_SAVED × 0.01 | Unit: lives | Click to view details, calculation & sources\">107 million lives (95% CI: 74 million lives-162 million lives)</a>"
"contribution_lives_saved_per_pct_point_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-contribution_lives_saved_per_pct_point\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Lives saved per percentage point of implementation probability shift. One percent of total lives saved from eliminating trial capacity bottleneck and efficacy lag. | Calculated from 1 input | ✓ High confidence | Formula: DFDA_TRIAL_CAPACITY_PLUS_EFFICACY_LAG_LIVES_SAVED × 0.01 | Unit: lives | Click to view details, calculation & sources\">107 million (95% CI: 74 million-162 million)</a>"
"contribution_lives_saved_per_pct_point_latex": "$$\n\\begin{gathered}\nLives_{pp} \\\\\n= Lives_{max} \\times 0.01 \\\\\n= 10.7B \\times 0.01 \\\\\n= 107M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLives_{max} \\\\\n= Deaths_{disease,daily} \\times T_{accel,max} \\times 338 \\\\\n= 150{,}000 \\times 212 \\times 338 \\\\\n= 10.7B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nT_{accel,max} = T_{accel} + T_{lag} = 204 + 8.2 = 212\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{accel} \\\\\n= T_{first,SQ} \\times \\left(1 - \\frac{1}{k_{capacity}}\\right) \\\\\n= 222 \\times \\left(1 - \\frac{1}{12.3}\\right) \\\\\n= 204\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{first,SQ} \\\\\n= T_{queue,SQ} \\times 0.5 \\\\\n= 443 \\times 0.5 \\\\\n= 222\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{queue,SQ} \\\\\n= \\frac{N_{untreated}}{Treatments_{new,ann}} \\\\\n= \\frac{6{,}650}{15} \\\\\n= 443\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$"
"contribution_suffering_hours_per_pct_point": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-contribution_suffering_hours_per_pct_point\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Suffering hours prevented per percentage point of implementation probability shift. One percent of total suffering hours from eliminating trial capacity bottleneck and efficacy lag. | Calculated from 1 input | ✓ High confidence | Formula: DFDA_TRIAL_CAPACITY_PLUS_EFFICACY_LAG_SUFFERING_HOURS × 0.01 | Unit: hours | Click to view details, calculation & sources\">19.3 trillion hours (95% CI: 13.6 trillion hours-26.2 trillion hours)</a>"
"contribution_suffering_hours_per_pct_point_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-contribution_suffering_hours_per_pct_point\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Suffering hours prevented per percentage point of implementation probability shift. One percent of total suffering hours from eliminating trial capacity bottleneck and efficacy lag. | Calculated from 1 input | ✓ High confidence | Formula: DFDA_TRIAL_CAPACITY_PLUS_EFFICACY_LAG_SUFFERING_HOURS × 0.01 | Unit: hours | Click to view details, calculation & sources\">19.3 trillion (95% CI: 13.6 trillion-26.2 trillion)</a>"
"contribution_suffering_hours_per_pct_point_latex": "$$\n\\begin{gathered}\nHours_{pp} \\\\\n= Hours_{suffer,max} \\times 0.01 \\\\\n= 1930T \\times 0.01 \\\\\n= 19.3T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nHours_{suffer,max} \\\\\n= DALYs_{max} \\times Pct_{YLD} \\times 8760 \\\\\n= 565B \\times 0.39 \\times 8760 \\\\\n= 1930T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDALYs_{max} \\\\\n= DALYs_{global,ann} \\times Pct_{avoid,DALY} \\times T_{accel,max} \\\\\n= 2.88B \\times 92.6\\% \\times 212 \\\\\n= 565B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nT_{accel,max} = T_{accel} + T_{lag} = 204 + 8.2 = 212\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{accel} \\\\\n= T_{first,SQ} \\times \\left(1 - \\frac{1}{k_{capacity}}\\right) \\\\\n= 222 \\times \\left(1 - \\frac{1}{12.3}\\right) \\\\\n= 204\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{first,SQ} \\\\\n= T_{queue,SQ} \\times 0.5 \\\\\n= 443 \\times 0.5 \\\\\n= 222\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{queue,SQ} \\\\\n= \\frac{N_{untreated}}{Treatments_{new,ann}} \\\\\n= \\frac{6{,}650}{15} \\\\\n= 443\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$"
"conventional_retirement_horizon_multiple": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-conventional_retirement_horizon_multiple\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Compound multiple for conventional retirement investing over the PRIZE pool resolution horizon (tied to the destructive economy 50% threshold year). | Calculated from 3 inputs | ✓ High confidence | Formula: (1 + CONVENTIONAL_RETIREMENT_RETURN) ^ (DESTRUCTIVE_ECONOMY_50PCT_YEAR - DESTRUCTIVE_ECONOMY_BASE_YEAR) | Unit: x | Click to view details, calculation & sources\">2.57x (95% CI: 2.14x-3.07x)</a>"
"conventional_retirement_horizon_multiple_latex": "$$\nM_{retire} = (1 + r_{retire}) ^{Y_{50\\%} - Y_0}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nY_{50\\%} \\\\\n= Y_0 \\\\\n+ \\frac{\\ln\\left(0.50 / \\text{DESTRUCTIVE\\_PCT\\_GDP}\\right)}{\\ln\\left(1 + \\text{DESTRUCTIVE\\_GROWTH} - \\text{GDP\\_GROWTH}\\right)}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nr_{destruct:GDP} \\\\\n= \\frac{Cost_{destruct}}{GDP_{global}} \\\\\n= \\frac{\\$13.2T}{\\$115T} \\\\\n= 11.5\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{destruct} \\\\\n= Spending_{mil} + Cost_{cyber} \\\\\n= \\$2.72T + \\$10.5T \\\\\n= \\$13.2T\n\\end{gathered}\n$$"
"conventional_retirement_return": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-conventional_retirement_return\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"external\" data-confidence=\"high\" title=\"Average retail after-fee return on conventional retirement portfolios (60/40 stock/bond mix, ~1% advisory fees, ~0.4% fund fees). Used as the opportunity cost comparison: depositors are LOSING money by NOT participating in the Prize Fund. | ✓ High confidence | 95% CI: [5%, 8%] | Dist: Normal | Unit: percent | Click to view details, calculation & sources\">6.5% (95% CI: 5%-8%)</a>"
"cpi_multiplier_1980_to_2024": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-cpi_multiplier_1980_to_2024\" class=\"parameter-link\" data-source-ref=\"bls-cpi-inflation-calculator\" data-source-type=\"external\" data-confidence=\"high\" title=\"CPI inflation multiplier from 1980 to 2024 (280.48% cumulative inflation) | ✓ High confidence | 95% CI: [3.75:1, 3.85:1] | Dist: Normal | Unit: ratio | Click to view details, calculation & sources\">3.8 (95% CI: 3.75-3.85)</a>"
"cpi_multiplier_1980_to_2024_cite": "@bls-cpi-inflation-calculator"
"crowd_decision_accuracy": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-crowd_decision_accuracy\" class=\"parameter-link\" data-source-ref=\"surowiecki-2004\" data-source-type=\"external\" data-confidence=\"high\" title=\"Crowd accuracy on Who Wants to Be a Millionaire ask-the-audience lifeline. Studio audience picked the correct answer 91% of the time (Surowiecki 2004). Used as lower bound for wishocratic allocation accuracy. | ✓ High confidence | Dist: Fixed | Unit: percent | Click to view details, calculation & sources\">91%</a>"
"crowd_decision_accuracy_cite": "@surowiecki-2004"
"cumulative_military_in_govt_trial_years": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-cumulative_military_in_govt_trial_years\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Cumulative military spending since 1913 expressed in equivalent years of government clinical trial spending ($170T / $4.5B per year) | Calculated from 2 inputs | ✓ High confidence | Formula: CUMULATIVE_MILITARY_SPENDING_FED_ERA / GLOBAL_GOVERNMENT_CLINICAL_TRIALS_SPENDING_ANNUAL | Unit: years | Click to view details, calculation & sources\">37.8 thousand years (95% CI: 28.3 thousand years-55.9 thousand years)</a>"
"cumulative_military_in_govt_trial_years_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-cumulative_military_in_govt_trial_years\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Cumulative military spending since 1913 expressed in equivalent years of government clinical trial spending ($170T / $4.5B per year) | Calculated from 2 inputs | ✓ High confidence | Formula: CUMULATIVE_MILITARY_SPENDING_FED_ERA / GLOBAL_GOVERNMENT_CLINICAL_TRIALS_SPENDING_ANNUAL | Unit: years | Click to view details, calculation & sources\">37.8 thousand (95% CI: 28.3 thousand-55.9 thousand)</a>"
"cumulative_military_in_govt_trial_years_latex": "$$\n\\begin{gathered}\nYears_{mil \\to trials,gov} \\\\\n= \\frac{Spending_{mil,cum,fed}}{Spending_{trials,gov}} \\\\\n= \\frac{\\$170T}{\\$4.5B} \\\\\n= 37{,}800\n\\end{gathered}\n$$"
"cumulative_military_spending_all_history": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-cumulative_military_spending_all_history\" class=\"parameter-link\" data-source-ref=\"sipri-milex-2024\" data-source-type=\"definition\" data-confidence=\"low\" title=\"Cumulative global military spending across all recorded history in constant 2024 dollars. Fed era ($170T) + 19th century ($3T) + pre-1800 GDP-share estimate ($4-20T). Range: $150-225T. 75% was spent after 1945. | ? Low confidence | Dist: Fixed | Unit: USD | Click to view details, calculation & sources\">$180T</a>"
"cumulative_military_spending_fed_era": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-cumulative_military_spending_fed_era\" class=\"parameter-link\" data-source-ref=\"sipri-milex-2024\" data-source-type=\"definition\" data-confidence=\"low\" title=\"Cumulative global military spending since 1913 (Fed era) in constant 2024 dollars. Built from: SIPRI 1988-2024 ($65-72T), Cold War 1946-1987 ($50-70T reconstructed), WWI+WWII+interwar ($33T from Harrison). Range: $150-190T. | ? Low confidence | Dist: Fixed | Unit: USD | Click to view details, calculation & sources\">$170T</a>"
"current_active_trials": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-current_active_trials\" class=\"parameter-link\" data-source-ref=\"clinicaltrials-gov-enrollment-data-2025\" data-source-type=\"external\" data-confidence=\"high\" title=\"Current active trials at any given time (3-5 year duration) | ✓ High confidence | Unit: trials | Click to view details, calculation & sources\">10 thousand trials</a>"
"current_active_trials_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-current_active_trials\" class=\"parameter-link\" data-source-ref=\"clinicaltrials-gov-enrollment-data-2025\" data-source-type=\"external\" data-confidence=\"high\" title=\"Current active trials at any given time (3-5 year duration) | ✓ High confidence | Unit: trials | Click to view details, calculation & sources\">10 thousand</a>"
"current_active_trials_cite": "@clinicaltrials-gov-enrollment-data-2025"
"current_clinical_trial_participation_rate": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-current_clinical_trial_participation_rate\" class=\"parameter-link\" data-source-ref=\"clinical-trial-patient-participation-rate\" data-source-type=\"external\" data-confidence=\"high\" title=\"Current clinical trial participation rate (0.06% of population) | ✓ High confidence | Unit: rate | Click to view details, calculation & sources\">0.06%</a>"
"current_clinical_trial_participation_rate_cite": "@clinical-trial-patient-participation-rate"
"current_combination_exploration_years": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-current_combination_exploration_years\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Years to test all pairwise drug combinations at current trial capacity. Combination therapy is standard in oncology, HIV, cardiology. | Calculated from 2 inputs | ✓ High confidence | Formula: COMBINATION_SPACE ÷ CURRENT_TRIALS_PER_YEAR | Unit: years | Click to view details, calculation & sources\">13.7 million years (95% CI: 11.6 million years-16.3 million years)</a>"
"current_combination_exploration_years_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-current_combination_exploration_years\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Years to test all pairwise drug combinations at current trial capacity. Combination therapy is standard in oncology, HIV, cardiology. | Calculated from 2 inputs | ✓ High confidence | Formula: COMBINATION_SPACE ÷ CURRENT_TRIALS_PER_YEAR | Unit: years | Click to view details, calculation & sources\">13.7 million (95% CI: 11.6 million-16.3 million)</a>"
"current_combination_exploration_years_latex": "$$\n\\begin{gathered}\nT_{explore,combo} \\\\\n= \\frac{Space_{combo}}{Trials_{ann,curr}} \\\\\n= \\frac{45.1B}{3{,}300} \\\\\n= 13.7M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSpace_{combo} \\\\\n= N_{combo} \\times N_{diseases,trial} \\\\\n= 45.1M \\times 1{,}000 \\\\\n= 45.1B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nN_{combo} = \\frac{N_{safe} \\cdot (N_{safe} - 1)}{2}\n$$"
"current_disease_patients_global": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-current_disease_patients_global\" class=\"parameter-link\" data-source-ref=\"disease-prevalence-2-billion\" data-source-type=\"external\" data-confidence=\"high\" title=\"Global population with chronic diseases | ✓ High confidence | 95% CI: [2 billion people, 2.8 billion people] | Dist: Lognormal | Unit: people | Click to view details, calculation & sources\">2.4 billion people (95% CI: 2 billion people-2.8 billion people)</a>"
"current_disease_patients_global_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-current_disease_patients_global\" class=\"parameter-link\" data-source-ref=\"disease-prevalence-2-billion\" data-source-type=\"external\" data-confidence=\"high\" title=\"Global population with chronic diseases | ✓ High confidence | 95% CI: [2 billion people, 2.8 billion people] | Dist: Lognormal | Unit: people | Click to view details, calculation & sources\">2.4 billion (95% CI: 2 billion-2.8 billion)</a>"
"current_disease_patients_global_cite": "@disease-prevalence-2-billion"
"current_drug_approvals_per_year": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-current_drug_approvals_per_year\" class=\"parameter-link\" data-source-ref=\"global-new-drug-approvals-50-annually\" data-source-type=\"external\" data-confidence=\"high\" title=\"Average annual new drug approvals globally | ✓ High confidence | 95% CI: [45 drugs/year, 60 drugs/year] | Dist: Lognormal | Unit: drugs/year | Click to view details, calculation & sources\">50 drugs/year (95% CI: 45 drugs/year-60 drugs/year)</a>"
"current_drug_approvals_per_year_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-current_drug_approvals_per_year\" class=\"parameter-link\" data-source-ref=\"global-new-drug-approvals-50-annually\" data-source-type=\"external\" data-confidence=\"high\" title=\"Average annual new drug approvals globally | ✓ High confidence | 95% CI: [45 drugs/year, 60 drugs/year] | Dist: Lognormal | Unit: drugs/year | Click to view details, calculation & sources\">50 (95% CI: 45-60)</a>"
"current_drug_approvals_per_year_cite": "@global-new-drug-approvals-50-annually"
"current_known_safe_exploration_years": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-current_known_safe_exploration_years\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Years to test all known safe drug-disease combinations at current global trial capacity | Calculated from 2 inputs | ✓ High confidence | Formula: DRUG_DISEASE_COMBINATIONS ÷ CURRENT_TRIALS_PER_YEAR | Unit: years | Click to view details, calculation & sources\">2.88 thousand years (95% CI: 2.45 thousand years-3.43 thousand years)</a>"
"current_known_safe_exploration_years_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-current_known_safe_exploration_years\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Years to test all known safe drug-disease combinations at current global trial capacity | Calculated from 2 inputs | ✓ High confidence | Formula: DRUG_DISEASE_COMBINATIONS ÷ CURRENT_TRIALS_PER_YEAR | Unit: years | Click to view details, calculation & sources\">2.88 thousand (95% CI: 2.45 thousand-3.43 thousand)</a>"
"current_known_safe_exploration_years_latex": "$$\n\\begin{gathered}\nT_{explore,safe} \\\\\n= \\frac{N_{combos}}{Trials_{ann,curr}} \\\\\n= \\frac{9.5M}{3{,}300} \\\\\n= 2{,}880\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{combos} \\\\\n= N_{safe} \\times N_{diseases,trial} \\\\\n= 9{,}500 \\times 1{,}000 \\\\\n= 9.5M\n\\end{gathered}\n$$"
"current_patient_participation_rate": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-current_patient_participation_rate\" class=\"parameter-link\" data-source-ref=\"clinical-trial-patient-participation-rate\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Current patient participation rate in clinical trials (0.08% = 1.9M participants / 2.4B disease patients) | Calculated from 2 inputs | ✓ High confidence | Formula: CURRENT_TRIAL_SLOTS / DISEASE_PATIENTS | Unit: rate | Click to view details, calculation & sources\">0.0792% (95% CI: 0.0761%-0.0819%)</a>"
"current_patient_participation_rate_latex": "$$\n\\begin{gathered}\nRate_{part} \\\\\n= \\frac{Slots_{curr}}{N_{patients}} \\\\\n= \\frac{1.9M}{2.4B} \\\\\n= 0.0792\\%\n\\end{gathered}\n$$"
"current_total_exploration_years": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-current_total_exploration_years\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Years to test all therapeutic combinations (known safe + emerging modalities) at current capacity | Calculated from 2 inputs | ✓ High confidence | Formula: TOTAL_COMBINATIONS ÷ CURRENT_TRIALS_PER_YEAR | Unit: years | Click to view details, calculation & sources\">15.6 thousand years (95% CI: 13.3 thousand years-18.6 thousand years)</a>"
"current_total_exploration_years_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-current_total_exploration_years\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Years to test all therapeutic combinations (known safe + emerging modalities) at current capacity | Calculated from 2 inputs | ✓ High confidence | Formula: TOTAL_COMBINATIONS ÷ CURRENT_TRIALS_PER_YEAR | Unit: years | Click to view details, calculation & sources\">15.6 thousand (95% CI: 13.3 thousand-18.6 thousand)</a>"
"current_total_exploration_years_latex": "$$\n\\begin{gathered}\nT_{explore,total} \\\\\n= \\frac{N_{testable}}{Trials_{ann,curr}} \\\\\n= \\frac{51.5M}{3{,}300} \\\\\n= 15{,}600\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{testable} \\\\\n= N_{combos} + N_{emerging} \\\\\n= 9.5M + 42M \\\\\n= 51.5M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{combos} \\\\\n= N_{safe} \\times N_{diseases,trial} \\\\\n= 9{,}500 \\times 1{,}000 \\\\\n= 9.5M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{emerging} \\\\\n= Combos_{gene} + Combos_{mRNA} + Combos_{epi} + Combos_{cell} \\\\\n= 20M + 20M + 1.5M + 500{,}000 \\\\\n= 42M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCombos_{gene} \\\\\n= N_{genes} \\times N_{diseases,trial} \\\\\n= 20{,}000 \\times 1{,}000 \\\\\n= 20M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCombos_{mRNA} \\\\\n= N_{genes} \\times N_{diseases,trial} \\\\\n= 20{,}000 \\times 1{,}000 \\\\\n= 20M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCombos_{epi} \\\\\n= N_{epi} \\times N_{diseases,trial} \\\\\n= 1{,}500 \\times 1{,}000 \\\\\n= 1.5M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCombos_{cell} \\\\\n= N_{cell} \\times N_{diseases,trial} \\\\\n= 500 \\times 1{,}000 \\\\\n= 500{,}000\n\\end{gathered}\n$$"
"current_trajectory_avg_income_year_15": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-current_trajectory_avg_income_year_15\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Average income (GDP per capita) at year 15 under current trajectory. | Calculated from 2 inputs | ✓ High confidence | Formula: CURRENT_TRAJECTORY_GDP_YEAR_15 / GLOBAL_POPULATION_2040_PROJECTED | Unit: USD | Click to view details, calculation & sources\">$18.7K</a>"
"current_trajectory_avg_income_year_15_latex": "$$\n\\begin{gathered}\n\\bar{y}_{base,15} \\\\\n= \\frac{GDP_{base,15}}{Pop_{2040}} \\\\\n= \\frac{\\$167T}{8.9B} \\\\\n= \\$18.7K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nGDP_{base,15} = GDP_{global} \\times (1 + g_{base})^{15}\n$$"
"current_trajectory_avg_income_year_20": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-current_trajectory_avg_income_year_20\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Average income (GDP per capita) at year 20 under current trajectory trajectory. | Calculated from 2 inputs | ✓ High confidence | Formula: CURRENT_TRAJECTORY_GDP_YEAR_20 ÷ GLOBAL_POPULATION_2045_PROJECTED | Unit: USD | Click to view details, calculation & sources\">$20.5K</a>"
"current_trajectory_avg_income_year_20_latex": "$$\n\\begin{gathered}\n\\bar{y}_{base,20} \\\\\n= \\frac{GDP_{base,20}}{Pop_{2045}} \\\\\n= \\frac{\\$188T}{9.2B} \\\\\n= \\$20.5K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nGDP_{base,20} = GDP_{global} \\times (1 + g_{base})^{20}\n$$"
"current_trajectory_cumulative_lifetime_income": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-current_trajectory_cumulative_lifetime_income\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Cumulative per-capita income over an average remaining lifespan under current trajectory baseline trajectory. Uses the implied per-capita baseline CAGR from 2025 to 2045. | Calculated from 3 inputs | ✓ High confidence | Formula: GLOBAL_AVG_INCOME_2025 * (1+g_pc,base) * ((1+g_pc,base)^T - 1) / g_pc,base, where g_pc,base is implied by CURRENT_TRAJECTORY_AVG_INCOME_YEAR_20 | Unit: USD | Click to view details, calculation & sources\">$1.1M (95% CI: $992K-$1.21M)</a>"
"current_trajectory_cumulative_lifetime_income_latex": "$$\n\\begin{gathered}\nY_{cum,earth} \\\\\n= \\bar{y}_0 \\cdot \\frac{(1+g_{pc,base})((1+g_{pc,base})^{T_{remaining}}-1)}{g_{pc,base}}\n\\end{gathered}\n$$"
"current_trajectory_gdp_year_15": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-current_trajectory_gdp_year_15\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Global GDP at year 15 under status-quo current trajectory growth. | Calculated from 2 inputs | ✓ High confidence | Formula: GLOBAL_GDP_2025 * (1 + GDP_BASELINE_GROWTH_RATE)^15 | Unit: USD | Click to view details, calculation & sources\">$167T</a>"
"current_trajectory_gdp_year_15_latex": "$$\nGDP_{base,15} = GDP_{global} \\times (1 + g_{base})^{15}\n$$"
"current_trajectory_gdp_year_20": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-current_trajectory_gdp_year_20\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Global GDP at year 20 under status-quo current trajectory growth. | Calculated from 2 inputs | ✓ High confidence | Formula: GLOBAL_GDP_2025 × (1 + GDP_BASELINE_GROWTH_RATE)^20 | Unit: USD | Click to view details, calculation & sources\">$188T</a>"
"current_trajectory_gdp_year_20_latex": "$$\nGDP_{base,20} = GDP_{global} \\times (1 + g_{base})^{20}\n$$"
"current_trials_per_year": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-current_trials_per_year\" class=\"parameter-link\" data-source-ref=\"global-clinical-trials-market-2024\" data-source-type=\"external\" data-confidence=\"high\" title=\"Current global clinical trials per year | ✓ High confidence | 95% CI: [2.64 thousand trials/year, 3.96 thousand trials/year] | Dist: Lognormal | Unit: trials/year | Click to view details, calculation & sources\">3.3 thousand trials/year (95% CI: 2.64 thousand trials/year-3.96 thousand trials/year)</a>"
"current_trials_per_year_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-current_trials_per_year\" class=\"parameter-link\" data-source-ref=\"global-clinical-trials-market-2024\" data-source-type=\"external\" data-confidence=\"high\" title=\"Current global clinical trials per year | ✓ High confidence | 95% CI: [2.64 thousand trials/year, 3.96 thousand trials/year] | Dist: Lognormal | Unit: trials/year | Click to view details, calculation & sources\">3.3 thousand (95% CI: 2.64 thousand-3.96 thousand)</a>"
"current_trials_per_year_cite": "@global-clinical-trials-market-2024"
"current_trial_abandonment_rate": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-current_trial_abandonment_rate\" class=\"parameter-link\" data-source-ref=\"clinical-trial-abandonment-rate\" data-source-type=\"external\" data-confidence=\"high\" title=\"Current trial abandonment rate (40% never complete) | ✓ High confidence | Unit: rate | Click to view details, calculation & sources\">40%</a>"
"current_trial_abandonment_rate_cite": "@clinical-trial-abandonment-rate"
"current_trial_slots_available": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-current_trial_slots_available\" class=\"parameter-link\" data-source-ref=\"global-trial-participant-capacity\" data-source-type=\"external\" data-confidence=\"high\" title=\"Annual global clinical trial participants (IQVIA 2022: 1.9M post-COVID normalization) | ✓ High confidence | 95% CI: [1.5 million patients/year, 2.3 million patients/year] | Dist: Lognormal | Unit: patients/year | Click to view details, calculation & sources\">1.9 million patients/year (95% CI: 1.5 million patients/year-2.3 million patients/year)</a>"
"current_trial_slots_available_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-current_trial_slots_available\" class=\"parameter-link\" data-source-ref=\"global-trial-participant-capacity\" data-source-type=\"external\" data-confidence=\"high\" title=\"Annual global clinical trial participants (IQVIA 2022: 1.9M post-COVID normalization) | ✓ High confidence | 95% CI: [1.5 million patients/year, 2.3 million patients/year] | Dist: Lognormal | Unit: patients/year | Click to view details, calculation & sources\">1.9 million (95% CI: 1.5 million-2.3 million)</a>"
"current_trial_slots_available_cite": "@global-trial-participant-capacity"
"days_per_year": "<span class=\"parameter-link\" title=\"Parameter: DAYS_PER_YEAR\">365</span>"
"dct_platform_funding_medium": "<span class=\"parameter-definition\" title=\"Mid-range funding for commercial DCT platform | Unit: USD | Core definition\">$500M</span>"
"defense_lobbying_annual": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-defense_lobbying_annual\" class=\"parameter-link\" data-source-ref=\"lobbying-spend-defense\" data-source-type=\"external\" data-peer-reviewed=\"true\" data-confidence=\"high\" title=\"Annual defense industry lobbying spending | ✓ High confidence | \U0001F4CA Peer-reviewed | 95% CI: [$100M, $160M] | Updated: 2024 | Unit: USD/year | Click to view details, calculation & sources\">$127M (95% CI: $100M-$160M)</a>"
"defense_lobbying_annual_cite": "@lobbying-spend-defense"
"defense_sector_retention_pct": "<span class=\"parameter-definition\" title=\"Percentage of budget defense sector keeps under 1% treaty | Unit: rate | Core definition\">99%</span>"
"democide_total_20th_century": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-democide_total_20th_century\" class=\"parameter-link\" data-source-ref=\"rummel-death-by-government\" data-source-type=\"external\" data-confidence=\"high\" title=\"Total people murdered by governments worldwide, 1900-1999 (Rummel's democide estimate) | ✓ High confidence | 95% CI: [200 million deaths, 272 million deaths] | Dist: Uniform | Unit: deaths | Click to view details, calculation & sources\">262 million deaths (95% CI: 200 million deaths-272 million deaths)</a>"
"democide_total_20th_century_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-democide_total_20th_century\" class=\"parameter-link\" data-source-ref=\"rummel-death-by-government\" data-source-type=\"external\" data-confidence=\"high\" title=\"Total people murdered by governments worldwide, 1900-1999 (Rummel's democide estimate) | ✓ High confidence | 95% CI: [200 million deaths, 272 million deaths] | Dist: Uniform | Unit: deaths | Click to view details, calculation & sources\">262 million (95% CI: 200 million-272 million)</a>"
"democide_total_20th_century_cite": "@rummel-death-by-government"
"destructive_economy_25pct_year": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-destructive_economy_25pct_year\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Calendar year when the destructive economy (military + cybercrime) reaches 25% of GDP at current growth rates. Historical precedent suggests societies become unstable when extraction rates exceed 20-30% of economic output. | Calculated from 8 inputs | ✓ High confidence | Formula: DESTRUCTIVE_ECONOMY_BASE_YEAR + ln(0.25 / DESTRUCTIVE_PCT_GDP) / ln(1 + DESTRUCTIVE_GROWTH - GDP_GROWTH) | Unit: year | Click to view details, calculation & sources\">2033</a>"
"destructive_economy_25pct_year_latex": "$$\n\\begin{gathered}\nY_{25\\%} \\\\\n= Y_0 \\\\\n+ \\frac{\\ln\\left(0.25 / \\text{DESTRUCTIVE\\_PCT\\_GDP}\\right)}{\\ln\\left(1 + \\text{DESTRUCTIVE\\_GROWTH} - \\text{GDP\\_GROWTH}\\right)}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nr_{destruct:GDP} \\\\\n= \\frac{Cost_{destruct}}{GDP_{global}} \\\\\n= \\frac{\\$13.2T}{\\$115T} \\\\\n= 11.5\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{destruct} \\\\\n= Spending_{mil} + Cost_{cyber} \\\\\n= \\$2.72T + \\$10.5T \\\\\n= \\$13.2T\n\\end{gathered}\n$$"
"destructive_economy_35pct_year": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-destructive_economy_35pct_year\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Calendar year when the destructive economy (military + cybercrime) reaches 35% of GDP at current growth rates. Historical evidence from the Soviet Union, Yugoslavia, Argentina, and Zimbabwe shows that total extractive burdens of 35-45% consistently trigger self-reinforcing death spirals. This is the empirically-derived terminal parasitic load threshold. | Calculated from 8 inputs | ✓ High confidence | Formula: DESTRUCTIVE_ECONOMY_BASE_YEAR + ln(0.35 / DESTRUCTIVE_PCT_GDP) / ln(1 + DESTRUCTIVE_GROWTH - GDP_GROWTH) | Unit: year | Click to view details, calculation & sources\">2037</a>"
"destructive_economy_35pct_year_latex": "$$\n\\begin{gathered}\nY_{35\\%} \\\\\n= Y_0 \\\\\n+ \\frac{\\ln\\left(0.35 / \\text{DESTRUCTIVE\\_PCT\\_GDP}\\right)}{\\ln\\left(1 + \\text{DESTRUCTIVE\\_GROWTH} - \\text{GDP\\_GROWTH}\\right)}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nr_{destruct:GDP} \\\\\n= \\frac{Cost_{destruct}}{GDP_{global}} \\\\\n= \\frac{\\$13.2T}{\\$115T} \\\\\n= 11.5\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{destruct} \\\\\n= Spending_{mil} + Cost_{cyber} \\\\\n= \\$2.72T + \\$10.5T \\\\\n= \\$13.2T\n\\end{gathered}\n$$"
"destructive_economy_50pct_year": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-destructive_economy_50pct_year\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Calendar year when the destructive economy (military + cybercrime) reaches 50% of GDP at current growth rates. At that point, half of all economic activity is destructive, so stealing starts to beat creating for individuals, firms, and states because whatever gets created gets looted fast enough to kill productive investment. | Calculated from 8 inputs | ✓ High confidence | Formula: DESTRUCTIVE_ECONOMY_BASE_YEAR + ln(0.50 / DESTRUCTIVE_PCT_GDP) / ln(1 + DESTRUCTIVE_GROWTH - GDP_GROWTH) | Unit: year | Click to view details, calculation & sources\">2040</a>"
"destructive_economy_50pct_year_latex": "$$\n\\begin{gathered}\nY_{50\\%} \\\\\n= Y_0 \\\\\n+ \\frac{\\ln\\left(0.50 / \\text{DESTRUCTIVE\\_PCT\\_GDP}\\right)}{\\ln\\left(1 + \\text{DESTRUCTIVE\\_GROWTH} - \\text{GDP\\_GROWTH}\\right)}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nr_{destruct:GDP} \\\\\n= \\frac{Cost_{destruct}}{GDP_{global}} \\\\\n= \\frac{\\$13.2T}{\\$115T} \\\\\n= 11.5\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{destruct} \\\\\n= Spending_{mil} + Cost_{cyber} \\\\\n= \\$2.72T + \\$10.5T \\\\\n= \\$13.2T\n\\end{gathered}\n$$"
"destructive_economy_base_year": "<span class=\"parameter-definition\" title=\"Base year for destructive economy projections. All threshold timelines are measured from this year. | Unit: year | Core definition\">2025</span>"
"deworming_cost_per_daly": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-deworming_cost_per_daly\" class=\"parameter-link\" data-source-ref=\"deworming-cost-per-daly\" data-source-type=\"external\" data-confidence=\"low\" title=\"Cost per DALY for deworming programs (range $28-82, midpoint estimate). GiveWell notes this 2011 estimate is outdated and their current methodology focuses on long-term income effects rather than short-term health DALYs. | ? Low confidence | Unit: USD/DALY | Click to view details, calculation & sources\">$55</a>"
"deworming_cost_per_daly_cite": "@deworming-cost-per-daly"
"dfda_annual_opex": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_annual_opex\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Total annual Decentralized Framework for Drug Assessment operational costs (sum of all components: platform + staff + infra + regulatory + community) | Calculated from 5 inputs | ✓ High confidence | Formula: PLATFORM_MAINTENANCE + STAFF + INFRASTRUCTURE + REGULATORY + COMMUNITY | Unit: USD/year | Click to view details, calculation & sources\">$40M (95% CI: $27.3M-$55.6M)</a>"
"dfda_annual_opex_latex": "$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$"
"dfda_annual_trial_funding": "<span class=\"parameter-definition\" title=\"Assumed annual funding for dFDA pragmatic clinical trials (~$21.8B/year). Source-agnostic: could come from military reallocation, philanthropy, or government appropriation. | Unit: USD/year | Core definition\">$21.8B</span>"
"dfda_benefit_rd_only_annual": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_benefit_rd_only_annual\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Annual Decentralized Framework for Drug Assessment benefit from R&D savings (trial cost reduction, secondary component) | Calculated from 2 inputs | ✓ High confidence | Formula: TRIAL_SPENDING × COST_REDUCTION_PCT | Unit: USD/year | Click to view details, calculation & sources\">$58.6B (95% CI: $49.2B-$73.1B)</a>"
"dfda_benefit_rd_only_annual_latex": "$$\n\\begin{gathered}\nBenefit_{RD,ann} \\\\\n= Spending_{trials} \\times Reduce_{pct} \\\\\n= \\$60B \\times 97.7\\% \\\\\n= \\$58.6B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nReduce_{pct} \\\\\n= 1 - \\frac{Cost_{pragmatic,pt}}{Cost_{P3,pt}} \\\\\n= 1 - \\frac{\\$929}{\\$41K} \\\\\n= 97.7\\%\n\\end{gathered}\n$$"
"dfda_combined_treatment_speedup_multiplier": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_combined_treatment_speedup_multiplier\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Combined speedup factor for treatment discovery from dFDA. Trial capacity multiplier times valley of death rescue multiplier. Diseases that would take T years to get first treatment now take T/speedup years. | Calculated from 2 inputs | ~ Medium confidence | Formula: DFDA_TRIAL_CAPACITY_MULTIPLIER × DFDA_VALLEY_OF_DEATH_RESCUE_MULTIPLIER | Unit: multiplier | Click to view details, calculation & sources\">17.3x (95% CI: 5.88x-86x)</a>"
"dfda_combined_treatment_speedup_multiplier_latex": "$$\n\\begin{gathered}\nk_{speedup} \\\\\n= k_{capacity} \\times k_{rescue} \\\\\n= 12.3 \\times 1.4 \\\\\n= 17.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nk_{rescue} = Attrition_{valley} + 1 = 40\\% + 1 = 1.4\n$$"
"dfda_direct_funding_cost_per_daly": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_direct_funding_cost_per_daly\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Cost per DALY at direct funding level for the therapeutic space exploration period. Still highly cost-effective vs bed nets. | Calculated from 2 inputs | ~ Medium confidence | Formula: NPV_DIRECT_FUNDING ÷ DALYS_TIMELINE_SHIFT | Unit: USD/DALY | Click to view details, calculation & sources\">$0.842 (95% CI: $0.242-$1.75)</a>"
"dfda_direct_funding_cost_per_daly_latex": "$$\n\\begin{gathered}\nCost_{direct,DALY} \\\\\n= \\frac{NPV_{direct}}{DALYs_{max}} \\\\\n= \\frac{\\$476B}{565B} \\\\\n= \\$0.842\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nNPV_{direct} \\\\\n= \\frac{T_{queue,dFDA}}{Funding_{dFDA,ann} \\times r_{discount}} \\\\\n= \\frac{36}{\\$21.8B \\times 3\\%} \\\\\n= \\$476B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{queue,dFDA} \\\\\n= \\frac{T_{queue,SQ}}{k_{capacity}} \\\\\n= \\frac{443}{12.3} \\\\\n= 36\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{queue,SQ} \\\\\n= \\frac{N_{untreated}}{Treatments_{new,ann}} \\\\\n= \\frac{6{,}650}{15} \\\\\n= 443\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDALYs_{max} \\\\\n= DALYs_{global,ann} \\times Pct_{avoid,DALY} \\times T_{accel,max} \\\\\n= 2.88B \\times 92.6\\% \\times 212 \\\\\n= 565B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nT_{accel,max} = T_{accel} + T_{lag} = 204 + 8.2 = 212\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{accel} \\\\\n= T_{first,SQ} \\times \\left(1 - \\frac{1}{k_{capacity}}\\right) \\\\\n= 222 \\times \\left(1 - \\frac{1}{12.3}\\right) \\\\\n= 204\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{first,SQ} \\\\\n= T_{queue,SQ} \\times 0.5 \\\\\n= 443 \\times 0.5 \\\\\n= 222\n\\end{gathered}\n$$"
"dfda_direct_funding_queue_clearance_npv": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_direct_funding_queue_clearance_npv\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"NPV of annual direct funding for the therapeutic space exploration period. Funding period equals exploration time (queue clearance years at given capacity multiplier). After exploration completes, the full timeline shift benefit is realized. | Calculated from 3 inputs | ✓ High confidence | Formula: ANNUAL_FUNDING × [(1 - (1 + r)^-T) / r] where T = exploration time | Unit: USD | Click to view details, calculation & sources\">$476B (95% CI: $211B-$652B)</a>"
"dfda_direct_funding_queue_clearance_npv_latex": "$$\n\\begin{gathered}\nNPV_{direct} \\\\\n= \\frac{T_{queue,dFDA}}{Funding_{dFDA,ann} \\times r_{discount}} \\\\\n= \\frac{36}{\\$21.8B \\times 3\\%} \\\\\n= \\$476B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{queue,dFDA} \\\\\n= \\frac{T_{queue,SQ}}{k_{capacity}} \\\\\n= \\frac{443}{12.3} \\\\\n= 36\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{queue,SQ} \\\\\n= \\frac{N_{untreated}}{Treatments_{new,ann}} \\\\\n= \\frac{6{,}650}{15} \\\\\n= 443\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$"
"dfda_direct_funding_roi_trial_capacity_plus_efficacy_lag": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_direct_funding_roi_trial_capacity_plus_efficacy_lag\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"ROI from directly funding pragmatic clinical trials over the therapeutic space exploration period. | Calculated from 2 inputs | ✓ High confidence | Formula: ECONOMIC_VALUE ÷ DIRECT_FUNDING_NPV | Unit: ratio | Click to view details, calculation & sources\">178k (95% CI: 110k-421k)</a>"
"dfda_direct_funding_roi_trial_capacity_plus_efficacy_lag_latex": "$$\n\\begin{gathered}\nROI_{direct,max} \\\\\n= \\frac{Value_{max}}{NPV_{direct}} \\\\\n= \\frac{\\$84800T}{\\$476B} \\\\\n= 178{,}000\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nValue_{max} \\\\\n= DALYs_{max} \\times Value_{QALY} \\\\\n= 565B \\times \\$150K \\\\\n= \\$84800T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDALYs_{max} \\\\\n= DALYs_{global,ann} \\times Pct_{avoid,DALY} \\times T_{accel,max} \\\\\n= 2.88B \\times 92.6\\% \\times 212 \\\\\n= 565B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nT_{accel,max} = T_{accel} + T_{lag} = 204 + 8.2 = 212\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{accel} \\\\\n= T_{first,SQ} \\times \\left(1 - \\frac{1}{k_{capacity}}\\right) \\\\\n= 222 \\times \\left(1 - \\frac{1}{12.3}\\right) \\\\\n= 204\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{first,SQ} \\\\\n= T_{queue,SQ} \\times 0.5 \\\\\n= 443 \\times 0.5 \\\\\n= 222\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{queue,SQ} \\\\\n= \\frac{N_{untreated}}{Treatments_{new,ann}} \\\\\n= \\frac{6{,}650}{15} \\\\\n= 443\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nNPV_{direct} \\\\\n= \\frac{T_{queue,dFDA}}{Funding_{dFDA,ann} \\times r_{discount}} \\\\\n= \\frac{36}{\\$21.8B \\times 3\\%} \\\\\n= \\$476B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{queue,dFDA} \\\\\n= \\frac{T_{queue,SQ}}{k_{capacity}} \\\\\n= \\frac{443}{12.3} \\\\\n= 36\n\\end{gathered}\n$$"
"dfda_direct_funding_vs_bed_nets_multiplier": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_direct_funding_vs_bed_nets_multiplier\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"How many times more cost-effective direct funding of medical research is vs bed nets. | Calculated from 2 inputs | ✓ High confidence | Formula: BED_NETS_COST_PER_DALY ÷ DIRECT_FUNDING_COST_PER_DALY | Unit: x | Click to view details, calculation & sources\">106x (95% CI: 55.9x-329x)</a>"
"dfda_direct_funding_vs_bed_nets_multiplier_latex": "$$\n\\begin{gathered}\nk_{direct,nets} \\\\\n= \\frac{Cost_{nets}}{Cost_{direct,DALY}} \\\\\n= \\frac{\\$89}{\\$0.842} \\\\\n= 106\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{direct,DALY} \\\\\n= \\frac{NPV_{direct}}{DALYs_{max}} \\\\\n= \\frac{\\$476B}{565B} \\\\\n= \\$0.842\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nNPV_{direct} \\\\\n= \\frac{T_{queue,dFDA}}{Funding_{dFDA,ann} \\times r_{discount}} \\\\\n= \\frac{36}{\\$21.8B \\times 3\\%} \\\\\n= \\$476B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{queue,dFDA} \\\\\n= \\frac{T_{queue,SQ}}{k_{capacity}} \\\\\n= \\frac{443}{12.3} \\\\\n= 36\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{queue,SQ} \\\\\n= \\frac{N_{untreated}}{Treatments_{new,ann}} \\\\\n= \\frac{6{,}650}{15} \\\\\n= 443\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDALYs_{max} \\\\\n= DALYs_{global,ann} \\times Pct_{avoid,DALY} \\times T_{accel,max} \\\\\n= 2.88B \\times 92.6\\% \\times 212 \\\\\n= 565B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nT_{accel,max} = T_{accel} + T_{lag} = 204 + 8.2 = 212\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{accel} \\\\\n= T_{first,SQ} \\times \\left(1 - \\frac{1}{k_{capacity}}\\right) \\\\\n= 222 \\times \\left(1 - \\frac{1}{12.3}\\right) \\\\\n= 204\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{first,SQ} \\\\\n= T_{queue,SQ} \\times 0.5 \\\\\n= 443 \\times 0.5 \\\\\n= 222\n\\end{gathered}\n$$"
"dfda_efficacy_lag_elimination_dalys": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_efficacy_lag_elimination_dalys\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Total Disability-Adjusted Life Years lost from disease eradication delay (PRIMARY estimate) | Calculated from 2 inputs | ~ Medium confidence | Formula: YLL + YLD | Unit: DALYs | Click to view details, calculation & sources\">7.94 billion DALYs (95% CI: 4.43 billion DALYs-12.1 billion DALYs)</a>"
"dfda_efficacy_lag_elimination_dalys_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_efficacy_lag_elimination_dalys\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Total Disability-Adjusted Life Years lost from disease eradication delay (PRIMARY estimate) | Calculated from 2 inputs | ~ Medium confidence | Formula: YLL + YLD | Unit: DALYs | Click to view details, calculation & sources\">7.94 billion (95% CI: 4.43 billion-12.1 billion)</a>"
"dfda_efficacy_lag_elimination_dalys_latex": "$$\nDALYs_{lag} = YLL_{lag} + YLD_{lag} = 7.07B + 873M = 7.94B\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nYLL_{lag} \\\\\n= Deaths_{lag} \\times (LE_{global} - Age_{death,delay}) \\\\\n= 416M \\times (79 - 62) \\\\\n= 7.07B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDeaths_{lag} \\\\\n= T_{lag} \\times Deaths_{disease,daily} \\times 338 \\\\\n= 8.2 \\times 150{,}000 \\times 338 \\\\\n= 416M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nYLD_{lag} \\\\\n= Deaths_{lag} \\times T_{suffering} \\times DW_{chronic} \\\\\n= 416M \\times 6 \\times 0.35 \\\\\n= 873M\n\\end{gathered}\n$$"
"dfda_efficacy_lag_elimination_deaths_averted": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_efficacy_lag_elimination_deaths_averted\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Total eventually avoidable deaths from delaying disease eradication by 8.2 years (PRIMARY estimate, conservative). Excludes fundamentally unavoidable deaths (primarily accidents ~7.9%). | Calculated from 2 inputs | ~ Medium confidence | Formula: ANNUAL_DEATHS × EFFICACY_LAG_YEARS × EVENTUALLY_AVOIDABLE_DEATH_PCT | Unit: deaths | Click to view details, calculation & sources\">416 million deaths (95% CI: 225 million deaths-630 million deaths)</a>"
"dfda_efficacy_lag_elimination_deaths_averted_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_efficacy_lag_elimination_deaths_averted\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Total eventually avoidable deaths from delaying disease eradication by 8.2 years (PRIMARY estimate, conservative). Excludes fundamentally unavoidable deaths (primarily accidents ~7.9%). | Calculated from 2 inputs | ~ Medium confidence | Formula: ANNUAL_DEATHS × EFFICACY_LAG_YEARS × EVENTUALLY_AVOIDABLE_DEATH_PCT | Unit: deaths | Click to view details, calculation & sources\">416 million (95% CI: 225 million-630 million)</a>"
"dfda_efficacy_lag_elimination_deaths_averted_latex": "$$\n\\begin{gathered}\nDeaths_{lag} \\\\\n= T_{lag} \\times Deaths_{disease,daily} \\times 338 \\\\\n= 8.2 \\times 150{,}000 \\times 338 \\\\\n= 416M\n\\end{gathered}\n$$"
"dfda_efficacy_lag_elimination_economic_value": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_efficacy_lag_elimination_economic_value\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Total economic loss from delaying disease eradication by 8.2 years (PRIMARY estimate, 2024 USD). Values global DALYs at standardized US/International normative rate ($150k) rather than local ability-to-pay, representing the full human capital loss. | Calculated from 2 inputs | ~ Medium confidence | Formula: DALYS_TOTAL × VSLY | Unit: USD | Click to view details, calculation & sources\">$1.19 quadrillion (95% CI: $443T-$2.41 quadrillion)</a>"
"dfda_efficacy_lag_elimination_economic_value_latex": "$$\n\\begin{gathered}\nValue_{lag} \\\\\n= DALYs_{lag} \\times Value_{QALY} \\\\\n= 7.94B \\times \\$150K \\\\\n= \\$1190T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nDALYs_{lag} = YLL_{lag} + YLD_{lag} = 7.07B + 873M = 7.94B\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nYLL_{lag} \\\\\n= Deaths_{lag} \\times (LE_{global} - Age_{death,delay}) \\\\\n= 416M \\times (79 - 62) \\\\\n= 7.07B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDeaths_{lag} \\\\\n= T_{lag} \\times Deaths_{disease,daily} \\times 338 \\\\\n= 8.2 \\times 150{,}000 \\times 338 \\\\\n= 416M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nYLD_{lag} \\\\\n= Deaths_{lag} \\times T_{suffering} \\times DW_{chronic} \\\\\n= 416M \\times 6 \\times 0.35 \\\\\n= 873M\n\\end{gathered}\n$$"
"dfda_efficacy_lag_elimination_yld": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_efficacy_lag_elimination_yld\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Years Lived with Disability during disease eradication delay (PRIMARY estimate) | Calculated from 3 inputs | ~ Medium confidence | Formula: DEATHS_TOTAL × SUFFERING_PERIOD × DISABILITY_WEIGHT | Unit: years | Click to view details, calculation & sources\">873 million years (95% CI: 217 million years-2.43 billion years)</a>"
"dfda_efficacy_lag_elimination_yld_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_efficacy_lag_elimination_yld\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Years Lived with Disability during disease eradication delay (PRIMARY estimate) | Calculated from 3 inputs | ~ Medium confidence | Formula: DEATHS_TOTAL × SUFFERING_PERIOD × DISABILITY_WEIGHT | Unit: years | Click to view details, calculation & sources\">873 million (95% CI: 217 million-2.43 billion)</a>"
"dfda_efficacy_lag_elimination_yld_latex": "$$\n\\begin{gathered}\nYLD_{lag} \\\\\n= Deaths_{lag} \\times T_{suffering} \\times DW_{chronic} \\\\\n= 416M \\times 6 \\times 0.35 \\\\\n= 873M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDeaths_{lag} \\\\\n= T_{lag} \\times Deaths_{disease,daily} \\times 338 \\\\\n= 8.2 \\times 150{,}000 \\times 338 \\\\\n= 416M\n\\end{gathered}\n$$"
"dfda_efficacy_lag_elimination_yll": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_efficacy_lag_elimination_yll\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Years of Life Lost from disease eradication delay deaths (PRIMARY estimate) | Calculated from 3 inputs | ~ Medium confidence | Formula: DEATHS_TOTAL × (LIFE_EXPECTANCY - MEAN_AGE_OF_DEATH) | Unit: years | Click to view details, calculation & sources\">7.07 billion years (95% CI: 4.21 billion years-9.68 billion years)</a>"
"dfda_efficacy_lag_elimination_yll_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_efficacy_lag_elimination_yll\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Years of Life Lost from disease eradication delay deaths (PRIMARY estimate) | Calculated from 3 inputs | ~ Medium confidence | Formula: DEATHS_TOTAL × (LIFE_EXPECTANCY - MEAN_AGE_OF_DEATH) | Unit: years | Click to view details, calculation & sources\">7.07 billion (95% CI: 4.21 billion-9.68 billion)</a>"
"dfda_efficacy_lag_elimination_yll_latex": "$$\n\\begin{gathered}\nYLL_{lag} \\\\\n= Deaths_{lag} \\times (LE_{global} - Age_{death,delay}) \\\\\n= 416M \\times (79 - 62) \\\\\n= 7.07B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDeaths_{lag} \\\\\n= T_{lag} \\times Deaths_{disease,daily} \\times 338 \\\\\n= 8.2 \\times 150{,}000 \\times 338 \\\\\n= 416M\n\\end{gathered}\n$$"
"dfda_first_treatments_per_year": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_first_treatments_per_year\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Diseases per year receiving their first effective treatment with dFDA. Scales proportionally with trial capacity multiplier. | Calculated from 2 inputs | ? Low confidence | Formula: NEW_DISEASE_FIRST_TREATMENTS_PER_YEAR × DFDA_TRIAL_CAPACITY_MULTIPLIER | Unit: diseases/year | Click to view details, calculation & sources\">185 diseases/year (95% CI: 107 diseases/year-491 diseases/year)</a>"
"dfda_first_treatments_per_year_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_first_treatments_per_year\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Diseases per year receiving their first effective treatment with dFDA. Scales proportionally with trial capacity multiplier. | Calculated from 2 inputs | ? Low confidence | Formula: NEW_DISEASE_FIRST_TREATMENTS_PER_YEAR × DFDA_TRIAL_CAPACITY_MULTIPLIER | Unit: diseases/year | Click to view details, calculation & sources\">185 (95% CI: 107-491)</a>"
"dfda_first_treatments_per_year_latex": "$$\n\\begin{gathered}\nTreatments_{dFDA,ann} \\\\\n= Treatments_{new,ann} \\times k_{capacity} \\\\\n= 15 \\times 12.3 \\\\\n= 185\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$"
"dfda_known_safe_exploration_years": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_known_safe_exploration_years\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Years to test all known safe drug-disease combinations with dFDA trial capacity | Calculated from 2 inputs | ✓ High confidence | Formula: DRUG_DISEASE_COMBINATIONS ÷ DFDA_TRIALS_PER_YEAR | Unit: years | Click to view details, calculation & sources\">234 years (95% CI: 55.9 years-583 years)</a>"
"dfda_known_safe_exploration_years_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_known_safe_exploration_years\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Years to test all known safe drug-disease combinations with dFDA trial capacity | Calculated from 2 inputs | ✓ High confidence | Formula: DRUG_DISEASE_COMBINATIONS ÷ DFDA_TRIALS_PER_YEAR | Unit: years | Click to view details, calculation & sources\">234 (95% CI: 55.9-583)</a>"
"dfda_known_safe_exploration_years_latex": "$$\n\\begin{gathered}\nT_{safe,dFDA} \\\\\n= \\frac{N_{combos}}{Capacity_{trials}} \\\\\n= \\frac{9.5M}{40{,}700} \\\\\n= 234\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{combos} \\\\\n= N_{safe} \\times N_{diseases,trial} \\\\\n= 9{,}500 \\times 1{,}000 \\\\\n= 9.5M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCapacity_{trials} \\\\\n= Trials_{ann,curr} \\times k_{capacity} \\\\\n= 3{,}300 \\times 12.3 \\\\\n= 40{,}700\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$"
"dfda_max_trial_capacity_multiplier_physical": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_max_trial_capacity_multiplier_physical\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Physical upper bound on trial-capacity multiplier from participant availability. Even with unlimited funding, annual trial enrollment cannot exceed willing participant pool. | Calculated from 2 inputs | ~ Medium confidence | Formula: WILLING_TRIAL_PARTICIPANTS_GLOBAL ÷ CURRENT_TRIAL_SLOTS_AVAILABLE | Unit: x | Click to view details, calculation & sources\">566x (95% CI: 534x-597x)</a>"
"dfda_max_trial_capacity_multiplier_physical_latex": "$$\n\\begin{gathered}\nk_{capacity,max} \\\\\n= \\frac{N_{willing}}{Slots_{curr}} \\\\\n= \\frac{1.08B}{1.9M} \\\\\n= 566\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{willing} \\\\\n= N_{patients} \\times Pct_{willing} \\\\\n= 2.4B \\times 44.8\\% \\\\\n= 1.08B\n\\end{gathered}\n$$"
"dfda_net_savings_rd_only_annual": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_net_savings_rd_only_annual\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Annual net savings from R&D cost reduction only (gross savings minus operational costs, excludes regulatory delay value) | Calculated from 2 inputs | ✓ High confidence | Formula: GROSS_SAVINGS - ANNUAL_OPEX | Unit: USD/year | Click to view details, calculation & sources\">$58.6B (95% CI: $49.2B-$73B)</a>"
"dfda_net_savings_rd_only_annual_latex": "$$\n\\begin{gathered}\nSavings_{RD,ann} \\\\\n= Benefit_{RD,ann} - OPEX_{dFDA} \\\\\n= \\$58.6B - \\$40M \\\\\n= \\$58.6B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nBenefit_{RD,ann} \\\\\n= Spending_{trials} \\times Reduce_{pct} \\\\\n= \\$60B \\times 97.7\\% \\\\\n= \\$58.6B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nReduce_{pct} \\\\\n= 1 - \\frac{Cost_{pragmatic,pt}}{Cost_{P3,pt}} \\\\\n= 1 - \\frac{\\$929}{\\$41K} \\\\\n= 97.7\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$"
"dfda_npv_adoption_ramp_years": "<span class=\"parameter-definition\" title=\"Years to reach full Decentralized Framework for Drug Assessment adoption | Unit: years | Core definition\">5 years</span>"
"dfda_npv_adoption_ramp_years_nounit": "<span class=\"parameter-definition\" title=\"Years to reach full Decentralized Framework for Drug Assessment adoption | Unit: years | Core definition\">5</span>"
"dfda_npv_annual_opex": "<span class=\"parameter-definition\" title=\"Decentralized Framework for Drug Assessment Core framework annual opex (midpoint of $11-26.5M) | Unit: USD/year | Core definition\">$18.9M (95% CI: $11M-$26.5M)</span>"
"dfda_npv_annual_opex_total": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_npv_annual_opex_total\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Total NPV annual opex (Decentralized Framework for Drug Assessment core + DIH initiatives) | Calculated from 2 inputs | ✓ High confidence | Formula: DFDA_OPEX + DIH_OPEX | Unit: USD/year | Click to view details, calculation & sources\">$40M (95% CI: $27.5M-$55.4M)</a>"
"dfda_npv_annual_opex_total_latex": "$$\n\\begin{gathered}\nOPEX_{total} \\\\\n= OPEX_{ann} + OPEX_{DIH,ann} \\\\\n= \\$18.9M + \\$21.1M \\\\\n= \\$40M\n\\end{gathered}\n$$"
"dfda_npv_benefit_rd_only": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_npv_benefit_rd_only\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"NPV of Decentralized Framework for Drug Assessment R&D savings only with 5-year adoption ramp (10-year horizon, most conservative financial estimate) | Calculated from 2 inputs | ✓ High confidence | Formula: SUM[Savings × adoption(t) / (1+r)^t] for t=1..10 | Unit: USD | Click to view details, calculation & sources\">$389B (95% CI: $327B-$485B)</a>"
"dfda_npv_benefit_rd_only_latex": "$$\n\\begin{gathered}\nNPV_{RD} \\\\\n= \\sum_{t=1}^{10} \\frac{Savings_{RD,ann} \\cdot \\frac{\\min(t,5)}{5}}{(1+r)^t}\n\\end{gathered}\n$$"
"dfda_npv_net_benefit_rd_only": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_npv_net_benefit_rd_only\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"NPV net benefit using R&D savings only (benefits minus costs) | Calculated from 2 inputs | ✓ High confidence | Formula: NPV_BENEFIT - NPV_COST | Unit: USD | Click to view details, calculation & sources\">$389B (95% CI: $326B-$484B)</a>"
"dfda_npv_net_benefit_rd_only_latex": "$$\n\\begin{gathered}\nNPV_{net,RD} \\\\\n= NPV_{RD} - Cost_{dFDA,total} \\\\\n= \\$389B - \\$611M \\\\\n= \\$389B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nNPV_{RD} \\\\\n= \\sum_{t=1}^{10} \\frac{Savings_{RD,ann} \\cdot \\frac{\\min(t,5)}{5}}{(1+r)^t}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSavings_{RD,ann} \\\\\n= Benefit_{RD,ann} - OPEX_{dFDA} \\\\\n= \\$58.6B - \\$40M \\\\\n= \\$58.6B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nBenefit_{RD,ann} \\\\\n= Spending_{trials} \\times Reduce_{pct} \\\\\n= \\$60B \\times 97.7\\% \\\\\n= \\$58.6B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nReduce_{pct} \\\\\n= 1 - \\frac{Cost_{pragmatic,pt}}{Cost_{P3,pt}} \\\\\n= 1 - \\frac{\\$929}{\\$41K} \\\\\n= 97.7\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{dFDA,total} \\\\\n= PV_{OPEX} + Cost_{upfront,total} \\\\\n= \\$342M + \\$270M \\\\\n= \\$611M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nPV_{OPEX} \\\\\n= \\frac{T_{horizon}}{OPEX_{total} \\times r_{discount}} \\\\\n= \\frac{10}{\\$40M \\times 3\\%} \\\\\n= \\$342M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{total} \\\\\n= OPEX_{ann} + OPEX_{DIH,ann} \\\\\n= \\$18.9M + \\$21.1M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{upfront,total} \\\\\n= Cost_{upfront} + Cost_{DIH,init} \\\\\n= \\$40M + \\$230M \\\\\n= \\$270M\n\\end{gathered}\n$$"
"dfda_npv_pv_annual_opex": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_npv_pv_annual_opex\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Present value of annual opex over 10 years (NPV formula) | Calculated from 3 inputs | ✓ High confidence | Formula: OPEX × [(1 - (1 + r)^-T) / r] | Unit: USD | Click to view details, calculation & sources\">$342M (95% CI: $235M-$473M)</a>"
"dfda_npv_pv_annual_opex_latex": "$$\n\\begin{gathered}\nPV_{OPEX} \\\\\n= \\frac{T_{horizon}}{OPEX_{total} \\times r_{discount}} \\\\\n= \\frac{10}{\\$40M \\times 3\\%} \\\\\n= \\$342M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{total} \\\\\n= OPEX_{ann} + OPEX_{DIH,ann} \\\\\n= \\$18.9M + \\$21.1M \\\\\n= \\$40M\n\\end{gathered}\n$$"
"dfda_npv_total_cost": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_npv_total_cost\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Total NPV cost (upfront + PV of annual opex) | Calculated from 2 inputs | ✓ High confidence | Formula: UPFRONT + PV_OPEX | Unit: USD | Click to view details, calculation & sources\">$611M (95% CI: $415M-$853M)</a>"
"dfda_npv_total_cost_latex": "$$\n\\begin{gathered}\nCost_{dFDA,total} \\\\\n= PV_{OPEX} + Cost_{upfront,total} \\\\\n= \\$342M + \\$270M \\\\\n= \\$611M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nPV_{OPEX} \\\\\n= \\frac{T_{horizon}}{OPEX_{total} \\times r_{discount}} \\\\\n= \\frac{10}{\\$40M \\times 3\\%} \\\\\n= \\$342M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{total} \\\\\n= OPEX_{ann} + OPEX_{DIH,ann} \\\\\n= \\$18.9M + \\$21.1M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{upfront,total} \\\\\n= Cost_{upfront} + Cost_{DIH,init} \\\\\n= \\$40M + \\$230M \\\\\n= \\$270M\n\\end{gathered}\n$$"
"dfda_npv_upfront_cost": "<span class=\"parameter-definition\" title=\"Decentralized Framework for Drug Assessment Core framework build cost | Unit: USD | Core definition\">$40M (95% CI: $25M-$65M)</span>"
"dfda_npv_upfront_cost_total": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_npv_upfront_cost_total\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Total NPV upfront costs (Decentralized Framework for Drug Assessment core + DIH initiatives) | Calculated from 2 inputs | ✓ High confidence | Formula: DFDA_BUILD + DIH_INITIATIVES | Unit: USD | Click to view details, calculation & sources\">$270M (95% CI: $181M-$380M)</a>"
"dfda_npv_upfront_cost_total_latex": "$$\n\\begin{gathered}\nCost_{upfront,total} \\\\\n= Cost_{upfront} + Cost_{DIH,init} \\\\\n= \\$40M + \\$230M \\\\\n= \\$270M\n\\end{gathered}\n$$"
"dfda_observational_cost_per_patient": "<span class=\"parameter-definition\" title=\"Order-of-magnitude estimate for Stage 1 observational signal detection (PIS calculation). Validated by FDA Sentinel benchmark (~$1/patient/year for similar drug safety analysis at 100M+ scale). True cost varies with scale and complexity; exact value less important than order-of-magnitude difference vs pragmatic trials (~$500-929/patient) and traditional Phase 3 (~$41,000/patient). | Unit: USD/patient | Core definition\">$0.1 (95% CI: $0.03-$1)</span>"
"dfda_opex_community": "<span class=\"parameter-definition\" title=\"Decentralized Framework for Drug Assessment community support costs | Unit: USD/year | Core definition\">$2M (95% CI: $1M-$3M)</span>"
"dfda_opex_infrastructure": "<span class=\"parameter-definition\" title=\"Decentralized Framework for Drug Assessment infrastructure costs (cloud, security) | Unit: USD/year | Core definition\">$8M (95% CI: $5M-$12M)</span>"
"dfda_opex_pct_of_treaty_funding": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_opex_pct_of_treaty_funding\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Percentage of treaty funding allocated to Decentralized Framework for Drug Assessment framework overhead | Calculated from 2 inputs | ✓ High confidence | Formula: DFDA_OPEX / TREATY_FUNDING | Unit: rate | Click to view details, calculation & sources\">0.147% (95% CI: 0.1%-0.204%)</a>"
"dfda_opex_pct_of_treaty_funding_latex": "$$\n\\begin{gathered}\nOPEX_{pct} \\\\\n= \\frac{OPEX_{dFDA}}{Funding_{treaty}} \\\\\n= \\frac{\\$40M}{\\$27.2B} \\\\\n= 0.147\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nFunding_{treaty} \\\\\n= Spending_{mil} \\times Reduce_{treaty} \\\\\n= \\$2.72T \\times 1\\% \\\\\n= \\$27.2B\n\\end{gathered}\n$$"
"dfda_opex_platform_maintenance": "<span class=\"parameter-definition\" title=\"Decentralized Framework for Drug Assessment maintenance costs | Unit: USD/year | Core definition\">$15M (95% CI: $10M-$22M)</span>"
"dfda_opex_regulatory": "<span class=\"parameter-definition\" title=\"Decentralized Framework for Drug Assessment regulatory coordination costs | Unit: USD/year | Core definition\">$5M (95% CI: $3M-$8M)</span>"
"dfda_opex_staff": "<span class=\"parameter-definition\" title=\"Decentralized Framework for Drug Assessment staff costs (minimal, AI-assisted) | Unit: USD/year | Core definition\">$10M (95% CI: $7M-$15M)</span>"
"dfda_patients_fundable_annually": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_patients_fundable_annually\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Number of patients fundable annually from dFDA funding at pragmatic trial cost. Source-agnostic counterpart of DIH_PATIENTS_FUNDABLE_ANNUALLY. | Calculated from 2 inputs | ✓ High confidence | Formula: DFDA_TRIAL_SUBSIDIES_ANNUAL / DFDA_PRAGMATIC_TRIAL_COST_PER_PATIENT | Unit: patients/year | Click to view details, calculation & sources\">23.4 million patients/year (95% CI: 9.46 million patients/year-97 million patients/year)</a>"
"dfda_patients_fundable_annually_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_patients_fundable_annually\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Number of patients fundable annually from dFDA funding at pragmatic trial cost. Source-agnostic counterpart of DIH_PATIENTS_FUNDABLE_ANNUALLY. | Calculated from 2 inputs | ✓ High confidence | Formula: DFDA_TRIAL_SUBSIDIES_ANNUAL / DFDA_PRAGMATIC_TRIAL_COST_PER_PATIENT | Unit: patients/year | Click to view details, calculation & sources\">23.4 million (95% CI: 9.46 million-97 million)</a>"
"dfda_patients_fundable_annually_latex": "$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$"
"dfda_pragmatic_trial_cost_per_patient": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_pragmatic_trial_cost_per_patient\" class=\"parameter-link\" data-source-ref=\"pragmatic-trials-cost-advantage\" data-source-type=\"external\" data-confidence=\"medium\" title=\"dFDA pragmatic trial cost per patient. Uses ADAPTABLE trial ($929) as DELIBERATELY CONSERVATIVE central estimate. Ramsberg & Platt (2018) reviewed 108 embedded pragmatic trials; 64 with cost data had median of only $97/patient - our estimate may overstate costs by 10x. Confidence interval spans meta-analysis median to complex chronic disease trials. | ~ Medium confidence | 95% CI: [$97, $3K] | Dist: Lognormal | Unit: USD/patient | Click to view details, calculation & sources\">$929 (95% CI: $97-$3K)</a>"
"dfda_pragmatic_trial_cost_per_patient_cite": "@pragmatic-trials-cost-advantage"
"dfda_queue_clearance_years": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_queue_clearance_years\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Years to explore the entire therapeutic search space with dFDA implementation. At increased discovery rate, finding first treatments for all currently untreatable diseases takes ~36 years instead of ~443. | Calculated from 2 inputs | ? Low confidence | Formula: STATUS_QUO_QUEUE_CLEARANCE_YEARS ÷ DFDA_TRIAL_CAPACITY_MULTIPLIER | Unit: years | Click to view details, calculation & sources\">36 years (95% CI: 11.6 years-77.1 years)</a>"
"dfda_queue_clearance_years_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_queue_clearance_years\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Years to explore the entire therapeutic search space with dFDA implementation. At increased discovery rate, finding first treatments for all currently untreatable diseases takes ~36 years instead of ~443. | Calculated from 2 inputs | ? Low confidence | Formula: STATUS_QUO_QUEUE_CLEARANCE_YEARS ÷ DFDA_TRIAL_CAPACITY_MULTIPLIER | Unit: years | Click to view details, calculation & sources\">36 (95% CI: 11.6-77.1)</a>"
"dfda_queue_clearance_years_latex": "$$\n\\begin{gathered}\nT_{queue,dFDA} \\\\\n= \\frac{T_{queue,SQ}}{k_{capacity}} \\\\\n= \\frac{443}{12.3} \\\\\n= 36\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{queue,SQ} \\\\\n= \\frac{N_{untreated}}{Treatments_{new,ann}} \\\\\n= \\frac{6{,}650}{15} \\\\\n= 443\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$"
"dfda_rd_savings_daily": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_rd_savings_daily\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Daily R&D savings from trial cost reduction (opportunity cost of delay) | Calculated from 1 input | ✓ High confidence | Formula: ANNUAL_RD_SAVINGS ÷ DAYS_PER_YEAR | Unit: USD/day | Click to view details, calculation & sources\">$161M (95% CI: $135M-$200M)</a>"
"dfda_rd_savings_daily_latex": "$$\n\\begin{gathered}\nSavings_{RD,daily} \\\\\n= Benefit_{RD,ann} \\times 0.00274 \\\\\n= \\$58.6B \\times 0.00274 \\\\\n= \\$161M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nBenefit_{RD,ann} \\\\\n= Spending_{trials} \\times Reduce_{pct} \\\\\n= \\$60B \\times 97.7\\% \\\\\n= \\$58.6B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nReduce_{pct} \\\\\n= 1 - \\frac{Cost_{pragmatic,pt}}{Cost_{P3,pt}} \\\\\n= 1 - \\frac{\\$929}{\\$41K} \\\\\n= 97.7\\%\n\\end{gathered}\n$$"
"dfda_roi_rd_only": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_roi_rd_only\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"ROI from Decentralized Framework for Drug Assessment R&D savings only (10-year NPV, most conservative estimate) | Calculated from 2 inputs | ✓ High confidence | Formula: NPV_BENEFIT ÷ NPV_TOTAL_COST | Unit: ratio | Click to view details, calculation & sources\">637 (95% CI: 569-790)</a>"
"dfda_roi_rd_only_latex": "$$\n\\begin{gathered}\nROI_{RD} \\\\\n= \\frac{NPV_{RD}}{Cost_{dFDA,total}} \\\\\n= \\frac{\\$389B}{\\$611M} \\\\\n= 637\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nNPV_{RD} \\\\\n= \\sum_{t=1}^{10} \\frac{Savings_{RD,ann} \\cdot \\frac{\\min(t,5)}{5}}{(1+r)^t}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSavings_{RD,ann} \\\\\n= Benefit_{RD,ann} - OPEX_{dFDA} \\\\\n= \\$58.6B - \\$40M \\\\\n= \\$58.6B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nBenefit_{RD,ann} \\\\\n= Spending_{trials} \\times Reduce_{pct} \\\\\n= \\$60B \\times 97.7\\% \\\\\n= \\$58.6B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nReduce_{pct} \\\\\n= 1 - \\frac{Cost_{pragmatic,pt}}{Cost_{P3,pt}} \\\\\n= 1 - \\frac{\\$929}{\\$41K} \\\\\n= 97.7\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{dFDA,total} \\\\\n= PV_{OPEX} + Cost_{upfront,total} \\\\\n= \\$342M + \\$270M \\\\\n= \\$611M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nPV_{OPEX} \\\\\n= \\frac{T_{horizon}}{OPEX_{total} \\times r_{discount}} \\\\\n= \\frac{10}{\\$40M \\times 3\\%} \\\\\n= \\$342M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{total} \\\\\n= OPEX_{ann} + OPEX_{DIH,ann} \\\\\n= \\$18.9M + \\$21.1M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{upfront,total} \\\\\n= Cost_{upfront} + Cost_{DIH,init} \\\\\n= \\$40M + \\$230M \\\\\n= \\$270M\n\\end{gathered}\n$$"
"dfda_storage_cost_backup_per_patient_monthly": "<span class=\"parameter-definition\" title=\"Backup and redundancy cost per patient per month. For data safety and compliance. | Unit: USD/patient/month | Core definition\">$0.2 (95% CI: $0.1-$0.4)</span>"
"dfda_storage_cost_compute_per_patient_monthly": "<span class=\"parameter-definition\" title=\"Compute and API cost per patient per month. For data processing, correlation analysis, and PIS calculation. | Unit: USD/patient/month | Core definition\">$0.2 (95% CI: $0.1-$0.5)</span>"
"dfda_storage_cost_database_per_patient_monthly": "<span class=\"parameter-definition\" title=\"Database cost per patient per month. For structured data storage and querying. | Unit: USD/patient/month | Core definition\">$0.3 (95% CI: $0.15-$0.6)</span>"
"dfda_storage_cost_raw_per_patient_monthly": "<span class=\"parameter-definition\" title=\"Raw cloud storage cost per patient per month. Based on standard cloud storage rates for ~1GB patient data. | Unit: USD/patient/month | Core definition\">$0.02 (95% CI: $0.01-$0.05)</span>"
"dfda_storage_cost_total_per_patient_annual": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_storage_cost_total_per_patient_annual\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Total infrastructure cost per patient per year. Monthly cost × 12. | Calculated from 1 input | ✓ High confidence | Formula: MONTHLY_COST × 12 | Unit: USD/patient/year | Click to view details, calculation & sources\">$8.64 (95% CI: $4.34-$15)</a>"
"dfda_storage_cost_total_per_patient_annual_latex": "$$\n\\begin{gathered}\nCost_{infra,annual} \\\\\n= Cost_{infra,monthly} \\times 12 \\\\\n= \\$0.72 \\times 12 \\\\\n= \\$8.64\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{infra,monthly} \\\\\n= Cost_{storage,raw} + Cost_{compute} + Cost_{database} \\\\\n+ Cost_{backup} \\\\\n= \\$0.02 + \\$0.2 + \\$0.3 + \\$0.2 \\\\\n= \\$0.72\n\\end{gathered}\n$$"
"dfda_storage_cost_total_per_patient_monthly": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_storage_cost_total_per_patient_monthly\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Total infrastructure cost per patient per month. Sum of storage, compute, database, and backup costs. | Calculated from 4 inputs | ✓ High confidence | Formula: RAW + COMPUTE + DATABASE + BACKUP | Unit: USD/patient/month | Click to view details, calculation & sources\">$0.72 (95% CI: $0.361-$1.29)</a>"
"dfda_storage_cost_total_per_patient_monthly_latex": "$$\n\\begin{gathered}\nCost_{infra,monthly} \\\\\n= Cost_{storage,raw} + Cost_{compute} + Cost_{database} \\\\\n+ Cost_{backup} \\\\\n= \\$0.02 + \\$0.2 + \\$0.3 + \\$0.2 \\\\\n= \\$0.72\n\\end{gathered}\n$$"
"dfda_target_cost_per_patient_usd": "<span class=\"parameter-definition\" title=\"Target cost per patient in USD (same as DFDA_TARGET_COST_PER_PATIENT but in dollars) | Unit: USD/patient | Core definition\">$1K</span>"
"dfda_total_exploration_years": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_total_exploration_years\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Years to test all therapeutic combinations (known safe + emerging modalities) with dFDA capacity | Calculated from 2 inputs | ✓ High confidence | Formula: TOTAL_COMBINATIONS ÷ DFDA_TRIALS_PER_YEAR | Unit: years | Click to view details, calculation & sources\">1.27 thousand years (95% CI: 303 years-3.16 thousand years)</a>"
"dfda_total_exploration_years_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_total_exploration_years\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Years to test all therapeutic combinations (known safe + emerging modalities) with dFDA capacity | Calculated from 2 inputs | ✓ High confidence | Formula: TOTAL_COMBINATIONS ÷ DFDA_TRIALS_PER_YEAR | Unit: years | Click to view details, calculation & sources\">1.27 thousand (95% CI: 303-3.16 thousand)</a>"
"dfda_total_exploration_years_latex": "$$\n\\begin{gathered}\nT_{explore,dFDA} \\\\\n= \\frac{N_{testable}}{Capacity_{trials}} \\\\\n= \\frac{51.5M}{40{,}700} \\\\\n= 1{,}270\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{testable} \\\\\n= N_{combos} + N_{emerging} \\\\\n= 9.5M + 42M \\\\\n= 51.5M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{combos} \\\\\n= N_{safe} \\times N_{diseases,trial} \\\\\n= 9{,}500 \\times 1{,}000 \\\\\n= 9.5M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{emerging} \\\\\n= Combos_{gene} + Combos_{mRNA} + Combos_{epi} + Combos_{cell} \\\\\n= 20M + 20M + 1.5M + 500{,}000 \\\\\n= 42M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCombos_{gene} \\\\\n= N_{genes} \\times N_{diseases,trial} \\\\\n= 20{,}000 \\times 1{,}000 \\\\\n= 20M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCombos_{mRNA} \\\\\n= N_{genes} \\times N_{diseases,trial} \\\\\n= 20{,}000 \\times 1{,}000 \\\\\n= 20M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCombos_{epi} \\\\\n= N_{epi} \\times N_{diseases,trial} \\\\\n= 1{,}500 \\times 1{,}000 \\\\\n= 1.5M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCombos_{cell} \\\\\n= N_{cell} \\times N_{diseases,trial} \\\\\n= 500 \\times 1{,}000 \\\\\n= 500{,}000\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCapacity_{trials} \\\\\n= Trials_{ann,curr} \\times k_{capacity} \\\\\n= 3{,}300 \\times 12.3 \\\\\n= 40{,}700\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$"
"dfda_trials_per_year_capacity": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_trials_per_year_capacity\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Maximum trials per year possible with trial capacity multiplier | Calculated from 2 inputs | ✓ High confidence | Formula: CURRENT_TRIALS × DFDA_TRIAL_CAPACITY_MULTIPLIER | Unit: trials/year | Click to view details, calculation & sources\">40.7 thousand trials/year (95% CI: 16.3 thousand trials/year-170 thousand trials/year)</a>"
"dfda_trials_per_year_capacity_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_trials_per_year_capacity\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Maximum trials per year possible with trial capacity multiplier | Calculated from 2 inputs | ✓ High confidence | Formula: CURRENT_TRIALS × DFDA_TRIAL_CAPACITY_MULTIPLIER | Unit: trials/year | Click to view details, calculation & sources\">40.7 thousand (95% CI: 16.3 thousand-170 thousand)</a>"
"dfda_trials_per_year_capacity_latex": "$$\n\\begin{gathered}\nCapacity_{trials} \\\\\n= Trials_{ann,curr} \\times k_{capacity} \\\\\n= 3{,}300 \\times 12.3 \\\\\n= 40{,}700\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$"
"dfda_trial_capacity_dalys_averted": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_trial_capacity_dalys_averted\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Total DALYs averted from trial capacity increase alone. Calculated as annual global DALY burden × eventually avoidable percentage × treatment acceleration years. Includes both fatal and non-fatal diseases. | Calculated from 3 inputs | ? Low confidence | Formula: GLOBAL_ANNUAL_DALY_BURDEN × EVENTUALLY_AVOIDABLE_DALY_PCT × TREATMENT_ACCELERATION_YEARS | Unit: DALYs | Click to view details, calculation & sources\">543 billion DALYs (95% CI: 330 billion DALYs-864 billion DALYs)</a>"
"dfda_trial_capacity_dalys_averted_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_trial_capacity_dalys_averted\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Total DALYs averted from trial capacity increase alone. Calculated as annual global DALY burden × eventually avoidable percentage × treatment acceleration years. Includes both fatal and non-fatal diseases. | Calculated from 3 inputs | ? Low confidence | Formula: GLOBAL_ANNUAL_DALY_BURDEN × EVENTUALLY_AVOIDABLE_DALY_PCT × TREATMENT_ACCELERATION_YEARS | Unit: DALYs | Click to view details, calculation & sources\">543 billion (95% CI: 330 billion-864 billion)</a>"
"dfda_trial_capacity_dalys_averted_latex": "$$\n\\begin{gathered}\nDALYs_{capacity} \\\\\n= DALYs_{global,ann} \\times Pct_{avoid,DALY} \\times T_{accel} \\\\\n= 2.88B \\times 92.6\\% \\times 204 \\\\\n= 543B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{accel} \\\\\n= T_{first,SQ} \\times \\left(1 - \\frac{1}{k_{capacity}}\\right) \\\\\n= 222 \\times \\left(1 - \\frac{1}{12.3}\\right) \\\\\n= 204\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{first,SQ} \\\\\n= T_{queue,SQ} \\times 0.5 \\\\\n= 443 \\times 0.5 \\\\\n= 222\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{queue,SQ} \\\\\n= \\frac{N_{untreated}}{Treatments_{new,ann}} \\\\\n= \\frac{6{,}650}{15} \\\\\n= 443\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$"
"dfda_trial_capacity_economic_value": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_trial_capacity_economic_value\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Total economic value from trial capacity increase alone. DALYs valued at standard economic rate. | Calculated from 2 inputs | ? Low confidence | Formula: DFDA_TRIAL_CAPACITY_DALYS_AVERTED × STANDARD_QALY_VALUE | Unit: USD | Click to view details, calculation & sources\">$81.5 quadrillion (95% CI: $59.1 quadrillion-$94 quadrillion)</a>"
"dfda_trial_capacity_economic_value_latex": "$$\n\\begin{gathered}\nValue_{capacity} \\\\\n= DALYs_{capacity} \\times Value_{QALY} \\\\\n= 543B \\times \\$150K \\\\\n= \\$81500T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDALYs_{capacity} \\\\\n= DALYs_{global,ann} \\times Pct_{avoid,DALY} \\times T_{accel} \\\\\n= 2.88B \\times 92.6\\% \\times 204 \\\\\n= 543B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{accel} \\\\\n= T_{first,SQ} \\times \\left(1 - \\frac{1}{k_{capacity}}\\right) \\\\\n= 222 \\times \\left(1 - \\frac{1}{12.3}\\right) \\\\\n= 204\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{first,SQ} \\\\\n= T_{queue,SQ} \\times 0.5 \\\\\n= 443 \\times 0.5 \\\\\n= 222\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{queue,SQ} \\\\\n= \\frac{N_{untreated}}{Treatments_{new,ann}} \\\\\n= \\frac{6{,}650}{15} \\\\\n= 443\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$"
"dfda_trial_capacity_lives_saved": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_trial_capacity_lives_saved\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Total eventually avoidable deaths from trial capacity increase alone. Represents first treatments arriving earlier due to faster therapeutic space exploration from increased trial capacity. | Calculated from 2 inputs | ? Low confidence | Formula: ANNUAL_DEATHS × DFDA_TRIAL_CAPACITY_TREATMENT_ACCELERATION_YEARS × AVOIDABLE_PCT | Unit: deaths | Click to view details, calculation & sources\">10.3 billion deaths (95% CI: 6.77 billion deaths-16 billion deaths)</a>"
"dfda_trial_capacity_lives_saved_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_trial_capacity_lives_saved\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Total eventually avoidable deaths from trial capacity increase alone. Represents first treatments arriving earlier due to faster therapeutic space exploration from increased trial capacity. | Calculated from 2 inputs | ? Low confidence | Formula: ANNUAL_DEATHS × DFDA_TRIAL_CAPACITY_TREATMENT_ACCELERATION_YEARS × AVOIDABLE_PCT | Unit: deaths | Click to view details, calculation & sources\">10.3 billion (95% CI: 6.77 billion-16 billion)</a>"
"dfda_trial_capacity_lives_saved_latex": "$$\n\\begin{gathered}\nLives_{capacity} \\\\\n= Deaths_{disease,daily} \\times T_{accel} \\times 338 \\\\\n= 150{,}000 \\times 204 \\times 338 \\\\\n= 10.3B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{accel} \\\\\n= T_{first,SQ} \\times \\left(1 - \\frac{1}{k_{capacity}}\\right) \\\\\n= 222 \\times \\left(1 - \\frac{1}{12.3}\\right) \\\\\n= 204\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{first,SQ} \\\\\n= T_{queue,SQ} \\times 0.5 \\\\\n= 443 \\times 0.5 \\\\\n= 222\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{queue,SQ} \\\\\n= \\frac{N_{untreated}}{Treatments_{new,ann}} \\\\\n= \\frac{6{,}650}{15} \\\\\n= 443\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$"
"dfda_trial_capacity_multiplier": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_trial_capacity_multiplier\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Trial capacity multiplier from dFDA funding capacity vs. current global trial participation | Calculated from 2 inputs | ✓ High confidence | Formula: DFDA_PATIENTS_FUNDABLE_ANNUALLY ÷ CURRENT_TRIAL_SLOTS | Unit: x | Click to view details, calculation & sources\">12.3x (95% CI: 4.2x-61.4x)</a>"
"dfda_trial_capacity_multiplier_latex": "$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$"
"dfda_trial_capacity_plus_efficacy_lag_dalys": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_trial_capacity_plus_efficacy_lag_dalys\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Total DALYs averted from the combined dFDA timeline shift. Calculated as annual global DALY burden × eventually avoidable percentage × timeline shift years. Includes both fatal and non-fatal diseases (WHO GBD methodology). | Calculated from 3 inputs | ? Low confidence | Formula: GLOBAL_ANNUAL_DALY_BURDEN × EVENTUALLY_AVOIDABLE_DALY_PCT × TIMELINE_SHIFT | Unit: DALYs | Click to view details, calculation & sources\">565 billion DALYs (95% CI: 361 billion DALYs-877 billion DALYs)</a>"
"dfda_trial_capacity_plus_efficacy_lag_dalys_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_trial_capacity_plus_efficacy_lag_dalys\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Total DALYs averted from the combined dFDA timeline shift. Calculated as annual global DALY burden × eventually avoidable percentage × timeline shift years. Includes both fatal and non-fatal diseases (WHO GBD methodology). | Calculated from 3 inputs | ? Low confidence | Formula: GLOBAL_ANNUAL_DALY_BURDEN × EVENTUALLY_AVOIDABLE_DALY_PCT × TIMELINE_SHIFT | Unit: DALYs | Click to view details, calculation & sources\">565 billion (95% CI: 361 billion-877 billion)</a>"
"dfda_trial_capacity_plus_efficacy_lag_dalys_latex": "$$\n\\begin{gathered}\nDALYs_{max} \\\\\n= DALYs_{global,ann} \\times Pct_{avoid,DALY} \\times T_{accel,max} \\\\\n= 2.88B \\times 92.6\\% \\times 212 \\\\\n= 565B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nT_{accel,max} = T_{accel} + T_{lag} = 204 + 8.2 = 212\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{accel} \\\\\n= T_{first,SQ} \\times \\left(1 - \\frac{1}{k_{capacity}}\\right) \\\\\n= 222 \\times \\left(1 - \\frac{1}{12.3}\\right) \\\\\n= 204\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{first,SQ} \\\\\n= T_{queue,SQ} \\times 0.5 \\\\\n= 443 \\times 0.5 \\\\\n= 222\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{queue,SQ} \\\\\n= \\frac{N_{untreated}}{Treatments_{new,ann}} \\\\\n= \\frac{6{,}650}{15} \\\\\n= 443\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$"
"dfda_trial_capacity_plus_efficacy_lag_economic_value": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_trial_capacity_plus_efficacy_lag_economic_value\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Total economic value from the combined dFDA timeline shift. DALYs valued at standard economic rate. | Calculated from 2 inputs | ? Low confidence | Formula: DALYS × STANDARD_QALY_VALUE | Unit: USD | Click to view details, calculation & sources\">$84.8 quadrillion (95% CI: $62.4 quadrillion-$97.3 quadrillion)</a>"
"dfda_trial_capacity_plus_efficacy_lag_economic_value_latex": "$$\n\\begin{gathered}\nValue_{max} \\\\\n= DALYs_{max} \\times Value_{QALY} \\\\\n= 565B \\times \\$150K \\\\\n= \\$84800T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDALYs_{max} \\\\\n= DALYs_{global,ann} \\times Pct_{avoid,DALY} \\times T_{accel,max} \\\\\n= 2.88B \\times 92.6\\% \\times 212 \\\\\n= 565B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nT_{accel,max} = T_{accel} + T_{lag} = 204 + 8.2 = 212\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{accel} \\\\\n= T_{first,SQ} \\times \\left(1 - \\frac{1}{k_{capacity}}\\right) \\\\\n= 222 \\times \\left(1 - \\frac{1}{12.3}\\right) \\\\\n= 204\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{first,SQ} \\\\\n= T_{queue,SQ} \\times 0.5 \\\\\n= 443 \\times 0.5 \\\\\n= 222\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{queue,SQ} \\\\\n= \\frac{N_{untreated}}{Treatments_{new,ann}} \\\\\n= \\frac{6{,}650}{15} \\\\\n= 443\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$"
"dfda_trial_capacity_plus_efficacy_lag_lives_saved": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_trial_capacity_plus_efficacy_lag_lives_saved\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Total eventually avoidable deaths from the combined dFDA timeline shift. Represents deaths prevented when cures arrive earlier due to both increased trial capacity and eliminated efficacy lag. | Calculated from 2 inputs | ? Low confidence | Formula: ANNUAL_DEATHS × DFDA_TRIAL_CAPACITY_PLUS_EFFICACY_LAG_YEARS × AVOIDABLE_PCT | Unit: deaths | Click to view details, calculation & sources\">10.7 billion deaths (95% CI: 7.4 billion deaths-16.2 billion deaths)</a>"
"dfda_trial_capacity_plus_efficacy_lag_lives_saved_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_trial_capacity_plus_efficacy_lag_lives_saved\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Total eventually avoidable deaths from the combined dFDA timeline shift. Represents deaths prevented when cures arrive earlier due to both increased trial capacity and eliminated efficacy lag. | Calculated from 2 inputs | ? Low confidence | Formula: ANNUAL_DEATHS × DFDA_TRIAL_CAPACITY_PLUS_EFFICACY_LAG_YEARS × AVOIDABLE_PCT | Unit: deaths | Click to view details, calculation & sources\">10.7 billion (95% CI: 7.4 billion-16.2 billion)</a>"
"dfda_trial_capacity_plus_efficacy_lag_lives_saved_latex": "$$\n\\begin{gathered}\nLives_{max} \\\\\n= Deaths_{disease,daily} \\times T_{accel,max} \\times 338 \\\\\n= 150{,}000 \\times 212 \\times 338 \\\\\n= 10.7B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nT_{accel,max} = T_{accel} + T_{lag} = 204 + 8.2 = 212\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{accel} \\\\\n= T_{first,SQ} \\times \\left(1 - \\frac{1}{k_{capacity}}\\right) \\\\\n= 222 \\times \\left(1 - \\frac{1}{12.3}\\right) \\\\\n= 204\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{first,SQ} \\\\\n= T_{queue,SQ} \\times 0.5 \\\\\n= 443 \\times 0.5 \\\\\n= 222\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{queue,SQ} \\\\\n= \\frac{N_{untreated}}{Treatments_{new,ann}} \\\\\n= \\frac{6{,}650}{15} \\\\\n= 443\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$"
"dfda_trial_capacity_plus_efficacy_lag_suffering_hours": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_trial_capacity_plus_efficacy_lag_suffering_hours\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Hours of suffering eliminated from the combined dFDA timeline shift. Calculated from YLD component of DALYs (39% of total DALYs × hours per year). One-time benefit, not annual recurring. | Calculated from 2 inputs | ? Low confidence | Formula: DFDA_TRIAL_CAPACITY_PLUS_EFFICACY_LAG_DALYS × GLOBAL_YLD_PROPORTION × HOURS_PER_YEAR | Unit: hours | Click to view details, calculation & sources\">1.93 quadrillion hours (95% CI: 1.36 quadrillion hours-2.62 quadrillion hours)</a>"
"dfda_trial_capacity_plus_efficacy_lag_suffering_hours_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_trial_capacity_plus_efficacy_lag_suffering_hours\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Hours of suffering eliminated from the combined dFDA timeline shift. Calculated from YLD component of DALYs (39% of total DALYs × hours per year). One-time benefit, not annual recurring. | Calculated from 2 inputs | ? Low confidence | Formula: DFDA_TRIAL_CAPACITY_PLUS_EFFICACY_LAG_DALYS × GLOBAL_YLD_PROPORTION × HOURS_PER_YEAR | Unit: hours | Click to view details, calculation & sources\">1.93 quadrillion (95% CI: 1.36 quadrillion-2.62 quadrillion)</a>"
"dfda_trial_capacity_plus_efficacy_lag_suffering_hours_latex": "$$\n\\begin{gathered}\nHours_{suffer,max} \\\\\n= DALYs_{max} \\times Pct_{YLD} \\times 8760 \\\\\n= 565B \\times 0.39 \\times 8760 \\\\\n= 1930T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDALYs_{max} \\\\\n= DALYs_{global,ann} \\times Pct_{avoid,DALY} \\times T_{accel,max} \\\\\n= 2.88B \\times 92.6\\% \\times 212 \\\\\n= 565B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nT_{accel,max} = T_{accel} + T_{lag} = 204 + 8.2 = 212\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{accel} \\\\\n= T_{first,SQ} \\times \\left(1 - \\frac{1}{k_{capacity}}\\right) \\\\\n= 222 \\times \\left(1 - \\frac{1}{12.3}\\right) \\\\\n= 204\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{first,SQ} \\\\\n= T_{queue,SQ} \\times 0.5 \\\\\n= 443 \\times 0.5 \\\\\n= 222\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{queue,SQ} \\\\\n= \\frac{N_{untreated}}{Treatments_{new,ann}} \\\\\n= \\frac{6{,}650}{15} \\\\\n= 443\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$"
"dfda_trial_capacity_plus_efficacy_lag_years": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_trial_capacity_plus_efficacy_lag_years\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Average years earlier patients receive treatments due to dFDA. Combines treatment timeline acceleration from increased trial capacity with efficacy lag elimination for treatments already discovered. | Calculated from 2 inputs | ? Low confidence | Formula: DFDA_TRIAL_CAPACITY_TREATMENT_ACCELERATION_YEARS + EFFICACY_LAG_YEARS | Unit: years | Click to view details, calculation & sources\">212 years (95% CI: 135 years-355 years)</a>"
"dfda_trial_capacity_plus_efficacy_lag_years_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_trial_capacity_plus_efficacy_lag_years\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Average years earlier patients receive treatments due to dFDA. Combines treatment timeline acceleration from increased trial capacity with efficacy lag elimination for treatments already discovered. | Calculated from 2 inputs | ? Low confidence | Formula: DFDA_TRIAL_CAPACITY_TREATMENT_ACCELERATION_YEARS + EFFICACY_LAG_YEARS | Unit: years | Click to view details, calculation & sources\">212 (95% CI: 135-355)</a>"
"dfda_trial_capacity_plus_efficacy_lag_years_latex": "$$\nT_{accel,max} = T_{accel} + T_{lag} = 204 + 8.2 = 212\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{accel} \\\\\n= T_{first,SQ} \\times \\left(1 - \\frac{1}{k_{capacity}}\\right) \\\\\n= 222 \\times \\left(1 - \\frac{1}{12.3}\\right) \\\\\n= 204\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{first,SQ} \\\\\n= T_{queue,SQ} \\times 0.5 \\\\\n= 443 \\times 0.5 \\\\\n= 222\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{queue,SQ} \\\\\n= \\frac{N_{untreated}}{Treatments_{new,ann}} \\\\\n= \\frac{6{,}650}{15} \\\\\n= 443\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$"
"dfda_trial_capacity_treatment_acceleration_years": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_trial_capacity_treatment_acceleration_years\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Years earlier the average first treatment arrives due to dFDA's trial capacity increase. Calculated as the status quo timeline reduced by the inverse of the capacity multiplier. Uses only trial capacity multiplier (not combined with valley of death rescue) because additional candidates don't directly speed therapeutic space exploration. | Calculated from 2 inputs | ? Low confidence | Formula: STATUS_QUO_AVG_YEARS_TO_FIRST_TREATMENT × (1 - 1/DFDA_TRIAL_CAPACITY_MULTIPLIER) | Unit: years | Click to view details, calculation & sources\">204 years (95% CI: 123 years-350 years)</a>"
"dfda_trial_capacity_treatment_acceleration_years_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_trial_capacity_treatment_acceleration_years\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Years earlier the average first treatment arrives due to dFDA's trial capacity increase. Calculated as the status quo timeline reduced by the inverse of the capacity multiplier. Uses only trial capacity multiplier (not combined with valley of death rescue) because additional candidates don't directly speed therapeutic space exploration. | Calculated from 2 inputs | ? Low confidence | Formula: STATUS_QUO_AVG_YEARS_TO_FIRST_TREATMENT × (1 - 1/DFDA_TRIAL_CAPACITY_MULTIPLIER) | Unit: years | Click to view details, calculation & sources\">204 (95% CI: 123-350)</a>"
"dfda_trial_capacity_treatment_acceleration_years_latex": "$$\n\\begin{gathered}\nT_{accel} \\\\\n= T_{first,SQ} \\times \\left(1 - \\frac{1}{k_{capacity}}\\right) \\\\\n= 222 \\times \\left(1 - \\frac{1}{12.3}\\right) \\\\\n= 204\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{first,SQ} \\\\\n= T_{queue,SQ} \\times 0.5 \\\\\n= 443 \\times 0.5 \\\\\n= 222\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{queue,SQ} \\\\\n= \\frac{N_{untreated}}{Treatments_{new,ann}} \\\\\n= \\frac{6{,}650}{15} \\\\\n= 443\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$"
"dfda_trial_cost_reduction_factor": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_trial_cost_reduction_factor\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Cost reduction factor projected for dFDA pragmatic trials (traditional Phase 3 cost / dFDA pragmatic cost per patient) | Calculated from 2 inputs | ✓ High confidence | Formula: TRADITIONAL_PHASE3_COST / DFDA_PRAGMATIC_COST | Unit: multiplier | Click to view details, calculation & sources\">44.1x (95% CI: 39.4x-89.1x)</a>"
"dfda_trial_cost_reduction_factor_latex": "$$\n\\begin{gathered}\nk_{reduce} \\\\\n= \\frac{Cost_{P3,pt}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$41K}{\\$929} \\\\\n= 44.1\n\\end{gathered}\n$$"
"dfda_trial_cost_reduction_pct": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_trial_cost_reduction_pct\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Trial cost reduction percentage: 1 - (dFDA pragmatic cost / traditional Phase 3 cost) | Calculated from 2 inputs | ✓ High confidence | Formula: 1 - (DFDA_COST / TRADITIONAL_COST) | Unit: percentage | Click to view details, calculation & sources\">97.7% (95% CI: 97%-99%)</a>"
"dfda_trial_cost_reduction_pct_latex": "$$\n\\begin{gathered}\nReduce_{pct} \\\\\n= 1 - \\frac{Cost_{pragmatic,pt}}{Cost_{P3,pt}} \\\\\n= 1 - \\frac{\\$929}{\\$41K} \\\\\n= 97.7\\%\n\\end{gathered}\n$$"
"dfda_trial_subsidies_annual": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_trial_subsidies_annual\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Annual clinical trial patient subsidies from dFDA funding (total funding minus operational costs) | Calculated from 2 inputs | ✓ High confidence | Formula: DFDA_ANNUAL_TRIAL_FUNDING - DFDA_ANNUAL_OPEX | Unit: USD/year | Click to view details, calculation & sources\">$21.8B (95% CI: $21.7B-$21.8B)</a>"
"dfda_trial_subsidies_annual_latex": "$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$"
"dfda_upfront_build": "<span class=\"parameter-definition\" title=\"Decentralized Framework for Drug Assessment one-time build cost (central estimate) | Unit: USD | Core definition\">$40M</span>"
"dfda_upfront_build_max": "<span class=\"parameter-definition\" title=\"Decentralized Framework for Drug Assessment one-time build cost (high estimate) | Unit: USD | Core definition\">$46M</span>"
"dfda_valley_of_death_rescue_multiplier": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dfda_valley_of_death_rescue_multiplier\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Factor increase in drugs entering development when dFDA eliminates Phase 2/3 cost barrier. Valley-of-death attrition (40%) becomes new drugs, so 1 + 0.40 = 1.4× more drugs. | Calculated from 1 input | ~ Medium confidence | Formula: 1 + VALLEY_OF_DEATH_ATTRITION_PCT | Unit: multiplier | Click to view details, calculation & sources\">1.4x</a>"
"dfda_valley_of_death_rescue_multiplier_latex": "$$\nk_{rescue} = Attrition_{valley} + 1 = 40\\% + 1 = 1.4\n$$"
"dih_npv_annual_opex_initiatives": "<span class=\"parameter-definition\" title=\"DIH broader initiatives annual opex (medium case) | Unit: USD/year | Core definition\">$21.1M (95% CI: $14M-$32M)</span>"
"dih_npv_upfront_cost_initiatives": "<span class=\"parameter-definition\" title=\"DIH broader initiatives upfront cost (medium case) | Unit: USD | Core definition\">$230M (95% CI: $150M-$350M)</span>"
"dih_patients_fundable_annually": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dih_patients_fundable_annually\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Number of patients fundable annually at dFDA pragmatic trial cost. Based on empirical pragmatic trial costs (RECOVERY to PCORnet range). | Calculated from 2 inputs | ✓ High confidence | Formula: TRIAL_SUBSIDIES ÷ DFDA_COST_PER_PATIENT | Unit: patients/year | Click to view details, calculation & sources\">23.4 million patients/year (95% CI: 9.44 million patients/year-96.8 million patients/year)</a>"
"dih_patients_fundable_annually_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dih_patients_fundable_annually\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Number of patients fundable annually at dFDA pragmatic trial cost. Based on empirical pragmatic trial costs (RECOVERY to PCORnet range). | Calculated from 2 inputs | ✓ High confidence | Formula: TRIAL_SUBSIDIES ÷ DFDA_COST_PER_PATIENT | Unit: patients/year | Click to view details, calculation & sources\">23.4 million (95% CI: 9.44 million-96.8 million)</a>"
"dih_patients_fundable_annually_latex": "$$\n\\begin{gathered}\nN_{fundable,ann} \\\\\n= \\frac{Subsidies_{trial,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.7B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{trial,ann} \\\\\n= Treasury_{RD,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.7B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nTreasury_{RD,ann} \\\\\n= Funding_{treaty} - Payout_{bond,ann} - Funding_{political,ann} \\\\\n= \\$27.2B - \\$2.72B - \\$2.72B \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nFunding_{treaty} \\\\\n= Spending_{mil} \\times Reduce_{treaty} \\\\\n= \\$2.72T \\times 1\\% \\\\\n= \\$27.2B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nPayout_{bond,ann} \\\\\n= Funding_{treaty} \\times Pct_{bond} \\\\\n= \\$27.2B \\times 10\\% \\\\\n= \\$2.72B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nFunding_{political,ann} \\\\\n= Funding_{treaty} \\times Pct_{political} \\\\\n= \\$27.2B \\times 10\\% \\\\\n= \\$2.72B\n\\end{gathered}\n$$"
"dih_treasury_medical_research_pct": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dih_treasury_medical_research_pct\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Percentage of treaty funding allocated to medical research (after bond payouts and IAB incentives) | Calculated from 2 inputs | ✓ High confidence | Formula: MEDICAL_RESEARCH_FUNDING / TREATY_FUNDING | Unit: rate | Click to view details, calculation & sources\">80%</a>"
"dih_treasury_medical_research_pct_latex": "$$\n\\begin{gathered}\nPct_{treasury,RD} \\\\\n= \\frac{Treasury_{RD,ann}}{Funding_{treaty}} \\\\\n= \\frac{\\$21.8B}{\\$27.2B} \\\\\n= 80\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nTreasury_{RD,ann} \\\\\n= Funding_{treaty} - Payout_{bond,ann} - Funding_{political,ann} \\\\\n= \\$27.2B - \\$2.72B - \\$2.72B \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nFunding_{treaty} \\\\\n= Spending_{mil} \\times Reduce_{treaty} \\\\\n= \\$2.72T \\times 1\\% \\\\\n= \\$27.2B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nPayout_{bond,ann} \\\\\n= Funding_{treaty} \\times Pct_{bond} \\\\\n= \\$27.2B \\times 10\\% \\\\\n= \\$2.72B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nFunding_{political,ann} \\\\\n= Funding_{treaty} \\times Pct_{political} \\\\\n= \\$27.2B \\times 10\\% \\\\\n= \\$2.72B\n\\end{gathered}\n$$"
"dih_treasury_to_medical_research_annual": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dih_treasury_to_medical_research_annual\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Annual funding for pragmatic clinical trials (treaty funding minus VICTORY Incentive Alignment Bond payouts and IAB political incentive mechanism) | Calculated from 3 inputs | ✓ High confidence | Formula: TREATY_FUNDING - BOND_PAYOUT - IAB_POLITICAL_INCENTIVE_FUNDING | Unit: USD/year | Click to view details, calculation & sources\">$21.8B</a>"
"dih_treasury_to_medical_research_annual_latex": "$$\n\\begin{gathered}\nTreasury_{RD,ann} \\\\\n= Funding_{treaty} - Payout_{bond,ann} - Funding_{political,ann} \\\\\n= \\$27.2B - \\$2.72B - \\$2.72B \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nFunding_{treaty} \\\\\n= Spending_{mil} \\times Reduce_{treaty} \\\\\n= \\$2.72T \\times 1\\% \\\\\n= \\$27.2B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nPayout_{bond,ann} \\\\\n= Funding_{treaty} \\times Pct_{bond} \\\\\n= \\$27.2B \\times 10\\% \\\\\n= \\$2.72B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nFunding_{political,ann} \\\\\n= Funding_{treaty} \\times Pct_{political} \\\\\n= \\$27.2B \\times 10\\% \\\\\n= \\$2.72B\n\\end{gathered}\n$$"
"dih_treasury_trial_subsidies_annual": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dih_treasury_trial_subsidies_annual\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Annual clinical trial patient subsidies (all medical research funds after Decentralized Framework for Drug Assessment operations) | Calculated from 2 inputs | ✓ High confidence | Formula: MEDICAL_RESEARCH_FUNDING - DFDA_OPEX | Unit: USD/year | Click to view details, calculation & sources\">$21.7B (95% CI: $21.7B-$21.7B)</a>"
"dih_treasury_trial_subsidies_annual_latex": "$$\n\\begin{gathered}\nSubsidies_{trial,ann} \\\\\n= Treasury_{RD,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.7B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nTreasury_{RD,ann} \\\\\n= Funding_{treaty} - Payout_{bond,ann} - Funding_{political,ann} \\\\\n= \\$27.2B - \\$2.72B - \\$2.72B \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nFunding_{treaty} \\\\\n= Spending_{mil} \\times Reduce_{treaty} \\\\\n= \\$2.72T \\times 1\\% \\\\\n= \\$27.2B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nPayout_{bond,ann} \\\\\n= Funding_{treaty} \\times Pct_{bond} \\\\\n= \\$27.2B \\times 10\\% \\\\\n= \\$2.72B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nFunding_{political,ann} \\\\\n= Funding_{treaty} \\times Pct_{political} \\\\\n= \\$27.2B \\times 10\\% \\\\\n= \\$2.72B\n\\end{gathered}\n$$"
"dih_treasury_trial_subsidies_pct": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dih_treasury_trial_subsidies_pct\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Percentage of treaty funding going directly to patient trial subsidies | Calculated from 2 inputs | ✓ High confidence | Formula: TRIAL_SUBSIDIES / TREATY_FUNDING | Unit: rate | Click to view details, calculation & sources\">79.9% (95% CI: 79.8%-79.9%)</a>"
"dih_treasury_trial_subsidies_pct_latex": "$$\n\\begin{gathered}\nPct_{subsidies} \\\\\n= \\frac{Subsidies_{trial,ann}}{Funding_{treaty}} \\\\\n= \\frac{\\$21.7B}{\\$27.2B} \\\\\n= 79.9\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{trial,ann} \\\\\n= Treasury_{RD,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.7B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nTreasury_{RD,ann} \\\\\n= Funding_{treaty} - Payout_{bond,ann} - Funding_{political,ann} \\\\\n= \\$27.2B - \\$2.72B - \\$2.72B \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nFunding_{treaty} \\\\\n= Spending_{mil} \\times Reduce_{treaty} \\\\\n= \\$2.72T \\times 1\\% \\\\\n= \\$27.2B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nPayout_{bond,ann} \\\\\n= Funding_{treaty} \\times Pct_{bond} \\\\\n= \\$27.2B \\times 10\\% \\\\\n= \\$2.72B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nFunding_{political,ann} \\\\\n= Funding_{treaty} \\times Pct_{political} \\\\\n= \\$27.2B \\times 10\\% \\\\\n= \\$2.72B\n\\end{gathered}\n$$"
"diseases_without_effective_treatment": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-diseases_without_effective_treatment\" class=\"parameter-link\" data-source-ref=\"rare-disease-only-5pct-have-treatment\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Number of diseases without effective treatment. 95% of 7,000 rare diseases lack FDA-approved treatment (per Orphanet 2024). This represents the therapeutic search space that remains unexplored. | Calculated from 1 input | ~ Medium confidence | Formula: RARE_DISEASES_COUNT_GLOBAL × 0.95 | Unit: diseases | Click to view details, calculation & sources\">6.65 thousand diseases (95% CI: 5.7 thousand diseases-8.24 thousand diseases)</a>"
"diseases_without_effective_treatment_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-diseases_without_effective_treatment\" class=\"parameter-link\" data-source-ref=\"rare-disease-only-5pct-have-treatment\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Number of diseases without effective treatment. 95% of 7,000 rare diseases lack FDA-approved treatment (per Orphanet 2024). This represents the therapeutic search space that remains unexplored. | Calculated from 1 input | ~ Medium confidence | Formula: RARE_DISEASES_COUNT_GLOBAL × 0.95 | Unit: diseases | Click to view details, calculation & sources\">6.65 thousand (95% CI: 5.7 thousand-8.24 thousand)</a>"
"diseases_without_effective_treatment_latex": "$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$"
"disease_burden_gdp_drag_pct": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-disease_burden_gdp_drag_pct\" class=\"parameter-link\" data-source-ref=\"disease-economic-burden-109t\" data-source-type=\"external\" data-confidence=\"high\" title=\"Fraction of GDP currently lost to disease (productivity losses + medical costs diverted from productive use). $5T productivity loss + $9.9T direct medical costs = $14.9T on $115T GDP = ~13%. As diseases are progressively cured, this drag is recovered as GDP growth. This is the missing factor that makes the treaty trajectory look like a singularity rather than a modest improvement. | ✓ High confidence | Dist: Fixed | Unit: percent | Click to view details, calculation & sources\">13%</a>"
"disease_burden_gdp_drag_pct_cite": "@disease-economic-burden-109t"
"disease_related_caregiver_pct": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-disease_related_caregiver_pct\" class=\"parameter-link\" data-source-ref=\"disease-related-caregiving-estimate\" data-source-type=\"definition\" data-confidence=\"high\" title=\"Percentage of caregiving for treatable disease conditions (vs aging, disability, children) | ✓ High confidence | Unit: rate | Click to view details, calculation & sources\">40%</a>"
"disease_vs_terrorism_deaths_ratio": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-disease_vs_terrorism_deaths_ratio\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Ratio of annual disease deaths to 9/11 terrorism deaths | Calculated from 2 inputs | ✓ High confidence | Formula: ANNUAL_DISEASE_DEATHS ÷ 911_DEATHS | Unit: ratio | Click to view details, calculation & sources\">18.4k (95% CI: 15.6k-21.1k)</a>"
"disease_vs_terrorism_deaths_ratio_latex": "$$\n\\begin{gathered}\nRatio_{dis:terror} \\\\\n= \\frac{Deaths_{curable,ann}}{Deaths_{9/11}} \\\\\n= \\frac{55M}{3{,}000} \\\\\n= 18{,}400\n\\end{gathered}\n$$"
"disease_vs_war_deaths_ratio": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-disease_vs_war_deaths_ratio\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Ratio of annual disease deaths to war deaths | Calculated from 2 inputs | ✓ High confidence | Formula: ANNUAL_DISEASE_DEATHS ÷ WAR_DEATHS | Unit: ratio | Click to view details, calculation & sources\">225 (95% CI: 210-239)</a>"
"disease_vs_war_deaths_ratio_latex": "$$\n\\begin{gathered}\nRatio_{dis:war} \\\\\n= \\frac{Deaths_{curable,ann}}{Deaths_{conflict}} \\\\\n= \\frac{55M}{245{,}000} \\\\\n= 225\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDeaths_{conflict} \\\\\n= Deaths_{combat} + Deaths_{state} + Deaths_{terror} \\\\\n= 234{,}000 + 2{,}700 + 8{,}300 \\\\\n= 245{,}000\n\\end{gathered}\n$$"
"dividend_coverage_factor": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dividend_coverage_factor\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Coverage factor of treaty funding vs Decentralized Framework for Drug Assessment opex (sustainability margin) | Calculated from 2 inputs | ✓ High confidence | Formula: TREATY_FUNDING ÷ DFDA_OPEX | Unit: ratio | Click to view details, calculation & sources\">680 (95% CI: 489-995)</a>"
"dividend_coverage_factor_latex": "$$\n\\begin{gathered}\nk_{coverage} \\\\\n= \\frac{Funding_{treaty}}{OPEX_{dFDA}} \\\\\n= \\frac{\\$27.2B}{\\$40M} \\\\\n= 680\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nFunding_{treaty} \\\\\n= Spending_{mil} \\times Reduce_{treaty} \\\\\n= \\$2.72T \\times 1\\% \\\\\n= \\$27.2B\n\\end{gathered}\n$$"
"dot_value_of_statistical_life": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-dot_value_of_statistical_life\" class=\"parameter-link\" data-source-ref=\"dot-vsl-2024\" data-source-type=\"external\" data-confidence=\"high\" title=\"DOT Value of Statistical Life (2024). Used by federal agencies to evaluate safety regulations and quantify the economic value of mortality risk reductions. | ✓ High confidence | Dist: Fixed | Unit: USD | Click to view details, calculation & sources\">$13.7M</a>"
"dot_value_of_statistical_life_cite": "@dot-vsl-2024"
"drugs_approved_since_1962": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-drugs_approved_since_1962\" class=\"parameter-link\" data-source-ref=\"global-new-drug-approvals-50-annually\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Estimated total drugs approved globally since 1962 (62 years × average approval rate). Conservative: uses current rate, actual historical rate was lower in 1960s-80s. | Calculated from 1 input | ~ Medium confidence | Formula: APPROVALS_PER_YEAR × 62 | Unit: drugs | Click to view details, calculation & sources\">3.1 thousand drugs (95% CI: 2.79 thousand drugs-3.5 thousand drugs)</a>"
"drugs_approved_since_1962_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-drugs_approved_since_1962\" class=\"parameter-link\" data-source-ref=\"global-new-drug-approvals-50-annually\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Estimated total drugs approved globally since 1962 (62 years × average approval rate). Conservative: uses current rate, actual historical rate was lower in 1960s-80s. | Calculated from 1 input | ~ Medium confidence | Formula: APPROVALS_PER_YEAR × 62 | Unit: drugs | Click to view details, calculation & sources\">3.1 thousand (95% CI: 2.79 thousand-3.5 thousand)</a>"
"drugs_approved_since_1962_latex": "$$\n\\begin{gathered}\nN_{drugs,62} \\\\\n= Drugs_{ann,curr} \\times 62 \\\\\n= 50 \\times 62 \\\\\n= 3{,}100\n\\end{gathered}\n$$"
"drug_cost_increase_1980s_to_current_multiplier": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-drug_cost_increase_1980s_to_current_multiplier\" class=\"parameter-link\" data-source-ref=\"pre-1962-drug-costs-timeline\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Drug development cost increase from 1980s to current | Calculated from 2 inputs | ✓ High confidence | Formula: PHARMA_DRUG_DEVELOPMENT_COST_CURRENT ÷ DRUG_DEVELOPMENT_COST_1980S | Unit: x | Click to view details, calculation & sources\">13.4x (95% CI: 11.9x-14.7x)</a>"
"drug_cost_increase_1980s_to_current_multiplier_latex": "$$\n\\begin{gathered}\nk_{cost,80s} \\\\\n= \\frac{Cost_{dev,curr}}{Cost_{dev,80s}} \\\\\n= \\frac{\\$2.6B}{\\$194M} \\\\\n= 13.4\n\\end{gathered}\n$$"
"drug_cost_increase_pre1962_to_current_multiplier": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-drug_cost_increase_pre1962_to_current_multiplier\" class=\"parameter-link\" data-source-ref=\"pre-1962-drug-costs-baily-1972\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Drug development cost increase from pre-1962 to current | Calculated from 2 inputs | ✓ High confidence | Formula: PHARMA_DRUG_DEVELOPMENT_COST_CURRENT ÷ PRE_1962_DRUG_DEVELOPMENT_COST_2024_USD | Unit: x | Click to view details, calculation & sources\">105x (95% CI: 90.6x-119x)</a>"
"drug_cost_increase_pre1962_to_current_multiplier_latex": "$$\n\\begin{gathered}\nk_{cost,pre62} \\\\\n= \\frac{Cost_{dev,curr}}{Cost_{pre62,24}} \\\\\n= \\frac{\\$2.6B}{\\$24.7M} \\\\\n= 105\n\\end{gathered}\n$$"
"drug_development_cost_1980s": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-drug_development_cost_1980s\" class=\"parameter-link\" data-source-ref=\"pre-1962-drug-costs-timeline\" data-source-type=\"external\" data-confidence=\"high\" title=\"Drug development cost in 1980s (compounded to approval, 1990 dollars) | ✓ High confidence | 95% CI: [$146M, $242M] | Dist: Lognormal | Unit: USD | Click to view details, calculation & sources\">$194M (95% CI: $146M-$242M)</a>"
"drug_development_cost_1980s_cite": "@pre-1962-drug-costs-timeline"
"drug_discovery_to_approval_years": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-drug_discovery_to_approval_years\" class=\"parameter-link\" data-source-ref=\"bio-clinical-development-2021\" data-source-type=\"external\" data-confidence=\"high\" title=\"Full drug development timeline from discovery to FDA approval. Typical range is 12-15 years based on BIO 2021 and PMC meta-analyses. Breakdown: preclinical 4-6 years + clinical 10.5 years. Using 14 years as central estimate. | ✓ High confidence | 95% CI: [12 years, 17 years] | Unit: years | Click to view details, calculation & sources\">14 years (95% CI: 12 years-17 years)</a>"
"drug_discovery_to_approval_years_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-drug_discovery_to_approval_years\" class=\"parameter-link\" data-source-ref=\"bio-clinical-development-2021\" data-source-type=\"external\" data-confidence=\"high\" title=\"Full drug development timeline from discovery to FDA approval. Typical range is 12-15 years based on BIO 2021 and PMC meta-analyses. Breakdown: preclinical 4-6 years + clinical 10.5 years. Using 14 years as central estimate. | ✓ High confidence | 95% CI: [12 years, 17 years] | Unit: years | Click to view details, calculation & sources\">14 (95% CI: 12-17)</a>"
"drug_discovery_to_approval_years_cite": "@bio-clinical-development-2021"
"drug_disease_combinations_possible": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-drug_disease_combinations_possible\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Total possible drug-disease combinations using existing safe compounds | Calculated from 2 inputs | ✓ High confidence | Formula: SAFE_COMPOUNDS × DISEASES | Unit: combinations | Click to view details, calculation & sources\">9.5 million combinations</a>"
"drug_disease_combinations_possible_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-drug_disease_combinations_possible\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Total possible drug-disease combinations using existing safe compounds | Calculated from 2 inputs | ✓ High confidence | Formula: SAFE_COMPOUNDS × DISEASES | Unit: combinations | Click to view details, calculation & sources\">9.5 million</a>"
"drug_disease_combinations_possible_latex": "$$\n\\begin{gathered}\nN_{combos} \\\\\n= N_{safe} \\times N_{diseases,trial} \\\\\n= 9{,}500 \\times 1{,}000 \\\\\n= 9.5M\n\\end{gathered}\n$$"
"drug_repurposing_success_rate": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-drug_repurposing_success_rate\" class=\"parameter-link\" data-source-ref=\"drug-repurposing-rate\" data-source-type=\"external\" data-confidence=\"high\" title=\"Percentage of drugs that gain at least one new indication after initial approval | ✓ High confidence | Unit: percentage | Click to view details, calculation & sources\">30%</a>"
"drug_repurposing_success_rate_cite": "@drug-repurposing-rate"
"economic_multiplier_education_investment": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-economic_multiplier_education_investment\" class=\"parameter-link\" data-source-ref=\"education-investment-economic-multiplier\" data-source-type=\"external\" data-confidence=\"high\" title=\"Economic multiplier for education investment (2.1x ROI) | ✓ High confidence | Unit: x | Click to view details, calculation & sources\">2.1x</a>"
"economic_multiplier_education_investment_cite": "@education-investment-economic-multiplier"
"economic_multiplier_healthcare_investment": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-economic_multiplier_healthcare_investment\" class=\"parameter-link\" data-source-ref=\"healthcare-investment-economic-multiplier\" data-source-type=\"external\" data-confidence=\"high\" title=\"Economic multiplier for healthcare investment (4.3x ROI). Literature range 3.0-6.0×. | ✓ High confidence | 95% CI: [3x, 6x] | Dist: Lognormal | Unit: x | Click to view details, calculation & sources\">4.3x (95% CI: 3x-6x)</a>"
"economic_multiplier_healthcare_investment_cite": "@healthcare-investment-economic-multiplier"
"economic_multiplier_infrastructure_investment": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-economic_multiplier_infrastructure_investment\" class=\"parameter-link\" data-source-ref=\"infrastructure-investment-economic-multiplier\" data-source-type=\"external\" data-confidence=\"high\" title=\"Economic multiplier for infrastructure investment (1.6x ROI) | ✓ High confidence | Unit: x | Click to view details, calculation & sources\">1.6x</a>"
"economic_multiplier_infrastructure_investment_cite": "@infrastructure-investment-economic-multiplier"
"economic_multiplier_military_spending": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-economic_multiplier_military_spending\" class=\"parameter-link\" data-source-ref=\"military-spending-economic-multiplier\" data-source-type=\"external\" data-confidence=\"high\" title=\"Economic multiplier for military spending (0.6x ROI). Literature range 0.4-1.0×. | ✓ High confidence | 95% CI: [0.4x, 0.9x] | Dist: Lognormal | Unit: x | Click to view details, calculation & sources\">0.6x (95% CI: 0.4x-0.9x)</a>"
"economic_multiplier_military_spending_cite": "@military-spending-economic-multiplier"
"efficacy_lag_cumulative_excess_cost": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-efficacy_lag_cumulative_excess_cost\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Cumulative Phase 2/3 efficacy testing cost since 1962. Uses direct Phase 2/3 cost per drug - this is a LOWER BOUND because it excludes opportunity cost of delays, compounds abandoned due to cost barrier, and regulatory overhead. | Calculated from 2 inputs | ~ Medium confidence | Formula: PHASE_2_3_COST × DRUGS_APPROVED | Unit: USD | Click to view details, calculation & sources\">$4.84T (95% CI: $3.42T-$6.62T)</a>"
"efficacy_lag_cumulative_excess_cost_latex": "$$\n\\begin{gathered}\nCost_{eff,cumul} \\\\\n= Cost_{P2+P3} \\times N_{drugs,62} \\\\\n= \\$1.56B \\times 3{,}100 \\\\\n= \\$4.84T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{drugs,62} \\\\\n= Drugs_{ann,curr} \\times 62 \\\\\n= 50 \\times 62 \\\\\n= 3{,}100\n\\end{gathered}\n$$"
"efficacy_lag_deaths_911_equivalents": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-efficacy_lag_deaths_911_equivalents\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Total deaths from efficacy lag expressed in 9/11 equivalents. Makes the mortality cost viscerally understandable: how many September 11ths worth of deaths did the 1962 efficacy requirements cause? | Calculated from 2 inputs | ~ Medium confidence | Formula: EXISTING_DRUGS_EFFICACY_LAG_DEATHS_TOTAL ÷ SEPT_11_DEATHS | Unit: 9/11s | Click to view details, calculation & sources\">34.1 thousand 9/11s (95% CI: 12.4 thousand 9/11s-71.8 thousand 9/11s)</a>"
"efficacy_lag_deaths_911_equivalents_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-efficacy_lag_deaths_911_equivalents\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Total deaths from efficacy lag expressed in 9/11 equivalents. Makes the mortality cost viscerally understandable: how many September 11ths worth of deaths did the 1962 efficacy requirements cause? | Calculated from 2 inputs | ~ Medium confidence | Formula: EXISTING_DRUGS_EFFICACY_LAG_DEATHS_TOTAL ÷ SEPT_11_DEATHS | Unit: 9/11s | Click to view details, calculation & sources\">34.1 thousand (95% CI: 12.4 thousand-71.8 thousand)</a>"
"efficacy_lag_deaths_911_equivalents_latex": "$$\n\\begin{gathered}\nN_{9/11,equiv} \\\\\n= \\frac{Deaths_{lag,total}}{N_{9/11}} \\\\\n= \\frac{102M}{2{,}980} \\\\\n= 34{,}100\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDeaths_{lag,total} \\\\\n= Lives_{saved,annual} \\times T_{lag} \\\\\n= 12.4M \\times 8.2 \\\\\n= 102M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLives_{saved,annual} \\\\\n= \\frac{LY_{saved,annual}}{T_{ext}} \\\\\n= \\frac{149M}{12} \\\\\n= 12.4M\n\\end{gathered}\n$$"
"efficacy_lag_treatment_delay_yld_annual": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-efficacy_lag_treatment_delay_yld_annual\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Annual YLD from treatment delay: patients receiving chronic disease treatment would have collectively avoided this disability if treatments were available 8.2 years earlier. Represents morbidity burden for treatment beneficiaries (distinct from mortality burden). | Calculated from 3 inputs | ? Low confidence | Formula: PATIENTS × EFFICACY_LAG × DISABILITY_REDUCTION | Unit: DALYs | Click to view details, calculation & sources\">2.01 billion DALYs (95% CI: 661 million DALYs-4.41 billion DALYs)</a>"
"efficacy_lag_treatment_delay_yld_annual_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-efficacy_lag_treatment_delay_yld_annual\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Annual YLD from treatment delay: patients receiving chronic disease treatment would have collectively avoided this disability if treatments were available 8.2 years earlier. Represents morbidity burden for treatment beneficiaries (distinct from mortality burden). | Calculated from 3 inputs | ? Low confidence | Formula: PATIENTS × EFFICACY_LAG × DISABILITY_REDUCTION | Unit: DALYs | Click to view details, calculation & sources\">2.01 billion (95% CI: 661 million-4.41 billion)</a>"
"efficacy_lag_treatment_delay_yld_annual_latex": "$$\n\\begin{gathered}\nYLD_{treat\\_delay} \\\\\n= N_{treated} \\times T_{lag} \\times \\Delta DW_{treat} \\\\\n= 982M \\times 8.2 \\times 0.25 \\\\\n= 2.01B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{treated} \\\\\n= DOT_{chronic} \\times 0.000767 \\\\\n= 1.28T \\times 0.000767 \\\\\n= 982M\n\\end{gathered}\n$$"
"efficacy_lag_years": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-efficacy_lag_years\" class=\"parameter-link\" data-source-ref=\"bio-clinical-development-2021\" data-source-type=\"external\" data-peer-reviewed=\"true\" data-confidence=\"medium\" title=\"Regulatory delay for efficacy testing (Phase II/III) post-safety verification. Based on BIO 2021 industry survey. Note: This is for drugs that COMPLETE the pipeline - survivor bias means actual delay for any given disease may be longer if candidates fail and must restart. | ~ Medium confidence | \U0001F4CA Peer-reviewed | Dist: Normal (SE: 2 years) | Updated: 2021 | Formula: TOTAL_TIME_TO_MARKET - PHASE_1_DURATION | Unit: years | Click to view details, calculation & sources\">8.2 years (95% CI: 4.85 years-11.5 years)</a>"
"efficacy_lag_years_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-efficacy_lag_years\" class=\"parameter-link\" data-source-ref=\"bio-clinical-development-2021\" data-source-type=\"external\" data-peer-reviewed=\"true\" data-confidence=\"medium\" title=\"Regulatory delay for efficacy testing (Phase II/III) post-safety verification. Based on BIO 2021 industry survey. Note: This is for drugs that COMPLETE the pipeline - survivor bias means actual delay for any given disease may be longer if candidates fail and must restart. | ~ Medium confidence | \U0001F4CA Peer-reviewed | Dist: Normal (SE: 2 years) | Updated: 2021 | Formula: TOTAL_TIME_TO_MARKET - PHASE_1_DURATION | Unit: years | Click to view details, calculation & sources\">8.2 (95% CI: 4.85-11.5)</a>"
"efficacy_lag_years_cite": "@bio-clinical-development-2021"
"emerging_modality_combinations": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-emerging_modality_combinations\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Total emerging modality combinations (gene therapy + mRNA + epigenetics + cell therapy) | Calculated from 4 inputs | ✓ High confidence | Formula: GENE + MRNA + EPIGENETIC + CELL | Unit: combinations | Click to view details, calculation & sources\">42 million combinations</a>"
"emerging_modality_combinations_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-emerging_modality_combinations\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Total emerging modality combinations (gene therapy + mRNA + epigenetics + cell therapy) | Calculated from 4 inputs | ✓ High confidence | Formula: GENE + MRNA + EPIGENETIC + CELL | Unit: combinations | Click to view details, calculation & sources\">42 million</a>"
"emerging_modality_combinations_latex": "$$\n\\begin{gathered}\nN_{emerging} \\\\\n= Combos_{gene} + Combos_{mRNA} + Combos_{epi} + Combos_{cell} \\\\\n= 20M + 20M + 1.5M + 500{,}000 \\\\\n= 42M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCombos_{gene} \\\\\n= N_{genes} \\times N_{diseases,trial} \\\\\n= 20{,}000 \\times 1{,}000 \\\\\n= 20M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCombos_{mRNA} \\\\\n= N_{genes} \\times N_{diseases,trial} \\\\\n= 20{,}000 \\times 1{,}000 \\\\\n= 20M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCombos_{epi} \\\\\n= N_{epi} \\times N_{diseases,trial} \\\\\n= 1{,}500 \\times 1{,}000 \\\\\n= 1.5M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCombos_{cell} \\\\\n= N_{cell} \\times N_{diseases,trial} \\\\\n= 500 \\times 1{,}000 \\\\\n= 500{,}000\n\\end{gathered}\n$$"
"epigenetic_disease_combinations": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-epigenetic_disease_combinations\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Epigenetic reprogramming target-disease combinations | Calculated from 2 inputs | ✓ High confidence | Formula: EPIGENETIC_TARGETS × DISEASES | Unit: combinations | Click to view details, calculation & sources\">1.5 million combinations</a>"
"epigenetic_disease_combinations_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-epigenetic_disease_combinations\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Epigenetic reprogramming target-disease combinations | Calculated from 2 inputs | ✓ High confidence | Formula: EPIGENETIC_TARGETS × DISEASES | Unit: combinations | Click to view details, calculation & sources\">1.5 million</a>"
"epigenetic_disease_combinations_latex": "$$\n\\begin{gathered}\nCombos_{epi} \\\\\n= N_{epi} \\times N_{diseases,trial} \\\\\n= 1{,}500 \\times 1{,}000 \\\\\n= 1.5M\n\\end{gathered}\n$$"
"epigenetic_targets_count": "<span class=\"parameter-definition\" title=\"Druggable epigenetic targets (HDACs, DNMTs, histone modifiers, bromodomains) | Unit: targets | Core definition\">1.5 thousand targets (95% CI: 1 thousand targets-2 thousand targets)</span>"
"epigenetic_targets_count_nounit": "<span class=\"parameter-definition\" title=\"Druggable epigenetic targets (HDACs, DNMTs, histone modifiers, bromodomains) | Unit: targets | Core definition\">1.5 thousand (95% CI: 1 thousand-2 thousand)</span>"
"eventually_avoidable_daly_pct": "<span class=\"parameter-definition\" title=\"Percentage of DALYs that are eventually avoidable with sufficient biomedical research. Uses same methodology as EVENTUALLY_AVOIDABLE_DEATH_PCT. Most non-fatal chronic conditions (arthritis, depression, chronic pain) are also addressable through research, so the percentage is similar to deaths. | Unit: percentage | Core definition\">92.6% (95% CI: 50%-98%)</span>"
"eventually_avoidable_death_pct": "<span class=\"parameter-definition\" title=\"Percentage of deaths that are eventually avoidable with sufficient biomedical research and technological advancement. Central estimate ~92% based on ~7.9% fundamentally unavoidable (primarily accidents). Wide uncertainty reflects debate over: (1) aging as addressable vs. fundamental, (2) asymptotic difficulty of last diseases, (3) multifactorial disease complexity. | Unit: percentage | Core definition\">92.6% (95% CI: 50%-98%)</span>"
"existing_drugs_efficacy_lag_deaths_total": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-existing_drugs_efficacy_lag_deaths_total\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Total deaths from delaying existing drugs over 8.2-year efficacy lag. One-time impact of eliminating Phase 2-4 testing delay for drugs already approved 1962-2024. Based on Lichtenberg (2019) estimate of 12M lives saved annually × 8.2 years efficacy lag. Excludes innovation acceleration effects. | Calculated from 2 inputs | ~ Medium confidence | Formula: PHARMA_LIVES_SAVED_ANNUAL × EFFICACY_LAG_YEARS | Unit: deaths | Click to view details, calculation & sources\">102 million deaths (95% CI: 36.9 million deaths-214 million deaths)</a>"
"existing_drugs_efficacy_lag_deaths_total_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-existing_drugs_efficacy_lag_deaths_total\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Total deaths from delaying existing drugs over 8.2-year efficacy lag. One-time impact of eliminating Phase 2-4 testing delay for drugs already approved 1962-2024. Based on Lichtenberg (2019) estimate of 12M lives saved annually × 8.2 years efficacy lag. Excludes innovation acceleration effects. | Calculated from 2 inputs | ~ Medium confidence | Formula: PHARMA_LIVES_SAVED_ANNUAL × EFFICACY_LAG_YEARS | Unit: deaths | Click to view details, calculation & sources\">102 million (95% CI: 36.9 million-214 million)</a>"
"existing_drugs_efficacy_lag_deaths_total_latex": "$$\n\\begin{gathered}\nDeaths_{lag,total} \\\\\n= Lives_{saved,annual} \\times T_{lag} \\\\\n= 12.4M \\times 8.2 \\\\\n= 102M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLives_{saved,annual} \\\\\n= \\frac{LY_{saved,annual}}{T_{ext}} \\\\\n= \\frac{149M}{12} \\\\\n= 12.4M\n\\end{gathered}\n$$"
"existing_drugs_efficacy_lag_economic_loss": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-existing_drugs_efficacy_lag_economic_loss\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Total economic loss from delaying existing drugs over 8.2-year efficacy lag. One-time benefit of eliminating Phase 2-4 delay. Excludes innovation acceleration effects. | Calculated from 4 inputs | ~ Medium confidence | Formula: DEATHS_TOTAL × YLL × VSLY | Unit: USD | Click to view details, calculation & sources\">$259T (95% CI: $68.9T-$655T)</a>"
"existing_drugs_efficacy_lag_economic_loss_latex": "$$\n\\begin{gathered}\nLoss_{lag} \\\\\n= Deaths_{lag,total} \\times (LE_{global} - Age_{death,delay}) \\times Value_{QALY} \\\\\n= 102M \\times (79 - 62) \\times \\$150K \\\\\n= \\$259T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDeaths_{lag,total} \\\\\n= Lives_{saved,annual} \\times T_{lag} \\\\\n= 12.4M \\times 8.2 \\\\\n= 102M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLives_{saved,annual} \\\\\n= \\frac{LY_{saved,annual}}{T_{ext}} \\\\\n= \\frac{149M}{12} \\\\\n= 12.4M\n\\end{gathered}\n$$"
"expert_decision_accuracy": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-expert_decision_accuracy\" class=\"parameter-link\" data-source-ref=\"surowiecki-2004\" data-source-type=\"external\" data-confidence=\"high\" title=\"Expert accuracy on Who Wants to Be a Millionaire phone-a-friend lifeline. Credentialed expert picked the correct answer 65% of the time (Surowiecki 2004). Used as baseline for conventional fund manager / committee allocation. | ✓ High confidence | Dist: Fixed | Unit: percent | Click to view details, calculation & sources\">65%</a>"
"expert_decision_accuracy_cite": "@surowiecki-2004"
"exploration_ratio": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-exploration_ratio\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Fraction of possible drug-disease space actually tested (<1%) | Calculated from 2 inputs | ✓ High confidence | Formula: TESTED / POSSIBLE | Unit: percentage | Click to view details, calculation & sources\">0.342% (95% CI: 0%-1%)</a>"
"exploration_ratio_latex": "$$\n\\begin{gathered}\nRatio_{explore} \\\\\n= \\frac{N_{tested}}{N_{combos}} \\\\\n= \\frac{32{,}500}{9.5M} \\\\\n= 0.342\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{combos} \\\\\n= N_{safe} \\times N_{diseases,trial} \\\\\n= 9{,}500 \\times 1{,}000 \\\\\n= 9.5M\n\\end{gathered}\n$$"
"family_office_investment_min": "<span class=\"parameter-definition\" title=\"Minimum investment for family offices | Unit: USD | Core definition\">$5M</span>"
"fda_approved_products_count": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-fda_approved_products_count\" class=\"parameter-link\" data-source-ref=\"fda-approved-products-20k\" data-source-type=\"external\" data-confidence=\"high\" title=\"Total FDA-approved drug products in the U.S. | ✓ High confidence | Unit: products | Click to view details, calculation & sources\">20 thousand products</a>"
"fda_approved_products_count_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-fda_approved_products_count\" class=\"parameter-link\" data-source-ref=\"fda-approved-products-20k\" data-source-type=\"external\" data-confidence=\"high\" title=\"Total FDA-approved drug products in the U.S. | ✓ High confidence | Unit: products | Click to view details, calculation & sources\">20 thousand</a>"
"fda_approved_products_count_cite": "@fda-approved-products-20k"
"fda_approved_unique_active_ingredients": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-fda_approved_unique_active_ingredients\" class=\"parameter-link\" data-source-ref=\"fda-approved-products-20k\" data-source-type=\"external\" data-confidence=\"high\" title=\"Unique active pharmaceutical ingredients in FDA-approved products (midpoint of 1,300-2,000 range) | ✓ High confidence | 95% CI: [1.3 thousand compounds, 2 thousand compounds] | Dist: Uniform | Unit: compounds | Click to view details, calculation & sources\">1.65 thousand compounds (95% CI: 1.3 thousand compounds-2 thousand compounds)</a>"
"fda_approved_unique_active_ingredients_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-fda_approved_unique_active_ingredients\" class=\"parameter-link\" data-source-ref=\"fda-approved-products-20k\" data-source-type=\"external\" data-confidence=\"high\" title=\"Unique active pharmaceutical ingredients in FDA-approved products (midpoint of 1,300-2,000 range) | ✓ High confidence | 95% CI: [1.3 thousand compounds, 2 thousand compounds] | Dist: Uniform | Unit: compounds | Click to view details, calculation & sources\">1.65 thousand (95% CI: 1.3 thousand-2 thousand)</a>"
"fda_approved_unique_active_ingredients_cite": "@fda-approved-products-20k"
"fda_gras_substances_count": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-fda_gras_substances_count\" class=\"parameter-link\" data-source-ref=\"fda-gras-list-count\" data-source-type=\"external\" data-confidence=\"high\" title=\"FDA Generally Recognized as Safe (GRAS) substances (midpoint of 570-700 range) | ✓ High confidence | 95% CI: [570 substances, 700 substances] | Dist: Uniform | Unit: substances | Click to view details, calculation & sources\">635 substances (95% CI: 570 substances-700 substances)</a>"
"fda_gras_substances_count_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-fda_gras_substances_count\" class=\"parameter-link\" data-source-ref=\"fda-gras-list-count\" data-source-type=\"external\" data-confidence=\"high\" title=\"FDA Generally Recognized as Safe (GRAS) substances (midpoint of 570-700 range) | ✓ High confidence | 95% CI: [570 substances, 700 substances] | Dist: Uniform | Unit: substances | Click to view details, calculation & sources\">635 (95% CI: 570-700)</a>"
"fda_gras_substances_count_cite": "@fda-gras-list-count"
"fda_phase_1_to_approval_years": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-fda_phase_1_to_approval_years\" class=\"parameter-link\" data-source-ref=\"bio-clinical-development-2021\" data-source-type=\"external\" data-confidence=\"high\" title=\"FDA timeline from Phase 1 start to approval. Derived from BIO 2021 industry survey: Phase 1 (2.3 years) + efficacy lag (8.2 years) = 10.5 years. Consistent with PMC meta-analysis finding 9.1 years median (95% CI: 8.2-10.0). | ✓ High confidence | 95% CI: [6 years, 12 years] | Dist: Gamma (SE: 2 years) | Unit: years | Click to view details, calculation & sources\">10.5 years (95% CI: 6 years-12 years)</a>"
"fda_phase_1_to_approval_years_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-fda_phase_1_to_approval_years\" class=\"parameter-link\" data-source-ref=\"bio-clinical-development-2021\" data-source-type=\"external\" data-confidence=\"high\" title=\"FDA timeline from Phase 1 start to approval. Derived from BIO 2021 industry survey: Phase 1 (2.3 years) + efficacy lag (8.2 years) = 10.5 years. Consistent with PMC meta-analysis finding 9.1 years median (95% CI: 8.2-10.0). | ✓ High confidence | 95% CI: [6 years, 12 years] | Dist: Gamma (SE: 2 years) | Unit: years | Click to view details, calculation & sources\">10.5 (95% CI: 6-12)</a>"
"fda_phase_1_to_approval_years_cite": "@bio-clinical-development-2021"
"fda_to_oxford_recovery_trial_time_multiplier": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-fda_to_oxford_recovery_trial_time_multiplier\" class=\"parameter-link\" data-source-ref=\"recovery-trial-82x-cost-reduction\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Efficacy testing time vs Oxford RECOVERY trial (8.2 years ÷ 3 months = 32.8x slower). Compares efficacy lag only (post-safety Phase II/III) since RECOVERY was an efficacy trial. | Calculated from 2 inputs | ✓ High confidence | Formula: EFFICACY_LAG_YEARS × MONTHS_PER_YEAR ÷ OXFORD_RECOVERY_TRIAL_DURATION_MONTHS | Unit: multiplier | Click to view details, calculation & sources\">32.8x (95% CI: 19.4x-45.9x)</a>"
"fda_to_oxford_recovery_trial_time_multiplier_latex": "$$\n\\begin{gathered}\nk_{FDA:RECOVERY} \\\\\n= T_{lag} \\times \\text{MONTHS\\_PER\\_YEAR} / T_{RECOVERY}\n\\end{gathered}\n$$"
"fundamentally_unavoidable_death_pct": "<span class=\"parameter-definition\" title=\"Percentage of deaths that are fundamentally unavoidable even with perfect biotechnology (primarily accidents). Calculated as Σ(disease_burden × (1 - max_cure_potential)) across all disease categories. | Unit: percentage | Core definition\">7.37%</span>"
"gdp_baseline_growth_rate": "<span class=\"parameter-definition\" title=\"Status-quo baseline annual global GDP growth rate. | Unit: rate | Core definition\">2.5%</span>"
"gene_therapy_disease_combinations": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-gene_therapy_disease_combinations\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Gene therapy target-disease combinations (CRISPR, base editing, viral vectors) | Calculated from 2 inputs | ✓ High confidence | Formula: GENES × DISEASES | Unit: combinations | Click to view details, calculation & sources\">20 million combinations</a>"
"gene_therapy_disease_combinations_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-gene_therapy_disease_combinations\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Gene therapy target-disease combinations (CRISPR, base editing, viral vectors) | Calculated from 2 inputs | ✓ High confidence | Formula: GENES × DISEASES | Unit: combinations | Click to view details, calculation & sources\">20 million</a>"
"gene_therapy_disease_combinations_latex": "$$\n\\begin{gathered}\nCombos_{gene} \\\\\n= N_{genes} \\times N_{diseases,trial} \\\\\n= 20{,}000 \\times 1{,}000 \\\\\n= 20M\n\\end{gathered}\n$$"
"givewell_cost_per_life_avg": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-givewell_cost_per_life_avg\" class=\"parameter-link\" data-source-ref=\"givewell-cost-per-life-saved\" data-source-type=\"external\" data-confidence=\"high\" title=\"GiveWell average cost per life saved across top charities | ✓ High confidence | Unit: USD/life | Click to view details, calculation & sources\">$4.5K</a>"
"givewell_cost_per_life_avg_cite": "@givewell-cost-per-life-saved"
"givewell_cost_per_life_max": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-givewell_cost_per_life_max\" class=\"parameter-link\" data-source-ref=\"givewell-cost-per-life-saved\" data-source-type=\"external\" data-confidence=\"high\" title=\"GiveWell cost per life saved (Against Malaria Foundation) | ✓ High confidence | Unit: USD/life | Click to view details, calculation & sources\">$5.5K</a>"
"givewell_cost_per_life_max_cite": "@givewell-cost-per-life-saved"
"givewell_cost_per_life_min": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-givewell_cost_per_life_min\" class=\"parameter-link\" data-source-ref=\"givewell-cost-per-life-saved\" data-source-type=\"external\" data-confidence=\"high\" title=\"GiveWell cost per life saved (Helen Keller International) | ✓ High confidence | Unit: USD/life | Click to view details, calculation & sources\">$3.5K</a>"
"givewell_cost_per_life_min_cite": "@givewell-cost-per-life-saved"
"global_annual_conflict_deaths_active_combat": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_annual_conflict_deaths_active_combat\" class=\"parameter-link\" data-source-ref=\"acled-active-combat-deaths\" data-source-type=\"external\" data-confidence=\"high\" title=\"Annual deaths from active combat worldwide | ✓ High confidence | 95% CI: [180 thousand deaths/year, 300 thousand deaths/year] | Dist: Lognormal | Unit: deaths/year | Click to view details, calculation & sources\">234 thousand deaths/year (95% CI: 180 thousand deaths/year-300 thousand deaths/year)</a>"
"global_annual_conflict_deaths_active_combat_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_annual_conflict_deaths_active_combat\" class=\"parameter-link\" data-source-ref=\"acled-active-combat-deaths\" data-source-type=\"external\" data-confidence=\"high\" title=\"Annual deaths from active combat worldwide | ✓ High confidence | 95% CI: [180 thousand deaths/year, 300 thousand deaths/year] | Dist: Lognormal | Unit: deaths/year | Click to view details, calculation & sources\">234 thousand (95% CI: 180 thousand-300 thousand)</a>"
"global_annual_conflict_deaths_active_combat_cite": "@acled-active-combat-deaths"
"global_annual_conflict_deaths_state_violence": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_annual_conflict_deaths_state_violence\" class=\"parameter-link\" data-source-ref=\"ucdp-state-violence-deaths\" data-source-type=\"external\" data-confidence=\"high\" title=\"Annual deaths from state violence | ✓ High confidence | 95% CI: [1.5 thousand deaths/year, 5 thousand deaths/year] | Dist: Lognormal | Unit: deaths/year | Click to view details, calculation & sources\">2.7 thousand deaths/year (95% CI: 1.5 thousand deaths/year-5 thousand deaths/year)</a>"
"global_annual_conflict_deaths_state_violence_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_annual_conflict_deaths_state_violence\" class=\"parameter-link\" data-source-ref=\"ucdp-state-violence-deaths\" data-source-type=\"external\" data-confidence=\"high\" title=\"Annual deaths from state violence | ✓ High confidence | 95% CI: [1.5 thousand deaths/year, 5 thousand deaths/year] | Dist: Lognormal | Unit: deaths/year | Click to view details, calculation & sources\">2.7 thousand (95% CI: 1.5 thousand-5 thousand)</a>"
"global_annual_conflict_deaths_state_violence_cite": "@ucdp-state-violence-deaths"
"global_annual_conflict_deaths_terror_attacks": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_annual_conflict_deaths_terror_attacks\" class=\"parameter-link\" data-source-ref=\"gtd-terror-attack-deaths\" data-source-type=\"external\" data-confidence=\"high\" title=\"Annual deaths from terror attacks globally | ✓ High confidence | 95% CI: [6 thousand deaths/year, 12 thousand deaths/year] | Dist: Lognormal | Unit: deaths/year | Click to view details, calculation & sources\">8.3 thousand deaths/year (95% CI: 6 thousand deaths/year-12 thousand deaths/year)</a>"
"global_annual_conflict_deaths_terror_attacks_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_annual_conflict_deaths_terror_attacks\" class=\"parameter-link\" data-source-ref=\"gtd-terror-attack-deaths\" data-source-type=\"external\" data-confidence=\"high\" title=\"Annual deaths from terror attacks globally | ✓ High confidence | 95% CI: [6 thousand deaths/year, 12 thousand deaths/year] | Dist: Lognormal | Unit: deaths/year | Click to view details, calculation & sources\">8.3 thousand (95% CI: 6 thousand-12 thousand)</a>"
"global_annual_conflict_deaths_terror_attacks_cite": "@gtd-terror-attack-deaths"
"global_annual_conflict_deaths_total": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_annual_conflict_deaths_total\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Total annual conflict deaths globally (sum of combat, terror, state violence) | Calculated from 3 inputs | ✓ High confidence | Formula: COMBAT + TERROR + STATE_VIOLENCE | Unit: deaths/year | Click to view details, calculation & sources\">245 thousand deaths/year (95% CI: 194 thousand deaths/year-302 thousand deaths/year)</a>"
"global_annual_conflict_deaths_total_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_annual_conflict_deaths_total\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Total annual conflict deaths globally (sum of combat, terror, state violence) | Calculated from 3 inputs | ✓ High confidence | Formula: COMBAT + TERROR + STATE_VIOLENCE | Unit: deaths/year | Click to view details, calculation & sources\">245 thousand (95% CI: 194 thousand-302 thousand)</a>"
"global_annual_conflict_deaths_total_latex": "$$\n\\begin{gathered}\nDeaths_{conflict} \\\\\n= Deaths_{combat} + Deaths_{state} + Deaths_{terror} \\\\\n= 234{,}000 + 2{,}700 + 8{,}300 \\\\\n= 245{,}000\n\\end{gathered}\n$$"
"global_annual_daly_burden": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_annual_daly_burden\" class=\"parameter-link\" data-source-ref=\"ihme-gbd-2021\" data-source-type=\"external\" data-peer-reviewed=\"true\" data-confidence=\"high\" title=\"Global annual DALY burden from all diseases and injuries (WHO/IHME Global Burden of Disease 2021). Includes both YLL (years of life lost) and YLD (years lived with disability) from all causes. | ✓ High confidence | \U0001F4CA Peer-reviewed | Dist: Normal (SE: 150 million DALYs/year) | Unit: DALYs/year | Click to view details, calculation & sources\">2.88 billion DALYs/year (95% CI: 2.63 billion DALYs/year-3.13 billion DALYs/year)</a>"
"global_annual_daly_burden_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_annual_daly_burden\" class=\"parameter-link\" data-source-ref=\"ihme-gbd-2021\" data-source-type=\"external\" data-peer-reviewed=\"true\" data-confidence=\"high\" title=\"Global annual DALY burden from all diseases and injuries (WHO/IHME Global Burden of Disease 2021). Includes both YLL (years of life lost) and YLD (years lived with disability) from all causes. | ✓ High confidence | \U0001F4CA Peer-reviewed | Dist: Normal (SE: 150 million DALYs/year) | Unit: DALYs/year | Click to view details, calculation & sources\">2.88 billion (95% CI: 2.63 billion-3.13 billion)</a>"
"global_annual_daly_burden_cite": "@ihme-gbd-2021"
"global_annual_deaths_curable_diseases": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_annual_deaths_curable_diseases\" class=\"parameter-link\" data-source-ref=\"who-global-health-estimates-2024\" data-source-type=\"external\" data-confidence=\"high\" title=\"Annual deaths from all diseases and aging globally | ✓ High confidence | Dist: Normal (SE: 5 million deaths/year) | Unit: deaths/year | Click to view details, calculation & sources\">55 million deaths/year (95% CI: 46.6 million deaths/year-63.2 million deaths/year)</a>"
"global_annual_deaths_curable_diseases_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_annual_deaths_curable_diseases\" class=\"parameter-link\" data-source-ref=\"who-global-health-estimates-2024\" data-source-type=\"external\" data-confidence=\"high\" title=\"Annual deaths from all diseases and aging globally | ✓ High confidence | Dist: Normal (SE: 5 million deaths/year) | Unit: deaths/year | Click to view details, calculation & sources\">55 million (95% CI: 46.6 million-63.2 million)</a>"
"global_annual_deaths_curable_diseases_cite": "@who-global-health-estimates-2024"
"global_annual_direct_indirect_war_cost": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_annual_direct_indirect_war_cost\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Total annual cost of war worldwide (direct + indirect costs) | Calculated from 2 inputs | ✓ High confidence | Formula: DIRECT_COSTS + INDIRECT_COSTS | Unit: USD/year | Click to view details, calculation & sources\">$11.4T (95% CI: $9.01T-$14.1T)</a>"
"global_annual_direct_indirect_war_cost_latex": "$$\n\\begin{gathered}\nCost_{war,total} \\\\\n= Cost_{war,direct} + Cost_{war,indirect} \\\\\n= \\$7.66T + \\$3.7T \\\\\n= \\$11.4T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,direct} \\\\\n= Loss_{life,conflict} + Damage_{infra,total} \\\\\n+ Disruption_{trade} + Spending_{mil} \\\\\n= \\$2.45T + \\$1.88T + \\$616B + \\$2.72T \\\\\n= \\$7.66T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{life,conflict} \\\\\n= Cost_{combat,human} + Cost_{state,human} \\\\\n+ Cost_{terror,human} \\\\\n= \\$2.34T + \\$27B + \\$83B \\\\\n= \\$2.45T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{combat,human} \\\\\n= Deaths_{combat} \\times VSL \\\\\n= 234{,}000 \\times \\$10M \\\\\n= \\$2.34T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{state,human} \\\\\n= Deaths_{state} \\times VSL \\\\\n= 2{,}700 \\times \\$10M \\\\\n= \\$27B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{terror,human} \\\\\n= Deaths_{terror} \\times VSL \\\\\n= 8{,}300 \\times \\$10M \\\\\n= \\$83B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDamage_{infra,total} \\\\\n= Damage_{comms} + Damage_{edu} + Damage_{energy} \\\\\n+ Damage_{health} + Damage_{transport} + Damage_{water} \\\\\n= \\$298B + \\$234B + \\$422B + \\$166B + \\$487B + \\$268B \\\\\n= \\$1.88T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDisruption_{trade} \\\\\n= Disruption_{currency} + Disruption_{energy} \\\\\n+ Disruption_{shipping} + Disruption_{supply} \\\\\n= \\$57.4B + \\$125B + \\$247B + \\$187B \\\\\n= \\$616B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,indirect} \\\\\n= Damage_{env} + Loss_{growth,mil} + Loss_{capital,conflict} \\\\\n+ Cost_{psych} + Cost_{refugee} + Cost_{vet} \\\\\n= \\$100B + \\$2.72T + \\$300B + \\$232B + \\$150B + \\$200B \\\\\n= \\$3.7T\n\\end{gathered}\n$$"
"global_annual_environmental_damage_conflict": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_annual_environmental_damage_conflict\" class=\"parameter-link\" data-source-ref=\"environmental-cost-of-war\" data-source-type=\"external\" data-confidence=\"high\" title=\"Annual environmental damage and restoration costs from conflict | ✓ High confidence | 95% CI: [$70B, $140B] | Dist: Lognormal | Unit: USD | Click to view details, calculation & sources\">$100B (95% CI: $70B-$140B)</a>"
"global_annual_environmental_damage_conflict_cite": "@environmental-cost-of-war"
"global_annual_human_cost_active_combat": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_annual_human_cost_active_combat\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Annual cost of combat deaths (deaths × VSL) | Calculated from 2 inputs | ✓ High confidence | Formula: COMBAT_DEATHS × VSL  | Unit: USD/year | Click to view details, calculation & sources\">$2.34T (95% CI: $1.25T-$3.57T)</a>"
"global_annual_human_cost_active_combat_latex": "$$\n\\begin{gathered}\nCost_{combat,human} \\\\\n= Deaths_{combat} \\times VSL \\\\\n= 234{,}000 \\times \\$10M \\\\\n= \\$2.34T\n\\end{gathered}\n$$"
"global_annual_human_cost_state_violence": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_annual_human_cost_state_violence\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Annual cost of state violence deaths (deaths × VSL) | Calculated from 2 inputs | ✓ High confidence | Formula: STATE_DEATHS × VSL  | Unit: USD/year | Click to view details, calculation & sources\">$27B (95% CI: $12B-$48.4B)</a>"
"global_annual_human_cost_state_violence_latex": "$$\n\\begin{gathered}\nCost_{state,human} \\\\\n= Deaths_{state} \\times VSL \\\\\n= 2{,}700 \\times \\$10M \\\\\n= \\$27B\n\\end{gathered}\n$$"
"global_annual_human_cost_terror_attacks": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_annual_human_cost_terror_attacks\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Annual cost of terror deaths (deaths × VSL) | Calculated from 2 inputs | ✓ High confidence | Formula: TERROR_DEATHS × VSL  | Unit: USD/year | Click to view details, calculation & sources\">$83B (95% CI: $43.1B-$131B)</a>"
"global_annual_human_cost_terror_attacks_latex": "$$\n\\begin{gathered}\nCost_{terror,human} \\\\\n= Deaths_{terror} \\times VSL \\\\\n= 8{,}300 \\times \\$10M \\\\\n= \\$83B\n\\end{gathered}\n$$"
"global_annual_human_life_losses_conflict": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_annual_human_life_losses_conflict\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Total annual human life losses from conflict (sum of combat, terror, state violence) | Calculated from 3 inputs | ✓ High confidence | Formula: COMBAT_COST + TERROR_COST + STATE_VIOLENCE_COST | Unit: USD/year | Click to view details, calculation & sources\">$2.45T (95% CI: $1.31T-$3.75T)</a>"
"global_annual_human_life_losses_conflict_latex": "$$\n\\begin{gathered}\nLoss_{life,conflict} \\\\\n= Cost_{combat,human} + Cost_{state,human} \\\\\n+ Cost_{terror,human} \\\\\n= \\$2.34T + \\$27B + \\$83B \\\\\n= \\$2.45T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{combat,human} \\\\\n= Deaths_{combat} \\times VSL \\\\\n= 234{,}000 \\times \\$10M \\\\\n= \\$2.34T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{state,human} \\\\\n= Deaths_{state} \\times VSL \\\\\n= 2{,}700 \\times \\$10M \\\\\n= \\$27B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{terror,human} \\\\\n= Deaths_{terror} \\times VSL \\\\\n= 8{,}300 \\times \\$10M \\\\\n= \\$83B\n\\end{gathered}\n$$"
"global_annual_infrastructure_damage_communications_conflict": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_annual_infrastructure_damage_communications_conflict\" class=\"parameter-link\" data-source-ref=\"environmental-cost-of-war\" data-source-type=\"external\" data-confidence=\"high\" title=\"Annual infrastructure damage to communications from conflict | ✓ High confidence | 95% CI: [$209B, $418B] | Dist: Lognormal | Unit: USD | Click to view details, calculation & sources\">$298B (95% CI: $209B-$418B)</a>"
"global_annual_infrastructure_damage_communications_conflict_cite": "@environmental-cost-of-war"
"global_annual_infrastructure_damage_education_conflict": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_annual_infrastructure_damage_education_conflict\" class=\"parameter-link\" data-source-ref=\"environmental-cost-of-war\" data-source-type=\"external\" data-confidence=\"high\" title=\"Annual infrastructure damage to education facilities from conflict | ✓ High confidence | 95% CI: [$164B, $328B] | Dist: Lognormal | Unit: USD | Click to view details, calculation & sources\">$234B (95% CI: $164B-$328B)</a>"
"global_annual_infrastructure_damage_education_conflict_cite": "@environmental-cost-of-war"
"global_annual_infrastructure_damage_energy_conflict": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_annual_infrastructure_damage_energy_conflict\" class=\"parameter-link\" data-source-ref=\"environmental-cost-of-war\" data-source-type=\"external\" data-confidence=\"high\" title=\"Annual infrastructure damage to energy systems from conflict | ✓ High confidence | 95% CI: [$295B, $590B] | Dist: Lognormal | Unit: USD | Click to view details, calculation & sources\">$422B (95% CI: $295B-$590B)</a>"
"global_annual_infrastructure_damage_energy_conflict_cite": "@environmental-cost-of-war"
"global_annual_infrastructure_damage_healthcare_conflict": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_annual_infrastructure_damage_healthcare_conflict\" class=\"parameter-link\" data-source-ref=\"environmental-cost-of-war\" data-source-type=\"external\" data-confidence=\"high\" title=\"Annual infrastructure damage to healthcare facilities from conflict | ✓ High confidence | 95% CI: [$116B, $232B] | Dist: Lognormal | Unit: USD | Click to view details, calculation & sources\">$166B (95% CI: $116B-$232B)</a>"
"global_annual_infrastructure_damage_healthcare_conflict_cite": "@environmental-cost-of-war"
"global_annual_infrastructure_damage_transportation_conflict": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_annual_infrastructure_damage_transportation_conflict\" class=\"parameter-link\" data-source-ref=\"environmental-cost-of-war\" data-source-type=\"external\" data-confidence=\"high\" title=\"Annual infrastructure damage to transportation from conflict | ✓ High confidence | 95% CI: [$340B, $680B] | Dist: Lognormal | Unit: USD | Click to view details, calculation & sources\">$487B (95% CI: $340B-$680B)</a>"
"global_annual_infrastructure_damage_transportation_conflict_cite": "@environmental-cost-of-war"
"global_annual_infrastructure_damage_water_conflict": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_annual_infrastructure_damage_water_conflict\" class=\"parameter-link\" data-source-ref=\"environmental-cost-of-war\" data-source-type=\"external\" data-confidence=\"high\" title=\"Annual infrastructure damage to water systems from conflict | ✓ High confidence | 95% CI: [$187B, $375B] | Dist: Lognormal | Unit: USD | Click to view details, calculation & sources\">$268B (95% CI: $187B-$375B)</a>"
"global_annual_infrastructure_damage_water_conflict_cite": "@environmental-cost-of-war"
"global_annual_infrastructure_destruction_conflict": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_annual_infrastructure_destruction_conflict\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Total annual infrastructure destruction (sum of transportation, energy, communications, water, education, healthcare) | Calculated from 6 inputs | ✓ High confidence | Formula: TRANSPORT + ENERGY + COMMS + WATER + EDUCATION + HEALTHCARE | Unit: USD/year | Click to view details, calculation & sources\">$1.88T (95% CI: $1.37T-$2.47T)</a>"
"global_annual_infrastructure_destruction_conflict_latex": "$$\n\\begin{gathered}\nDamage_{infra,total} \\\\\n= Damage_{comms} + Damage_{edu} + Damage_{energy} \\\\\n+ Damage_{health} + Damage_{transport} + Damage_{water} \\\\\n= \\$298B + \\$234B + \\$422B + \\$166B + \\$487B + \\$268B \\\\\n= \\$1.88T\n\\end{gathered}\n$$"
"global_annual_lives_saved_by_med_research": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_annual_lives_saved_by_med_research\" class=\"parameter-link\" data-source-ref=\"medical-research-lives-saved-annually\" data-source-type=\"external\" data-confidence=\"high\" title=\"Annual lives saved by medical research globally | ✓ High confidence | 95% CI: [3 million lives/year, 6 million lives/year] | Dist: Lognormal | Unit: lives/year | Click to view details, calculation & sources\">4.2 million lives/year (95% CI: 3 million lives/year-6 million lives/year)</a>"
"global_annual_lives_saved_by_med_research_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_annual_lives_saved_by_med_research\" class=\"parameter-link\" data-source-ref=\"medical-research-lives-saved-annually\" data-source-type=\"external\" data-confidence=\"high\" title=\"Annual lives saved by medical research globally | ✓ High confidence | 95% CI: [3 million lives/year, 6 million lives/year] | Dist: Lognormal | Unit: lives/year | Click to view details, calculation & sources\">4.2 million (95% CI: 3 million-6 million)</a>"
"global_annual_lives_saved_by_med_research_cite": "@medical-research-lives-saved-annually"
"global_annual_lost_economic_growth_military_spending": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_annual_lost_economic_growth_military_spending\" class=\"parameter-link\" data-source-ref=\"disparity-ratio-weapons-vs-cures\" data-source-type=\"external\" data-confidence=\"high\" title=\"Annual foregone economic output from military spending vs productive alternatives. This estimate implicitly captures fiscal multiplier differences (military ~0.6x vs healthcare ~4.3x GDP multiplier). Do not add separate GDP multiplier adjustment to avoid double-counting. | ✓ High confidence | 95% CI: [$1.9T, $3.8T] | Dist: Lognormal | Unit: USD | Click to view details, calculation & sources\">$2.72T (95% CI: $1.9T-$3.8T)</a>"
"global_annual_lost_economic_growth_military_spending_cite": "@disparity-ratio-weapons-vs-cures"
"global_annual_lost_human_capital_conflict": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_annual_lost_human_capital_conflict\" class=\"parameter-link\" data-source-ref=\"lost-human-capital-war-cost\" data-source-type=\"external\" data-confidence=\"high\" title=\"Annual lost productivity from conflict casualties | ✓ High confidence | 95% CI: [$210B, $420B] | Dist: Lognormal | Unit: USD | Click to view details, calculation & sources\">$300B (95% CI: $210B-$420B)</a>"
"global_annual_lost_human_capital_conflict_cite": "@lost-human-capital-war-cost"
"global_annual_psychological_impact_costs_conflict": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_annual_psychological_impact_costs_conflict\" class=\"parameter-link\" data-source-ref=\"psychological-impact-war-cost\" data-source-type=\"external\" data-confidence=\"high\" title=\"Annual PTSD and mental health costs from conflict | ✓ High confidence | 95% CI: [$162B, $325B] | Dist: Lognormal | Unit: USD | Click to view details, calculation & sources\">$232B (95% CI: $162B-$325B)</a>"
"global_annual_psychological_impact_costs_conflict_cite": "@psychological-impact-war-cost"
"global_annual_refugee_support_costs": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_annual_refugee_support_costs\" class=\"parameter-link\" data-source-ref=\"unhcr-refugee-support-cost\" data-source-type=\"external\" data-confidence=\"high\" title=\"Annual refugee support costs (108.4M refugees × $1,384/year) | ✓ High confidence | 95% CI: [$105B, $210B] | Dist: Lognormal | Unit: USD | Click to view details, calculation & sources\">$150B (95% CI: $105B-$210B)</a>"
"global_annual_refugee_support_costs_cite": "@unhcr-refugee-support-cost"
"global_annual_savings": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_annual_savings\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Global annual savings in USD (savings rate × GDP) | Calculated from 2 inputs | ✓ High confidence | Formula: GLOBAL_SAVINGS_RATE_PCT × GLOBAL_GDP_2025 | Unit: USD | Click to view details, calculation & sources\">$31.1T (95% CI: $28.1T-$33.9T)</a>"
"global_annual_savings_latex": "$$\n\\begin{gathered}\nS_{annual} \\\\\n= s_{global} \\times GDP_{global} \\\\\n= 27\\% \\times \\$115T \\\\\n= \\$31.1T\n\\end{gathered}\n$$"
"global_annual_savings_per_capita": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_annual_savings_per_capita\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Global annual savings divided by global population. Useful as a rough average-person default for prize-contribution sizing. | Calculated from 2 inputs | ✓ High confidence | Formula: GLOBAL_ANNUAL_SAVINGS / GLOBAL_POPULATION_2024 | Unit: USD/person/year | Click to view details, calculation & sources\">$3.88K (95% CI: $3.59K-$4.16K)</a>"
"global_annual_savings_per_capita_latex": "$$\n\\begin{gathered}\nS_{annual,pc} \\\\\n= \\frac{S_{annual}}{Pop_{global}} \\\\\n= \\frac{\\$31.1T}{8B} \\\\\n= \\$3.88K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nS_{annual} \\\\\n= s_{global} \\times GDP_{global} \\\\\n= 27\\% \\times \\$115T \\\\\n= \\$31.1T\n\\end{gathered}\n$$"
"global_annual_trade_disruption_conflict": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_annual_trade_disruption_conflict\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Total annual trade disruption (sum of shipping, supply chain, energy prices, currency instability) | Calculated from 4 inputs | ✓ High confidence | Formula: SHIPPING + SUPPLY_CHAIN + ENERGY_PRICE + CURRENCY | Unit: USD/year | Click to view details, calculation & sources\">$616B (95% CI: $450B-$812B)</a>"
"global_annual_trade_disruption_conflict_latex": "$$\n\\begin{gathered}\nDisruption_{trade} \\\\\n= Disruption_{currency} + Disruption_{energy} \\\\\n+ Disruption_{shipping} + Disruption_{supply} \\\\\n= \\$57.4B + \\$125B + \\$247B + \\$187B \\\\\n= \\$616B\n\\end{gathered}\n$$"
"global_annual_trade_disruption_currency_conflict": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_annual_trade_disruption_currency_conflict\" class=\"parameter-link\" data-source-ref=\"world-bank-trade-disruption-conflict\" data-source-type=\"external\" data-confidence=\"high\" title=\"Annual trade disruption costs from currency instability | ✓ High confidence | 95% CI: [$40B, $80B] | Dist: Lognormal | Unit: USD | Click to view details, calculation & sources\">$57.4B (95% CI: $40B-$80B)</a>"
"global_annual_trade_disruption_currency_conflict_cite": "@world-bank-trade-disruption-conflict"
"global_annual_trade_disruption_energy_price_conflict": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_annual_trade_disruption_energy_price_conflict\" class=\"parameter-link\" data-source-ref=\"world-bank-trade-disruption-conflict\" data-source-type=\"external\" data-confidence=\"high\" title=\"Annual trade disruption costs from energy price volatility | ✓ High confidence | 95% CI: [$87B, $175B] | Dist: Lognormal | Unit: USD | Click to view details, calculation & sources\">$125B (95% CI: $87B-$175B)</a>"
"global_annual_trade_disruption_energy_price_conflict_cite": "@world-bank-trade-disruption-conflict"
"global_annual_trade_disruption_shipping_conflict": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_annual_trade_disruption_shipping_conflict\" class=\"parameter-link\" data-source-ref=\"world-bank-trade-disruption-conflict\" data-source-type=\"external\" data-confidence=\"high\" title=\"Annual trade disruption costs from shipping disruptions | ✓ High confidence | 95% CI: [$173B, $346B] | Dist: Lognormal | Unit: USD | Click to view details, calculation & sources\">$247B (95% CI: $173B-$346B)</a>"
"global_annual_trade_disruption_shipping_conflict_cite": "@world-bank-trade-disruption-conflict"
"global_annual_trade_disruption_supply_chain_conflict": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_annual_trade_disruption_supply_chain_conflict\" class=\"parameter-link\" data-source-ref=\"world-bank-trade-disruption-conflict\" data-source-type=\"external\" data-confidence=\"high\" title=\"Annual trade disruption costs from supply chain disruptions | ✓ High confidence | 95% CI: [$131B, $262B] | Dist: Lognormal | Unit: USD | Click to view details, calculation & sources\">$187B (95% CI: $131B-$262B)</a>"
"global_annual_trade_disruption_supply_chain_conflict_cite": "@world-bank-trade-disruption-conflict"
"global_annual_veteran_healthcare_costs": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_annual_veteran_healthcare_costs\" class=\"parameter-link\" data-source-ref=\"veteran-healthcare-cost-projections\" data-source-type=\"external\" data-confidence=\"high\" title=\"Annual veteran healthcare costs (20-year projected) | ✓ High confidence | 95% CI: [$140B, $280B] | Dist: Lognormal | Unit: USD | Click to view details, calculation & sources\">$200B (95% CI: $140B-$280B)</a>"
"global_annual_veteran_healthcare_costs_cite": "@veteran-healthcare-cost-projections"
"global_annual_war_direct_costs_total": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_annual_war_direct_costs_total\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Total annual direct war costs (military spending + infrastructure + human life + trade disruption) | Calculated from 4 inputs | ✓ High confidence | Formula: MILITARY + INFRASTRUCTURE + HUMAN_LIFE + TRADE | Unit: USD/year | Click to view details, calculation & sources\">$7.66T (95% CI: $6.14T-$9.4T)</a>"
"global_annual_war_direct_costs_total_latex": "$$\n\\begin{gathered}\nCost_{war,direct} \\\\\n= Loss_{life,conflict} + Damage_{infra,total} \\\\\n+ Disruption_{trade} + Spending_{mil} \\\\\n= \\$2.45T + \\$1.88T + \\$616B + \\$2.72T \\\\\n= \\$7.66T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{life,conflict} \\\\\n= Cost_{combat,human} + Cost_{state,human} \\\\\n+ Cost_{terror,human} \\\\\n= \\$2.34T + \\$27B + \\$83B \\\\\n= \\$2.45T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{combat,human} \\\\\n= Deaths_{combat} \\times VSL \\\\\n= 234{,}000 \\times \\$10M \\\\\n= \\$2.34T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{state,human} \\\\\n= Deaths_{state} \\times VSL \\\\\n= 2{,}700 \\times \\$10M \\\\\n= \\$27B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{terror,human} \\\\\n= Deaths_{terror} \\times VSL \\\\\n= 8{,}300 \\times \\$10M \\\\\n= \\$83B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDamage_{infra,total} \\\\\n= Damage_{comms} + Damage_{edu} + Damage_{energy} \\\\\n+ Damage_{health} + Damage_{transport} + Damage_{water} \\\\\n= \\$298B + \\$234B + \\$422B + \\$166B + \\$487B + \\$268B \\\\\n= \\$1.88T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDisruption_{trade} \\\\\n= Disruption_{currency} + Disruption_{energy} \\\\\n+ Disruption_{shipping} + Disruption_{supply} \\\\\n= \\$57.4B + \\$125B + \\$247B + \\$187B \\\\\n= \\$616B\n\\end{gathered}\n$$"
"global_annual_war_indirect_costs_total": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_annual_war_indirect_costs_total\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Total annual indirect war costs (opportunity cost + veterans + refugees + environment + mental health + lost productivity) | Calculated from 6 inputs | ✓ High confidence | Formula: OPPORTUNITY + VETERANS + REFUGEES + ENVIRONMENT + MENTAL_HEALTH + LOST_CAPITAL | Unit: USD/year | Click to view details, calculation & sources\">$3.7T (95% CI: $2.71T-$4.87T)</a>"
"global_annual_war_indirect_costs_total_latex": "$$\n\\begin{gathered}\nCost_{war,indirect} \\\\\n= Damage_{env} + Loss_{growth,mil} + Loss_{capital,conflict} \\\\\n+ Cost_{psych} + Cost_{refugee} + Cost_{vet} \\\\\n= \\$100B + \\$2.72T + \\$300B + \\$232B + \\$150B + \\$200B \\\\\n= \\$3.7T\n\\end{gathered}\n$$"
"global_avg_hourly_income": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_avg_hourly_income\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Global average hourly income derived from GDP per capita. Uses average (not median), which overestimates the cost of sharing, making the payoff ratio conservative. | Calculated from 2 inputs | ✓ High confidence | Formula: GLOBAL_AVG_INCOME_2025 / ANNUAL_WORKING_HOURS | Unit: USD/hour | Click to view details, calculation & sources\">$7.19 (95% CI: $7.04-$7.34)</a>"
"global_avg_hourly_income_latex": "$$\n\\begin{gathered}\n\\bar{w}_{hour} \\\\\n= \\frac{\\bar{y}_{0}}{H_{work}} \\\\\n= \\frac{\\$14.4K}{2{,}000} \\\\\n= \\$7.19\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{y}_{0} \\\\\n= \\frac{GDP_{global}}{Pop_{global}} \\\\\n= \\frac{\\$115T}{8B} \\\\\n= \\$14.4K\n\\end{gathered}\n$$"
"global_avg_income_2025": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_avg_income_2025\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Global average income (GDP per capita) in 2025 baseline. | Calculated from 2 inputs | ✓ High confidence | Formula: GLOBAL_GDP_2025 ÷ GLOBAL_POPULATION_2024 | Unit: USD | Click to view details, calculation & sources\">$14.4K (95% CI: $14.1K-$14.7K)</a>"
"global_avg_income_2025_latex": "$$\n\\begin{gathered}\n\\bar{y}_{0} \\\\\n= \\frac{GDP_{global}}{Pop_{global}} \\\\\n= \\frac{\\$115T}{8B} \\\\\n= \\$14.4K\n\\end{gathered}\n$$"
"global_avg_remaining_years": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_avg_remaining_years\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Average remaining lifespan for the median-age person. Conservative: uses life expectancy at birth minus median age, which underestimates remaining years because survivors to age 30 have higher conditional life expectancy. | Calculated from 2 inputs | ✓ High confidence | Formula: GLOBAL_LIFE_EXPECTANCY_2024 - GLOBAL_MEDIAN_AGE_2024 | Unit: years | Click to view details, calculation & sources\">48.5 years (95% CI: 45.2 years-51.8 years)</a>"
"global_avg_remaining_years_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_avg_remaining_years\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Average remaining lifespan for the median-age person. Conservative: uses life expectancy at birth minus median age, which underestimates remaining years because survivors to age 30 have higher conditional life expectancy. | Calculated from 2 inputs | ✓ High confidence | Formula: GLOBAL_LIFE_EXPECTANCY_2024 - GLOBAL_MEDIAN_AGE_2024 | Unit: years | Click to view details, calculation & sources\">48.5 (95% CI: 45.2-51.8)</a>"
"global_avg_remaining_years_latex": "$$\n\\begin{gathered}\nT_{remaining} \\\\\n= LE_{global} - Age_{median} \\\\\n= 79 - 30.5 \\\\\n= 48.5\n\\end{gathered}\n$$"
"global_chronic_therapy_days_annual": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_chronic_therapy_days_annual\" class=\"parameter-link\" data-source-ref=\"iqvia-global-medicines-2024\" data-source-type=\"external\" data-confidence=\"medium\" title=\"Annual days of therapy for chronic conditions globally (diabetes, CVD, respiratory, cancer). IQVIA reports 1.8 trillion total days of therapy in 2019, with 71% for chronic conditions. | ~ Medium confidence | 95% CI: [1 trillion days, 1.5 trillion days] | Dist: Lognormal | Unit: days | Click to view details, calculation & sources\">1.28 trillion days (95% CI: 1 trillion days-1.5 trillion days)</a>"
"global_chronic_therapy_days_annual_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_chronic_therapy_days_annual\" class=\"parameter-link\" data-source-ref=\"iqvia-global-medicines-2024\" data-source-type=\"external\" data-confidence=\"medium\" title=\"Annual days of therapy for chronic conditions globally (diabetes, CVD, respiratory, cancer). IQVIA reports 1.8 trillion total days of therapy in 2019, with 71% for chronic conditions. | ~ Medium confidence | 95% CI: [1 trillion days, 1.5 trillion days] | Dist: Lognormal | Unit: days | Click to view details, calculation & sources\">1.28 trillion (95% CI: 1 trillion-1.5 trillion)</a>"
"global_chronic_therapy_days_annual_cite": "@iqvia-global-medicines-2024"
"global_clinical_trials_spending_annual": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_clinical_trials_spending_annual\" class=\"parameter-link\" data-source-ref=\"industry-clinical-trial-spending-estimate\" data-source-type=\"external\" data-confidence=\"high\" title=\"Annual global spending on clinical trials (Industry: $45-60B + Government: $3-6B + Nonprofits: $2-5B). Conservative estimate using 15-20% of $300B total pharma R&D, not inflated market size projections. | ✓ High confidence | 95% CI: [$50B, $75B] | Dist: Lognormal (SE: $10B) | Unit: USD | Click to view details, calculation & sources\">$60B (95% CI: $50B-$75B)</a>"
"global_clinical_trials_spending_annual_cite": "@industry-clinical-trial-spending-estimate"
"global_coordination_activation_budget": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_coordination_activation_budget\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Canonical institutional activation threshold: capital required to make 50% participation credible through direct referral incentives, verification, payment rails, and global launch operations. This is the main institutional ask, not the PRIZE pool seed benchmark. | Calculated from 3 inputs | ✓ High confidence | Formula: GLOBAL_COORDINATION_TARGET_SUPPORTERS × GLOBAL_COORDINATION_ACTIVATION_COST_PER_PARTICIPANT + GLOBAL_COORDINATION_PLATFORM_AND_OPERATIONS_COST | Unit: USD | Click to view details, calculation & sources\">$30B (95% CI: $15.7B-$46.4B)</a>"
"global_coordination_activation_budget_latex": "$$\nB_{activate} = N_{coord} \\times C_{activate,pp} + C_{ops}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{coord} \\\\\n= Pop_{global} \\times R_{coord} \\\\\n= 8B \\times 50\\% \\\\\n= 4B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nC_{activate,pp} \\\\\n= R_{activate} + C_{verify,pp} \\\\\n= \\$5 + \\$1.5 \\\\\n= \\$6.5\n\\end{gathered}\n$$"
"global_coordination_activation_cost_per_participant": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_coordination_activation_cost_per_participant\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Blended variable activation cost per successful verified participant: direct incentive plus verification and payment operations. | Calculated from 2 inputs | ✓ High confidence | Formula: GLOBAL_COORDINATION_ACTIVATION_REWARD_PER_VERIFIED_PARTICIPANT + GLOBAL_COORDINATION_VERIFICATION_AND_PAYMENT_COST_PER_PARTICIPANT | Unit: USD | Click to view details, calculation & sources\">$6.5 (95% CI: $3.49-$9.79)</a>"
"global_coordination_activation_cost_per_participant_latex": "$$\n\\begin{gathered}\nC_{activate,pp} \\\\\n= R_{activate} + C_{verify,pp} \\\\\n= \\$5 + \\$1.5 \\\\\n= \\$6.5\n\\end{gathered}\n$$"
"global_coordination_activation_reward_per_verified_participant": "<span class=\"parameter-definition\" title=\"Planning midpoint for the direct cash incentive required to make a successful verified recruit materially worth sharing at global scale. Intended as a research-backed blended reward across referrer and recruit, not as the long-dated PRIZE claim value. | Unit: USD | Core definition\">$5 (95% CI: $2-$10)</span>"
"global_coordination_platform_and_operations_cost": "<span class=\"parameter-definition\" title=\"Fixed cost to run a global activation campaign toward 50% participation: platform buildout, localization, customer support, compliance, payout operations, fraud response, and regional launch infrastructure. | Unit: USD | Core definition\">$4B (95% CI: $2B-$8B)</span>"
"global_coordination_target_pct": "<span class=\"parameter-definition\" title=\"Modeled end-state global coordination target: half of humanity visibly supports the prize network, used in prose as roughly 90% of likely voters globally. | Unit: percent | Core definition\">50%</span>"
"global_coordination_target_supporters": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_coordination_target_supporters\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Number of people implied by the modeled end-state global coordination target (global population × 50%). | Calculated from 2 inputs | ✓ High confidence | Formula: GLOBAL_POPULATION_2024 × GLOBAL_COORDINATION_TARGET_PCT | Unit: of people | Click to view details, calculation & sources\">4 billion of people (95% CI: 3.92 billion of people-4.08 billion of people)</a>"
"global_coordination_target_supporters_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_coordination_target_supporters\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Number of people implied by the modeled end-state global coordination target (global population × 50%). | Calculated from 2 inputs | ✓ High confidence | Formula: GLOBAL_POPULATION_2024 × GLOBAL_COORDINATION_TARGET_PCT | Unit: of people | Click to view details, calculation & sources\">4 billion (95% CI: 3.92 billion-4.08 billion)</a>"
"global_coordination_target_supporters_latex": "$$\n\\begin{gathered}\nN_{coord} \\\\\n= Pop_{global} \\times R_{coord} \\\\\n= 8B \\times 50\\% \\\\\n= 4B\n\\end{gathered}\n$$"
"global_coordination_verification_and_payment_cost_per_participant": "<span class=\"parameter-definition\" title=\"Planning midpoint for non-reward variable cost per successful verified participant: identity verification, payment rails, fraud checks, support, and completion friction. | Unit: USD | Core definition\">$1.5 (95% CI: $1-$3)</span>"
"global_cost_per_life_saved_med_research_annual": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_cost_per_life_saved_med_research_annual\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Cost per life saved by medical research | Calculated from 2 inputs | ✓ High confidence | Formula: (RESEARCH_SPENDING × 1B) ÷ LIVES_SAVED | Unit: USD/life | Click to view details, calculation & sources\">$16.1K (95% CI: $14.3K-$18.3K)</a>"
"global_cost_per_life_saved_med_research_annual_latex": "$$\n\\begin{gathered}\nCost_{life,RD} \\\\\n= \\frac{Spending_{RD}}{Lives_{RD,ann}} \\\\\n= \\frac{\\$67.5B}{4.2M} \\\\\n= \\$16.1K\n\\end{gathered}\n$$"
"global_cybercrime_cagr": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_cybercrime_cagr\" class=\"parameter-link\" data-source-ref=\"cybercrime-economy-10-5t\" data-source-type=\"external\" data-confidence=\"high\" title=\"Compound annual growth rate of global cybercrime costs. Cybersecurity Ventures: $3T (2015) -> $6T (2021) -> $10.5T (2025). AI-enhanced attacks are accelerating this trend. | ✓ High confidence | Dist: Fixed | Unit: percent | Click to view details, calculation & sources\">15%</a>"
"global_cybercrime_cagr_cite": "@cybercrime-economy-10-5t"
"global_cybercrime_cost_annual_2025": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_cybercrime_cost_annual_2025\" class=\"parameter-link\" data-source-ref=\"cybercrime-economy-10-5t\" data-source-type=\"external\" data-confidence=\"high\" title=\"Projected global cybercrime costs in 2025. Includes data theft, productivity loss, IP theft, fraud. More profitable than global trade of all major illegal drugs combined. If measured as a country, would be the 3rd largest economy after US and China. | ✓ High confidence | Dist: Fixed | Unit: USD | Click to view details, calculation & sources\">$10.5T</a>"
"global_cybercrime_cost_annual_2025_cite": "@cybercrime-economy-10-5t"
"global_destructive_economy_annual_2025": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_destructive_economy_annual_2025\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Combined annual cost of military spending and cybercrime. The 'destructive economy' that competes with the productive economy. | Calculated from 2 inputs | ✓ High confidence | Formula: GLOBAL_MILITARY_SPENDING_ANNUAL_2024 + GLOBAL_CYBERCRIME_COST_ANNUAL_2025 | Unit: USD | Click to view details, calculation & sources\">$13.2T</a>"
"global_destructive_economy_annual_2025_latex": "$$\n\\begin{gathered}\nCost_{destruct} \\\\\n= Spending_{mil} + Cost_{cyber} \\\\\n= \\$2.72T + \\$10.5T \\\\\n= \\$13.2T\n\\end{gathered}\n$$"
"global_destructive_economy_pct_gdp": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_destructive_economy_pct_gdp\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Destructive economy (military + cybercrime) as percentage of global GDP. | Calculated from 2 inputs | ✓ High confidence | Formula: GLOBAL_DESTRUCTIVE_ECONOMY_ANNUAL_2025 / GLOBAL_GDP_2025 | Unit: percent | Click to view details, calculation & sources\">11.5%</a>"
"global_destructive_economy_pct_gdp_latex": "$$\n\\begin{gathered}\nr_{destruct:GDP} \\\\\n= \\frac{Cost_{destruct}}{GDP_{global}} \\\\\n= \\frac{\\$13.2T}{\\$115T} \\\\\n= 11.5\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{destruct} \\\\\n= Spending_{mil} + Cost_{cyber} \\\\\n= \\$2.72T + \\$10.5T \\\\\n= \\$13.2T\n\\end{gathered}\n$$"
"global_disease_deaths_daily": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_disease_deaths_daily\" class=\"parameter-link\" data-source-ref=\"who-global-health-estimates-2024\" data-source-type=\"external\" data-peer-reviewed=\"true\" data-confidence=\"high\" title=\"Total global deaths per day from all disease and aging (WHO Global Burden of Disease 2024) | ✓ High confidence | \U0001F4CA Peer-reviewed | Dist: Normal (SE: 7.5 thousand deaths/day) | Unit: deaths/day | Click to view details, calculation & sources\">150 thousand deaths/day</a>"
"global_disease_deaths_daily_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_disease_deaths_daily\" class=\"parameter-link\" data-source-ref=\"who-global-health-estimates-2024\" data-source-type=\"external\" data-peer-reviewed=\"true\" data-confidence=\"high\" title=\"Total global deaths per day from all disease and aging (WHO Global Burden of Disease 2024) | ✓ High confidence | \U0001F4CA Peer-reviewed | Dist: Normal (SE: 7.5 thousand deaths/day) | Unit: deaths/day | Click to view details, calculation & sources\">150 thousand</a>"
"global_disease_deaths_daily_cite": "@who-global-health-estimates-2024"
"global_disease_deaths_per_minute": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_disease_deaths_per_minute\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Global deaths per minute from all disease and aging | Calculated from 1 input | ✓ High confidence | Formula: GLOBAL_DISEASE_DEATHS_DAILY / 1440 | Unit: deaths/minute | Click to view details, calculation & sources\">104 deaths/minute (95% CI: 95.4 deaths/minute-113 deaths/minute)</a>"
"global_disease_deaths_per_minute_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_disease_deaths_per_minute\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Global deaths per minute from all disease and aging | Calculated from 1 input | ✓ High confidence | Formula: GLOBAL_DISEASE_DEATHS_DAILY / 1440 | Unit: deaths/minute | Click to view details, calculation & sources\">104 (95% CI: 95.4-113)</a>"
"global_disease_deaths_per_minute_latex": "$$\n\\begin{gathered}\nDeaths_{disease,min} \\\\\n= Deaths_{disease,daily} \\times 0.000694 \\\\\n= 150{,}000 \\times 0.000694 \\\\\n= 104\n\\end{gathered}\n$$"
"global_disease_direct_medical_cost_annual": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_disease_direct_medical_cost_annual\" class=\"parameter-link\" data-source-ref=\"disease-economic-burden-109t\" data-source-type=\"external\" data-confidence=\"high\" title=\"Direct medical costs of disease globally (treatment, hospitalization, medication). Standalone market-cost metric; not included in DALY-based welfare burden to avoid double-counting. | ✓ High confidence | 95% CI: [$7T, $14T] | Dist: Lognormal | Unit: USD/year | Click to view details, calculation & sources\">$9.9T (95% CI: $7T-$14T)</a>"
"global_disease_direct_medical_cost_annual_cite": "@disease-economic-burden-109t"
"global_disease_economic_burden_annual": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_disease_economic_burden_annual\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Annual welfare cost of avoidable disease globally. Calculated as global DALY burden × eventually avoidable percentage × standard QALY value ($150K). Uses consistent QALY valuation matching all other health impact calculations. Medical costs and productivity losses are NOT added separately to avoid double-counting (QALY valuation already captures these welfare components). | Calculated from 3 inputs | ✓ High confidence | Formula: GLOBAL_ANNUAL_DALY_BURDEN × EVENTUALLY_AVOIDABLE_DALY_PCT × STANDARD_ECONOMIC_QALY_VALUE_USD | Unit: USD/year | Click to view details, calculation & sources\">$400T (95% CI: $240T-$587T)</a>"
"global_disease_economic_burden_annual_latex": "$$\n\\begin{gathered}\nBurden_{disease} \\\\\n= DALYs_{global,ann} \\times Pct_{avoid,DALY} \\times Value_{QALY} \\\\\n= 2.88B \\times 92.6\\% \\times \\$150K \\\\\n= \\$400T\n\\end{gathered}\n$$"
"global_disease_productivity_loss_annual": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_disease_productivity_loss_annual\" class=\"parameter-link\" data-source-ref=\"disease-economic-burden-109t\" data-source-type=\"external\" data-confidence=\"high\" title=\"Annual productivity loss from disease globally (absenteeism, reduced output). Standalone market-cost metric; not included in DALY-based welfare burden to avoid double-counting. | ✓ High confidence | 95% CI: [$3.5T, $7T] | Dist: Lognormal | Unit: USD/year | Click to view details, calculation & sources\">$5T (95% CI: $3.5T-$7T)</a>"
"global_disease_productivity_loss_annual_cite": "@disease-economic-burden-109t"
"global_gdp_2025": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_gdp_2025\" class=\"parameter-link\" data-source-ref=\"political-dysfunction-tax-paper-2025\" data-source-type=\"external\" data-confidence=\"high\" title=\"Global nominal GDP (2025 estimate). From Political Dysfunction Tax paper citing StatisticsTimes/IMF World Economic Outlook. Used for calculating global opportunity costs as percentage of world economic output. Note: Latest IMF data shows $117T. | ✓ High confidence | Dist: Fixed | Unit: USD | Click to view details, calculation & sources\">$115T</a>"
"global_gdp_2025_cite": "@political-dysfunction-tax-paper-2025"
"global_gdp_per_capita_1900": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_gdp_per_capita_1900\" class=\"parameter-link\" data-source-ref=\"maddison-project-2020\" data-source-type=\"external\" data-confidence=\"medium\" title=\"Global GDP per capita in 1900 in constant 2024 USD. Maddison Project: ~$1,260 in 1990 international dollars, adjusted to 2024 USD (~2.5x). | ~ Medium confidence | Dist: Normal (SE: $500) | Unit: USD/person | Click to view details, calculation & sources\">$3.15K (95% CI: $2.31K-$3.97K)</a>"
"global_gdp_per_capita_1900_cite": "@maddison-project-2020"
"global_government_clinical_trials_spending_annual": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_government_clinical_trials_spending_annual\" class=\"parameter-link\" data-source-ref=\"global-government-clinical-trial-spending-estimate\" data-source-type=\"external\" data-confidence=\"high\" title=\"Annual global government spending on interventional clinical trials (~5-10% of total) | ✓ High confidence | 95% CI: [$3B, $6B] | Dist: Lognormal (SE: $1B) | Unit: USD | Click to view details, calculation & sources\">$4.5B (95% CI: $3B-$6B)</a>"
"global_government_clinical_trials_spending_annual_cite": "@global-government-clinical-trial-spending-estimate"
"global_hale_current": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_hale_current\" class=\"parameter-link\" data-source-ref=\"who-global-health-estimates-2024\" data-source-type=\"external\" data-peer-reviewed=\"true\" data-confidence=\"high\" title=\"Global healthy life expectancy at birth (HALE) from WHO Global Health Observatory, 2019 data (most recent available). HALE measures years lived in full health, adjusting for years lived with disability or disease. | ✓ High confidence | \U0001F4CA Peer-reviewed | Dist: Normal (SE: 1.5 years) | Updated: 2019 | Unit: years | Click to view details, calculation & sources\">63.3 years (95% CI: 60.8 years-65.8 years)</a>"
"global_hale_current_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_hale_current\" class=\"parameter-link\" data-source-ref=\"who-global-health-estimates-2024\" data-source-type=\"external\" data-peer-reviewed=\"true\" data-confidence=\"high\" title=\"Global healthy life expectancy at birth (HALE) from WHO Global Health Observatory, 2019 data (most recent available). HALE measures years lived in full health, adjusting for years lived with disability or disease. | ✓ High confidence | \U0001F4CA Peer-reviewed | Dist: Normal (SE: 1.5 years) | Updated: 2019 | Unit: years | Click to view details, calculation & sources\">63.3 (95% CI: 60.8-65.8)</a>"
"global_hale_current_cite": "@who-global-health-estimates-2024"
"global_hale_gap": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_hale_gap\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Gap between life expectancy and healthy life expectancy. Represents years lived with disability or disease that could be recovered by curing diseases. | Calculated from 2 inputs | ✓ High confidence | Formula: GLOBAL_LIFE_EXPECTANCY_2024 - GLOBAL_HALE_CURRENT | Unit: years | Click to view details, calculation & sources\">15.7 years (95% CI: 14.9 years-16.5 years)</a>"
"global_hale_gap_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_hale_gap\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Gap between life expectancy and healthy life expectancy. Represents years lived with disability or disease that could be recovered by curing diseases. | Calculated from 2 inputs | ✓ High confidence | Formula: GLOBAL_LIFE_EXPECTANCY_2024 - GLOBAL_HALE_CURRENT | Unit: years | Click to view details, calculation & sources\">15.7 (95% CI: 14.9-16.5)</a>"
"global_hale_gap_latex": "$$\n\\Delta_{HALE} = LE_{global} - HALE_{0} = 79 - 63.3 = 15.7\n$$"
"global_household_wealth_usd": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_household_wealth_usd\" class=\"parameter-link\" data-source-ref=\"cs-global-wealth-report-2023\" data-source-type=\"external\" data-confidence=\"high\" title=\"Total global household wealth (2022/2023 estimate) | ✓ High confidence | Dist: Fixed | Unit: USD | Click to view details, calculation & sources\">$454T</a>"
"global_household_wealth_usd_cite": "@cs-global-wealth-report-2023"
"global_industry_clinical_trials_spending_annual": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_industry_clinical_trials_spending_annual\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Annual global industry spending on clinical trials (Total - Government) | Calculated from 2 inputs | ✓ High confidence | Formula: TOTAL_CLINICAL_TRIALS - GOVT_CLINICAL_TRIALS | Unit: USD | Click to view details, calculation & sources\">$55.5B (95% CI: $46.6B-$69B)</a>"
"global_industry_clinical_trials_spending_annual_latex": "$$\n\\begin{gathered}\nSpending_{trials,industry} \\\\\n= Spending_{trials} - Spending_{trials,gov} \\\\\n= \\$60B - \\$4.5B \\\\\n= \\$55.5B\n\\end{gathered}\n$$"
"global_investable_assets": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_investable_assets\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"external\" data-confidence=\"high\" title=\"Total global financial wealth (2024): equities, bonds, cash/deposits, and investment funds. Excludes real estate and physical assets. This is the addressable capital pool for PRIZE deposits. | ✓ High confidence | Dist: Fixed | Unit: USD | Click to view details, calculation & sources\">$305T</a>"
"global_life_expectancy_2024": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_life_expectancy_2024\" class=\"parameter-link\" data-source-ref=\"who-global-health-estimates-2024\" data-source-type=\"external\" data-peer-reviewed=\"true\" data-confidence=\"high\" title=\"Global life expectancy (2024) | ✓ High confidence | \U0001F4CA Peer-reviewed | Dist: Normal (SE: 2 years) | Updated: 2024 | Unit: years | Click to view details, calculation & sources\">79 years (95% CI: 75.7 years-82.3 years)</a>"
"global_life_expectancy_2024_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_life_expectancy_2024\" class=\"parameter-link\" data-source-ref=\"who-global-health-estimates-2024\" data-source-type=\"external\" data-peer-reviewed=\"true\" data-confidence=\"high\" title=\"Global life expectancy (2024) | ✓ High confidence | \U0001F4CA Peer-reviewed | Dist: Normal (SE: 2 years) | Updated: 2024 | Unit: years | Click to view details, calculation & sources\">79 (95% CI: 75.7-82.3)</a>"
"global_life_expectancy_2024_cite": "@who-global-health-estimates-2024"
"global_median_age_2024": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_median_age_2024\" class=\"parameter-link\" data-source-ref=\"global-median-age-un-wpp-2024\" data-source-type=\"external\" data-confidence=\"high\" title=\"Global median age in 2024 from UN World Population Prospects 2024 revision. | ✓ High confidence | Dist: Fixed | Unit: years | Click to view details, calculation & sources\">30.5 years</a>"
"global_median_age_2024_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_median_age_2024\" class=\"parameter-link\" data-source-ref=\"global-median-age-un-wpp-2024\" data-source-type=\"external\" data-confidence=\"high\" title=\"Global median age in 2024 from UN World Population Prospects 2024 revision. | ✓ High confidence | Dist: Fixed | Unit: years | Click to view details, calculation & sources\">30.5</a>"
"global_median_age_2024_cite": "@global-median-age-un-wpp-2024"
"global_med_research_spending": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_med_research_spending\" class=\"parameter-link\" data-source-ref=\"global-gov-med-research-spending\" data-source-type=\"external\" data-confidence=\"high\" title=\"Global government medical research spending | ✓ High confidence | 95% CI: [$54B, $81B] | Dist: Lognormal | Unit: USD | Click to view details, calculation & sources\">$67.5B (95% CI: $54B-$81B)</a>"
"global_med_research_spending_cite": "@global-gov-med-research-spending"
"global_military_spending_annual_2024": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_military_spending_annual_2024\" class=\"parameter-link\" data-source-ref=\"global-military-spending\" data-source-type=\"external\" data-confidence=\"high\" title=\"Global military spending in 2024 | ✓ High confidence | Dist: Fixed | Unit: USD | Click to view details, calculation & sources\">$2.72T</a>"
"global_military_spending_annual_2024_cite": "@global-military-spending"
"global_military_spending_per_capita_annual": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_military_spending_per_capita_annual\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Per capita military spending globally | Calculated from 2 inputs | ✓ High confidence | Formula: MILITARY_SPENDING ÷ POPULATION | Unit: USD/person/year | Click to view details, calculation & sources\">$340 (95% CI: $333-$347)</a>"
"global_military_spending_per_capita_annual_latex": "$$\n\\begin{gathered}\nSpending_{mil,pc} \\\\\n= \\frac{Spending_{mil}}{Pop_{global}} \\\\\n= \\frac{\\$2.72T}{8B} \\\\\n= \\$340\n\\end{gathered}\n$$"
"global_military_spending_post_treaty_annual_2024": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_military_spending_post_treaty_annual_2024\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Global military spending after 1% treaty reduction | Calculated from 2 inputs | ✓ High confidence | Formula: MILITARY_SPENDING × (1 - REDUCTION) | Unit: USD/year | Click to view details, calculation & sources\">$2.69T</a>"
"global_military_spending_post_treaty_annual_2024_latex": "$$\n\\begin{gathered}\nSpending_{mil,post} \\\\\n= Spending_{mil} \\times (1 - Reduce_{treaty}) \\\\\n= \\$2.72T \\times (1 - 1\\%) \\\\\n= \\$2.69T\n\\end{gathered}\n$$"
"global_military_spending_real_cagr_10yr": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_military_spending_real_cagr_10yr\" class=\"parameter-link\" data-source-ref=\"sipri-milex-2024\" data-source-type=\"external\" data-confidence=\"high\" title=\"Real compound annual growth rate of global military spending over the last decade (2014-2024). SIPRI reports 10 consecutive annual increases, with 2024 up 9.4% in real terms. The 10-year CAGR is approximately 3.4% real. | ✓ High confidence | Dist: Fixed | Unit: percent | Click to view details, calculation & sources\">3.4%</a>"
"global_military_spending_real_cagr_10yr_cite": "@sipri-milex-2024"
"global_nonprofit_clinical_trials_spending_annual": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_nonprofit_clinical_trials_spending_annual\" class=\"parameter-link\" data-source-ref=\"nonprofit-clinical-trial-spending-estimate\" data-source-type=\"external\" data-confidence=\"high\" title=\"Annual global nonprofit spending on clinical trials (foundations, disease advocacy groups) | ✓ High confidence | 95% CI: [$2B, $5B] | Unit: USD | Click to view details, calculation & sources\">$3.5B (95% CI: $2B-$5B)</a>"
"global_nonprofit_clinical_trials_spending_annual_cite": "@nonprofit-clinical-trial-spending-estimate"
"global_pharma_rd_spending_annual": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_pharma_rd_spending_annual\" class=\"parameter-link\" data-source-ref=\"global-pharma-rd-spending-300b\" data-source-type=\"external\" data-confidence=\"high\" title=\"Total global pharmaceutical R&D spending ($300B annually, clinical trials represent 15-20% of this total) | ✓ High confidence | Unit: USD | Click to view details, calculation & sources\">$300B</a>"
"global_pharma_rd_spending_annual_cite": "@global-pharma-rd-spending-300b"
"global_political_reform_investment": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_political_reform_investment\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Estimated global advocacy investment for policy reform. Calculated as US costs × global ratio (based on discretionary spending). Upper bound representing full democratic engagement at scale. | Calculated from 2 inputs | ? Low confidence | Formula: US_POLITICAL_REFORM × GLOBAL_RATIO | Unit: USD | Click to view details, calculation & sources\">$128B (95% CI: $55.2B-$266B)</a>"
"global_political_reform_investment_latex": "$$\n\\begin{gathered}\nCost_{global,reform} \\\\\n= Cost_{US,total} \\times \\rho_{global/US} \\\\\n= \\$25.5B \\times 5 \\\\\n= \\$128B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{US,total} \\\\\n= (Cost_{campaign} \\\\\n+ Cost_{lobby} \\times 2) \\times \\mu_{effort} + Cost_{career}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{US,congress} \\\\\n= N_{congress} \\times V_{post-office} \\\\\n= 535 \\times \\$10M \\\\\n= \\$5.35B\n\\end{gathered}\n$$"
"global_population_2024": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_population_2024\" class=\"parameter-link\" data-source-ref=\"global-population-8-billion\" data-source-type=\"external\" data-confidence=\"high\" title=\"Global population in 2024 | ✓ High confidence | 95% CI: [7.8 billion of people, 8.2 billion of people] | Dist: Lognormal | Unit: of people | Click to view details, calculation & sources\">8 billion of people (95% CI: 7.8 billion of people-8.2 billion of people)</a>"
"global_population_2024_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_population_2024\" class=\"parameter-link\" data-source-ref=\"global-population-8-billion\" data-source-type=\"external\" data-confidence=\"high\" title=\"Global population in 2024 | ✓ High confidence | 95% CI: [7.8 billion of people, 8.2 billion of people] | Dist: Lognormal | Unit: of people | Click to view details, calculation & sources\">8 billion (95% CI: 7.8 billion-8.2 billion)</a>"
"global_population_2024_cite": "@global-population-8-billion"
"global_population_2040_projected": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_population_2040_projected\" class=\"parameter-link\" data-source-ref=\"global-population-8-billion\" data-source-type=\"external\" data-confidence=\"high\" title=\"UN World Population Prospects 2022 median projection for 2040. Interpolated midpoint between ~8.1B (2025) and 9.2B (2045). | ✓ High confidence | Dist: Fixed | Unit: of people | Click to view details, calculation & sources\">8.9 billion of people</a>"
"global_population_2040_projected_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_population_2040_projected\" class=\"parameter-link\" data-source-ref=\"global-population-8-billion\" data-source-type=\"external\" data-confidence=\"high\" title=\"UN World Population Prospects 2022 median projection for 2040. Interpolated midpoint between ~8.1B (2025) and 9.2B (2045). | ✓ High confidence | Dist: Fixed | Unit: of people | Click to view details, calculation & sources\">8.9 billion</a>"
"global_population_2040_projected_cite": "@global-population-8-billion"
"global_population_2045_projected": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_population_2045_projected\" class=\"parameter-link\" data-source-ref=\"global-population-8-billion\" data-source-type=\"external\" data-confidence=\"high\" title=\"UN World Population Prospects 2022 median projection for 2045. | ✓ High confidence | Dist: Fixed | Unit: of people | Click to view details, calculation & sources\">9.2 billion of people</a>"
"global_population_2045_projected_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_population_2045_projected\" class=\"parameter-link\" data-source-ref=\"global-population-8-billion\" data-source-type=\"external\" data-confidence=\"high\" title=\"UN World Population Prospects 2022 median projection for 2045. | ✓ High confidence | Dist: Fixed | Unit: of people | Click to view details, calculation & sources\">9.2 billion</a>"
"global_population_2045_projected_cite": "@global-population-8-billion"
"global_population_activism_threshold_pct": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_population_activism_threshold_pct\" class=\"parameter-link\" data-source-ref=\"3-5-rule\" data-source-type=\"external\" data-confidence=\"high\" title=\"Critical mass threshold for social change (3.5% rule). Chenoweth studied national regime changes; applying to a global treaty adds uncertainty. Lower bound: some movements succeeded at ~1%. Upper bound: entrenched defense-industry opposition and weaker signal from digital signatures vs sustained protest may require up to 10%. | ✓ High confidence | 95% CI: [1%, 10%] | Dist: Lognormal | Unit: percent | Click to view details, calculation & sources\">3.5% (95% CI: 1%-10%)</a>"
"global_population_activism_threshold_pct_cite": "@3-5-rule"
"global_retirement_assets": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_retirement_assets\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"external\" data-confidence=\"high\" title=\"Total global pension and retirement assets (OECD 2024). This is the capital pool that the Prize Fund competes with and could partially absorb. | ✓ High confidence | Dist: Fixed | Unit: USD | Click to view details, calculation & sources\">$70T</a>"
"global_savings_rate_pct": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_savings_rate_pct\" class=\"parameter-link\" data-source-ref=\"world-bank-gross-savings-2023\" data-source-type=\"external\" data-confidence=\"high\" title=\"Global gross savings as share of GDP (World Bank, ~27% average 2023-2024) | ✓ High confidence | 95% CI: [24%, 30%] | Dist: Normal | Unit: percent | Click to view details, calculation & sources\">27% (95% CI: 24%-30%)</a>"
"global_savings_rate_pct_cite": "@world-bank-gross-savings-2023"
"global_symptomatic_disease_treatment_annual": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_symptomatic_disease_treatment_annual\" class=\"parameter-link\" data-source-ref=\"disease-economic-burden-109t\" data-source-type=\"external\" data-confidence=\"high\" title=\"Annual global spending on symptomatic disease treatment | ✓ High confidence | 95% CI: [$6.5T, $10T] | Dist: Lognormal | Unit: USD/year | Click to view details, calculation & sources\">$8.2T (95% CI: $6.5T-$10T)</a>"
"global_symptomatic_disease_treatment_annual_cite": "@disease-economic-burden-109t"
"global_total_health_and_war_cost_annual": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_total_health_and_war_cost_annual\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Total annual welfare cost of war and disease. Disease burden uses DALY-based welfare valuation; war costs use direct + indirect economic costs. Symptomatic treatment costs NOT added separately (already captured in QALY valuation). | Calculated from 2 inputs | ✓ High confidence | Formula: WAR_TOTAL_COSTS + DISEASE_WELFARE_BURDEN | Unit: USD/year | Click to view details, calculation & sources\">$412T (95% CI: $250T-$601T)</a>"
"global_total_health_and_war_cost_annual_latex": "$$\n\\begin{gathered}\nCost_{health+war} \\\\\n= Cost_{war,total} + Burden_{disease} \\\\\n= \\$11.4T + \\$400T \\\\\n= \\$412T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,total} \\\\\n= Cost_{war,direct} + Cost_{war,indirect} \\\\\n= \\$7.66T + \\$3.7T \\\\\n= \\$11.4T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,direct} \\\\\n= Loss_{life,conflict} + Damage_{infra,total} \\\\\n+ Disruption_{trade} + Spending_{mil} \\\\\n= \\$2.45T + \\$1.88T + \\$616B + \\$2.72T \\\\\n= \\$7.66T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{life,conflict} \\\\\n= Cost_{combat,human} + Cost_{state,human} \\\\\n+ Cost_{terror,human} \\\\\n= \\$2.34T + \\$27B + \\$83B \\\\\n= \\$2.45T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{combat,human} \\\\\n= Deaths_{combat} \\times VSL \\\\\n= 234{,}000 \\times \\$10M \\\\\n= \\$2.34T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{state,human} \\\\\n= Deaths_{state} \\times VSL \\\\\n= 2{,}700 \\times \\$10M \\\\\n= \\$27B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{terror,human} \\\\\n= Deaths_{terror} \\times VSL \\\\\n= 8{,}300 \\times \\$10M \\\\\n= \\$83B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDamage_{infra,total} \\\\\n= Damage_{comms} + Damage_{edu} + Damage_{energy} \\\\\n+ Damage_{health} + Damage_{transport} + Damage_{water} \\\\\n= \\$298B + \\$234B + \\$422B + \\$166B + \\$487B + \\$268B \\\\\n= \\$1.88T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDisruption_{trade} \\\\\n= Disruption_{currency} + Disruption_{energy} \\\\\n+ Disruption_{shipping} + Disruption_{supply} \\\\\n= \\$57.4B + \\$125B + \\$247B + \\$187B \\\\\n= \\$616B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,indirect} \\\\\n= Damage_{env} + Loss_{growth,mil} + Loss_{capital,conflict} \\\\\n+ Cost_{psych} + Cost_{refugee} + Cost_{vet} \\\\\n= \\$100B + \\$2.72T + \\$300B + \\$232B + \\$150B + \\$200B \\\\\n= \\$3.7T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nBurden_{disease} \\\\\n= DALYs_{global,ann} \\times Pct_{avoid,DALY} \\times Value_{QALY} \\\\\n= 2.88B \\times 92.6\\% \\times \\$150K \\\\\n= \\$400T\n\\end{gathered}\n$$"
"global_to_us_political_cost_ratio": "<span class=\"parameter-definition\" title=\"Ratio of global to US political reform costs. Based on discretionary spending ratio (~9x) discounted by ~50% for less transparent/expensive non-US political systems. Range 3-8 reflects uncertainty about non-US political dynamics and hidden influence channels. | Unit: ratio | Core definition\">5 (95% CI: 3-8)</span>"
"global_yld_proportion_of_dalys": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_yld_proportion_of_dalys\" class=\"parameter-link\" data-source-ref=\"ihme-gbd-2021\" data-source-type=\"external\" data-peer-reviewed=\"true\" data-confidence=\"high\" title=\"Proportion of global DALYs that are YLD (years lived with disability) vs YLL (years of life lost). From GBD 2021: 1.13B YLD out of 2.88B total DALYs = 39%. | ✓ High confidence | \U0001F4CA Peer-reviewed | Dist: Normal (SE: 0.03 proportion) | Unit: proportion | Click to view details, calculation & sources\">0.39 proportion (95% CI: 0.34 proportion-0.439 proportion)</a>"
"global_yld_proportion_of_dalys_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-global_yld_proportion_of_dalys\" class=\"parameter-link\" data-source-ref=\"ihme-gbd-2021\" data-source-type=\"external\" data-peer-reviewed=\"true\" data-confidence=\"high\" title=\"Proportion of global DALYs that are YLD (years lived with disability) vs YLL (years of life lost). From GBD 2021: 1.13B YLD out of 2.88B total DALYs = 39%. | ✓ High confidence | \U0001F4CA Peer-reviewed | Dist: Normal (SE: 0.03 proportion) | Unit: proportion | Click to view details, calculation & sources\">0.39 (95% CI: 0.34-0.439)</a>"
"global_yld_proportion_of_dalys_cite": "@ihme-gbd-2021"
"hale_longevity_realization_share_year_15": "<span class=\"parameter-definition\" title=\"Share of longer-run life-extension gains that have plausibly materialized into healthy years by year 15. Calibrated to the repo's conservative disease-eradication helper, which implies that only a minority of eventual longevity gains are realized within the first 15 years even under rapid research acceleration. | Unit: rate | Core definition\">30%</span>"
"healthcare_vs_military_multiplier_ratio": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-healthcare_vs_military_multiplier_ratio\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Ratio of healthcare to military fiscal multipliers. Healthcare investment generates 7× more economic activity per dollar than military spending. | Calculated from 2 inputs | ✓ High confidence | Formula: ECONOMIC_MULTIPLIER_HEALTHCARE_INVESTMENT / ECONOMIC_MULTIPLIER_MILITARY_SPENDING | Unit: x | Click to view details, calculation & sources\">7.17x (95% CI: 6.83x-7.57x)</a>"
"healthcare_vs_military_multiplier_ratio_latex": "$$\n\\begin{gathered}\nr_{health/mil} \\\\\n= \\frac{k_{health}}{k_{mil}} \\\\\n= \\frac{4.3}{0.6} \\\\\n= 7.17\n\\end{gathered}\n$$"
"home_bias_alpha": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-home_bias_alpha\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"external\" data-confidence=\"high\" title=\"Return drag from home bias in fragmented national pension systems. 70+ countries each overweight domestic assets, missing global diversification. IMF and Vanguard studies estimate 0.3-1.5% annual return cost. Wishocratic allocation is inherently global, eliminating this drag. | ✓ High confidence | 95% CI: [0.3%, 1.5%] | Dist: Normal | Unit: percent | Click to view details, calculation & sources\">0.8% (95% CI: 0.3%-1.5%)</a>"
"hours_per_day": "<span class=\"parameter-link\" title=\"Parameter: HOURS_PER_DAY\">24</span>"
"hours_per_year": "<span class=\"parameter-link\" title=\"8760\">8.76 thousand</span>"
"human_genome_project_total_economic_impact": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-human_genome_project_total_economic_impact\" class=\"parameter-link\" data-source-ref=\"human-genome-and-genetic-editing\" data-source-type=\"external\" data-confidence=\"high\" title=\"Estimated total economic impact of Human Genome Project | ✓ High confidence | Unit: USD | Click to view details, calculation & sources\">$1T</a>"
"human_genome_project_total_economic_impact_cite": "@human-genome-and-genetic-editing"
"human_interactome_targeted_pct": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-human_interactome_targeted_pct\" class=\"parameter-link\" data-source-ref=\"clinical-trials-puzzle-interactome\" data-source-type=\"external\" data-confidence=\"high\" title=\"Percentage of human interactome (protein-protein interactions) targeted by drugs | ✓ High confidence | Unit: percentage | Click to view details, calculation & sources\">12%</a>"
"human_interactome_targeted_pct_cite": "@clinical-trials-puzzle-interactome"
"human_protein_coding_genes": "<span class=\"parameter-definition\" title=\"Human protein-coding genes targetable by gene therapy, mRNA, or biologics (Human Genome Project consensus) | Unit: genes | Core definition\">20 thousand genes (95% CI: 19 thousand genes-21 thousand genes)</span>"
"human_protein_coding_genes_nounit": "<span class=\"parameter-definition\" title=\"Human protein-coding genes targetable by gene therapy, mRNA, or biologics (Human Genome Project consensus) | Unit: genes | Core definition\">20 thousand (95% CI: 19 thousand-21 thousand)</span>"
"iab_mechanism_annual_cost": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-iab_mechanism_annual_cost\" class=\"parameter-link\" data-source-ref=\"https://iab.warondisease.org#welfare-analysis\" data-source-type=\"definition\" data-confidence=\"high\" title=\"Estimated annual cost of the IAB mechanism (high-end estimate including regulatory defense) | ✓ High confidence | 95% CI: [$160M, $750M] | Unit: USD/year | Click to view details, calculation & sources\">$750M (95% CI: $160M-$750M)</a>"
"iab_mechanism_benefit_cost_ratio": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-iab_mechanism_benefit_cost_ratio\" class=\"parameter-link\" data-source-ref=\"https://iab.warondisease.org##welfare-analysis\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Benefit-Cost Ratio of the IAB mechanism itself | Calculated from 2 inputs | ✓ High confidence | Formula: TREATY_PEACE_PLUS_RD_BENEFITS ÷ IAB_MECHANISM_COST | Unit: ratio | Click to view details, calculation & sources\">230 (95% CI: 186-284)</a>"
"iab_mechanism_benefit_cost_ratio_latex": "$$\n\\begin{gathered}\nBCR_{IAB} \\\\\n= \\frac{Benefit_{peace+RD}}{Cost_{IAB,ann}} \\\\\n= \\frac{\\$172B}{\\$750M} \\\\\n= 230\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nBenefit_{peace+RD} \\\\\n= Benefit_{peace,soc} + Benefit_{RD,ann} \\\\\n= \\$114B + \\$58.6B \\\\\n= \\$172B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nBenefit_{peace,soc} \\\\\n= Cost_{war,total} \\times Reduce_{treaty} \\\\\n= \\$11.4T \\times 1\\% \\\\\n= \\$114B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,total} \\\\\n= Cost_{war,direct} + Cost_{war,indirect} \\\\\n= \\$7.66T + \\$3.7T \\\\\n= \\$11.4T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,direct} \\\\\n= Loss_{life,conflict} + Damage_{infra,total} \\\\\n+ Disruption_{trade} + Spending_{mil} \\\\\n= \\$2.45T + \\$1.88T + \\$616B + \\$2.72T \\\\\n= \\$7.66T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{life,conflict} \\\\\n= Cost_{combat,human} + Cost_{state,human} \\\\\n+ Cost_{terror,human} \\\\\n= \\$2.34T + \\$27B + \\$83B \\\\\n= \\$2.45T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{combat,human} \\\\\n= Deaths_{combat} \\times VSL \\\\\n= 234{,}000 \\times \\$10M \\\\\n= \\$2.34T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{state,human} \\\\\n= Deaths_{state} \\times VSL \\\\\n= 2{,}700 \\times \\$10M \\\\\n= \\$27B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{terror,human} \\\\\n= Deaths_{terror} \\times VSL \\\\\n= 8{,}300 \\times \\$10M \\\\\n= \\$83B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDamage_{infra,total} \\\\\n= Damage_{comms} + Damage_{edu} + Damage_{energy} \\\\\n+ Damage_{health} + Damage_{transport} + Damage_{water} \\\\\n= \\$298B + \\$234B + \\$422B + \\$166B + \\$487B + \\$268B \\\\\n= \\$1.88T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDisruption_{trade} \\\\\n= Disruption_{currency} + Disruption_{energy} \\\\\n+ Disruption_{shipping} + Disruption_{supply} \\\\\n= \\$57.4B + \\$125B + \\$247B + \\$187B \\\\\n= \\$616B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,indirect} \\\\\n= Damage_{env} + Loss_{growth,mil} + Loss_{capital,conflict} \\\\\n+ Cost_{psych} + Cost_{refugee} + Cost_{vet} \\\\\n= \\$100B + \\$2.72T + \\$300B + \\$232B + \\$150B + \\$200B \\\\\n= \\$3.7T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nBenefit_{RD,ann} \\\\\n= Spending_{trials} \\times Reduce_{pct} \\\\\n= \\$60B \\times 97.7\\% \\\\\n= \\$58.6B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nReduce_{pct} \\\\\n= 1 - \\frac{Cost_{pragmatic,pt}}{Cost_{P3,pt}} \\\\\n= 1 - \\frac{\\$929}{\\$41K} \\\\\n= 97.7\\%\n\\end{gathered}\n$$"
"iab_political_incentive_funding_annual": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-iab_political_incentive_funding_annual\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Annual funding for IAB political incentive mechanism (independent expenditures supporting high-scoring politicians, post-office fellowship endowments, Public Good Score infrastructure) | Calculated from 2 inputs | ✓ High confidence | Formula: TREATY_FUNDING × IAB_POLITICAL_INCENTIVE_PCT | Unit: USD/year | Click to view details, calculation & sources\">$2.72B</a>"
"iab_political_incentive_funding_annual_latex": "$$\n\\begin{gathered}\nFunding_{political,ann} \\\\\n= Funding_{treaty} \\times Pct_{political} \\\\\n= \\$27.2B \\times 10\\% \\\\\n= \\$2.72B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nFunding_{treaty} \\\\\n= Spending_{mil} \\times Reduce_{treaty} \\\\\n= \\$2.72T \\times 1\\% \\\\\n= \\$27.2B\n\\end{gathered}\n$$"
"iab_political_incentive_funding_pct": "<span class=\"parameter-definition\" title=\"Percentage of treaty funding allocated to Incentive Alignment Bond mechanism for political incentives (independent expenditures/PACs, post-office fellowships, Public Good Score infrastructure) | Unit: rate | Core definition\">10%</span>"
"iab_vs_defense_lobby_ratio_at_1pct": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-iab_vs_defense_lobby_ratio_at_1pct\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Ratio of IAB political incentive funding to defense industry lobbying at 1% treaty level. At just 1%, the health lobby already outguns the defense lobby by this factor. | Calculated from 2 inputs | ✓ High confidence | Formula: IAB_POLITICAL_INCENTIVE_FUNDING_ANNUAL / DEFENSE_LOBBYING_ANNUAL | Unit: x | Click to view details, calculation & sources\">21.4x</a>"
"iab_vs_defense_lobby_ratio_at_1pct_latex": "$$\n\\begin{gathered}\nk_{IAB:defense} \\\\\n= \\frac{Funding_{political,ann}}{Lobby_{def,ann}} \\\\\n= \\frac{\\$2.72B}{\\$127M} \\\\\n= 21.4\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nFunding_{political,ann} \\\\\n= Funding_{treaty} \\times Pct_{political} \\\\\n= \\$27.2B \\times 10\\% \\\\\n= \\$2.72B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nFunding_{treaty} \\\\\n= Spending_{mil} \\times Reduce_{treaty} \\\\\n= \\$2.72T \\times 1\\% \\\\\n= \\$27.2B\n\\end{gathered}\n$$"
"icd_10_total_codes": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-icd_10_total_codes\" class=\"parameter-link\" data-source-ref=\"icd-10-code-count\" data-source-type=\"external\" data-confidence=\"high\" title=\"Total ICD-10 diagnostic codes for human diseases and conditions | ✓ High confidence | Unit: codes | Click to view details, calculation & sources\">14 thousand codes</a>"
"icd_10_total_codes_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-icd_10_total_codes\" class=\"parameter-link\" data-source-ref=\"icd-10-code-count\" data-source-type=\"external\" data-confidence=\"high\" title=\"Total ICD-10 diagnostic codes for human diseases and conditions | ✓ High confidence | Unit: codes | Click to view details, calculation & sources\">14 thousand</a>"
"icd_10_total_codes_cite": "@icd-10-code-count"
"industry_vs_government_clinical_trials_spending_ratio": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-industry_vs_government_clinical_trials_spending_ratio\" class=\"parameter-link\" data-source-ref=\"industry-vs-government-trial-spending-split\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Ratio of Industry to Government spending on clinical trials (approx 90/10 split) | Calculated from 2 inputs | ✓ High confidence | Formula: (TOTAL - GOVT) / GOVT | Unit: ratio | Click to view details, calculation & sources\">12.3 (95% CI: 11.5-15.4)</a>"
"industry_vs_government_clinical_trials_spending_ratio_latex": "$$\n\\begin{gathered}\nRatio_{ind:gov} \\\\\n= \\frac{Spending_{trials}}{Spending_{trials,gov}} - 1 \\\\\n= \\frac{\\$60B}{\\$4.5B} - 1 \\\\\n= 12.3\n\\end{gathered}\n$$"
"institutional_investor_min": "<span class=\"parameter-definition\" title=\"Minimum investment for institutional investors | Unit: USD | Core definition\">$10M</span>"
"life_expectancy_gain_1883_1962_years_per_decade": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-life_expectancy_gain_1883_1962_years_per_decade\" class=\"parameter-link\" data-source-ref=\"life-expectancy-increase-pre-1962\" data-source-type=\"calculated\" data-peer-reviewed=\"true\" data-confidence=\"high\" title=\"US life expectancy linear gain rate 1883-1962 (pre-Kefauver-Harris). | Calculated from 2 inputs | ✓ High confidence | \U0001F4CA Peer-reviewed | Formula: (life_exp_1962 - life_exp_1880) / 7.9 decades | Unit: years/decade | Click to view details, calculation & sources\">0 years/decade (95% CI: 3.85 years/decade-3.91 years/decade)</a>"
"life_expectancy_gain_1883_1962_years_per_decade_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-life_expectancy_gain_1883_1962_years_per_decade\" class=\"parameter-link\" data-source-ref=\"life-expectancy-increase-pre-1962\" data-source-type=\"calculated\" data-peer-reviewed=\"true\" data-confidence=\"high\" title=\"US life expectancy linear gain rate 1883-1962 (pre-Kefauver-Harris). | Calculated from 2 inputs | ✓ High confidence | \U0001F4CA Peer-reviewed | Formula: (life_exp_1962 - life_exp_1880) / 7.9 decades | Unit: years/decade | Click to view details, calculation & sources\">0 (95% CI: 3.85-3.91)</a>"
"life_expectancy_gain_1883_1962_years_per_decade_latex": "$$\n\\begin{gathered}\n\\Delta LE_{pre62} \\\\\n= \\frac{LE_{US,1962} - LE_{US,1880}}{7.69} \\\\\n= \\frac{70.1 - 39.4}{7.69} \\\\\n= 0\n\\end{gathered}\n$$"
"life_expectancy_gain_1962_2019_years_per_decade": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-life_expectancy_gain_1962_2019_years_per_decade\" class=\"parameter-link\" data-source-ref=\"post-1962-life-expectancy-slowdown\" data-source-type=\"calculated\" data-peer-reviewed=\"true\" data-confidence=\"high\" title=\"US life expectancy linear gain rate 1962-2019 (post-Kefauver-Harris). | Calculated from 2 inputs | ✓ High confidence | \U0001F4CA Peer-reviewed | Formula: (life_exp_2019 - life_exp_1962) / 5.7 decades | Unit: years/decade | Click to view details, calculation & sources\">0 years/decade</a>"
"life_expectancy_gain_1962_2019_years_per_decade_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-life_expectancy_gain_1962_2019_years_per_decade\" class=\"parameter-link\" data-source-ref=\"post-1962-life-expectancy-slowdown\" data-source-type=\"calculated\" data-peer-reviewed=\"true\" data-confidence=\"high\" title=\"US life expectancy linear gain rate 1962-2019 (post-Kefauver-Harris). | Calculated from 2 inputs | ✓ High confidence | \U0001F4CA Peer-reviewed | Formula: (life_exp_2019 - life_exp_1962) / 5.7 decades | Unit: years/decade | Click to view details, calculation & sources\">0</a>"
"life_expectancy_gain_1962_2019_years_per_decade_latex": "$$\n\\begin{gathered}\n\\Delta LE_{post62} \\\\\n= \\frac{LE_{US,2019} - LE_{US,1962}}{5.56} \\\\\n= \\frac{78.9 - 70.1}{5.56} \\\\\n= 0\n\\end{gathered}\n$$"
"life_extension_years": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-life_extension_years\" class=\"parameter-link\" data-source-ref=\"longevity-escape-velocity\" data-source-type=\"external\" data-confidence=\"low\" title=\"Expected years of life extension from 1% treaty research acceleration (25x trial capacity). Bounds: 0 (complete failure) to ~150 (accident-limited lifespan minus current). Lognormal distribution allows for breakthrough scenarios. | ? Low confidence | 95% CI: [5 years, 100 years] | Dist: Lognormal | Unit: years | Click to view details, calculation & sources\">20 years (95% CI: 5 years-100 years)</a>"
"life_extension_years_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-life_extension_years\" class=\"parameter-link\" data-source-ref=\"longevity-escape-velocity\" data-source-type=\"external\" data-confidence=\"low\" title=\"Expected years of life extension from 1% treaty research acceleration (25x trial capacity). Bounds: 0 (complete failure) to ~150 (accident-limited lifespan minus current). Lognormal distribution allows for breakthrough scenarios. | ? Low confidence | 95% CI: [5 years, 100 years] | Dist: Lognormal | Unit: years | Click to view details, calculation & sources\">20 (95% CI: 5-100)</a>"
"life_extension_years_cite": "@longevity-escape-velocity"
"lobbyist_bond_investment_max": "<span class=\"parameter-definition\" title=\"Maximum bond investment for lobbyist incentives | Unit: USD | Core definition\">$20M</span>"
"lobbyist_salary_max": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-lobbyist_salary_max\" class=\"parameter-link\" data-source-ref=\"lobbyist-statistics-dc\" data-source-type=\"external\" data-confidence=\"high\" title=\"Maximum annual lobbyist salary range | ✓ High confidence | Unit: USD | Click to view details, calculation & sources\">$2M</a>"
"lobbyist_salary_max_cite": "@lobbyist-statistics-dc"
"lobbyist_salary_min_k": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-lobbyist_salary_min_k\" class=\"parameter-link\" data-source-ref=\"lobbyist-statistics-dc\" data-source-type=\"external\" data-confidence=\"high\" title=\"Minimum annual lobbyist salary range | ✓ High confidence | Unit: USD | Click to view details, calculation & sources\">$500K</a>"
"lobbyist_salary_min_k_cite": "@lobbyist-statistics-dc"
"measles_vaccination_roi": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-measles_vaccination_roi\" class=\"parameter-link\" data-source-ref=\"measles-vaccination-roi\" data-source-type=\"external\" data-confidence=\"high\" title=\"Return on investment from measles (MMR) vaccination programs | ✓ High confidence | Unit: ratio | Click to view details, calculation & sources\">14</a>"
"measles_vaccination_roi_cite": "@measles-vaccination-roi"
"medical_qaly_threshold": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-medical_qaly_threshold\" class=\"parameter-link\" data-source-ref=\"qaly-threshold-history\" data-source-type=\"external\" data-confidence=\"high\" title=\"Medical cost-effectiveness QALY threshold. Standard threshold for evaluating whether health interventions are cost-effective. Interventions below $100K/QALY are generally considered cost-effective. | ✓ High confidence | Dist: Fixed | Unit: USD/QALY | Click to view details, calculation & sources\">$100K</a>"
"medical_qaly_threshold_cite": "@qaly-threshold-history"
"medical_research_pct_of_disease_burden": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-medical_research_pct_of_disease_burden\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Medical research spending as percentage of total disease burden | Calculated from 2 inputs | ✓ High confidence | Formula: MED_RESEARCH ÷ TOTAL_BURDEN | Unit: rate | Click to view details, calculation & sources\">0.0164% (95% CI: 0.013%-0.0243%)</a>"
"medical_research_pct_of_disease_burden_latex": "$$\n\\begin{gathered}\nPct_{RD:burden} \\\\\n= \\frac{Spending_{RD}}{Cost_{health+war}} \\\\\n= \\frac{\\$67.5B}{\\$412T} \\\\\n= 0.0164\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{health+war} \\\\\n= Cost_{war,total} + Burden_{disease} \\\\\n= \\$11.4T + \\$400T \\\\\n= \\$412T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,total} \\\\\n= Cost_{war,direct} + Cost_{war,indirect} \\\\\n= \\$7.66T + \\$3.7T \\\\\n= \\$11.4T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,direct} \\\\\n= Loss_{life,conflict} + Damage_{infra,total} \\\\\n+ Disruption_{trade} + Spending_{mil} \\\\\n= \\$2.45T + \\$1.88T + \\$616B + \\$2.72T \\\\\n= \\$7.66T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{life,conflict} \\\\\n= Cost_{combat,human} + Cost_{state,human} \\\\\n+ Cost_{terror,human} \\\\\n= \\$2.34T + \\$27B + \\$83B \\\\\n= \\$2.45T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{combat,human} \\\\\n= Deaths_{combat} \\times VSL \\\\\n= 234{,}000 \\times \\$10M \\\\\n= \\$2.34T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{state,human} \\\\\n= Deaths_{state} \\times VSL \\\\\n= 2{,}700 \\times \\$10M \\\\\n= \\$27B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{terror,human} \\\\\n= Deaths_{terror} \\times VSL \\\\\n= 8{,}300 \\times \\$10M \\\\\n= \\$83B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDamage_{infra,total} \\\\\n= Damage_{comms} + Damage_{edu} + Damage_{energy} \\\\\n+ Damage_{health} + Damage_{transport} + Damage_{water} \\\\\n= \\$298B + \\$234B + \\$422B + \\$166B + \\$487B + \\$268B \\\\\n= \\$1.88T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDisruption_{trade} \\\\\n= Disruption_{currency} + Disruption_{energy} \\\\\n+ Disruption_{shipping} + Disruption_{supply} \\\\\n= \\$57.4B + \\$125B + \\$247B + \\$187B \\\\\n= \\$616B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,indirect} \\\\\n= Damage_{env} + Loss_{growth,mil} + Loss_{capital,conflict} \\\\\n+ Cost_{psych} + Cost_{refugee} + Cost_{vet} \\\\\n= \\$100B + \\$2.72T + \\$300B + \\$232B + \\$150B + \\$200B \\\\\n= \\$3.7T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nBurden_{disease} \\\\\n= DALYs_{global,ann} \\times Pct_{avoid,DALY} \\times Value_{QALY} \\\\\n= 2.88B \\times 92.6\\% \\times \\$150K \\\\\n= \\$400T\n\\end{gathered}\n$$"
"mental_health_productivity_loss_per_capita": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-mental_health_productivity_loss_per_capita\" class=\"parameter-link\" data-source-ref=\"mental-health-burden\" data-source-type=\"external\" data-confidence=\"high\" title=\"Annual productivity loss per capita from mental health issues (beyond treatment costs) | ✓ High confidence | Unit: USD/year | Click to view details, calculation & sources\">$2K</a>"
"mental_health_productivity_loss_per_capita_cite": "@mental-health-burden"
"military_redirect_gdp_boost_at_30pct": "<span class=\"parameter-definition\" title=\"Historical calibration target: 30% military reallocation maps to ~5.5 percentage points annual GDP growth boost. | Unit: rate | Core definition\">5.5% (95% CI: 3.5%-7.5%)</span>"
"military_to_clinical_trials_spending_ratio": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-military_to_clinical_trials_spending_ratio\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Ratio of global military spending to all clinical trials spending (government + industry + nonprofit) | Calculated from 2 inputs | ✓ High confidence | Formula: MILITARY_SPENDING / TOTAL_CLINICAL_TRIALS | Unit: ratio | Click to view details, calculation & sources\">45.3 (95% CI: 36.3-54.4)</a>"
"military_to_clinical_trials_spending_ratio_latex": "$$\n\\begin{gathered}\nRatio_{mil:trials} \\\\\n= \\frac{Spending_{mil}}{Spending_{trials}} \\\\\n= \\frac{\\$2.72T}{\\$60B} \\\\\n= 45.3\n\\end{gathered}\n$$"
"military_to_government_clinical_trials_spending_ratio": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-military_to_government_clinical_trials_spending_ratio\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Ratio of global military spending to government clinical trials spending | Calculated from 2 inputs | ✓ High confidence | Formula: MILITARY_SPENDING / GOVT_CLINICAL_TRIALS_SPENDING | Unit: ratio | Click to view details, calculation & sources\">604 (95% CI: 453-894)</a>"
"military_to_government_clinical_trials_spending_ratio_latex": "$$\n\\begin{gathered}\nRatio_{mil:gov} \\\\\n= \\frac{Spending_{mil}}{Spending_{trials,gov}} \\\\\n= \\frac{\\$2.72T}{\\$4.5B} \\\\\n= 604\n\\end{gathered}\n$$"
"military_vs_medical_research_ratio": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-military_vs_medical_research_ratio\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Ratio of military spending to medical research spending | Calculated from 2 inputs | ✓ High confidence | Formula: MILITARY_SPENDING ÷ MEDICAL_RESEARCH | Unit: ratio | Click to view details, calculation & sources\">40.3 (95% CI: 34.3-48)</a>"
"military_vs_medical_research_ratio_latex": "$$\n\\begin{gathered}\nRatio_{mil:RD} \\\\\n= \\frac{Spending_{mil}}{Spending_{RD}} \\\\\n= \\frac{\\$2.72T}{\\$67.5B} \\\\\n= 40.3\n\\end{gathered}\n$$"
"minutes_per_hour": "<span class=\"parameter-link\" title=\"Parameter: MINUTES_PER_HOUR\">60</span>"
"misallocation_factor_death_vs_saving": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-misallocation_factor_death_vs_saving\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Misallocation factor: cost to kill vs cost to save | Calculated from 3 inputs | ✓ High confidence | Formula: COST_PER_DEATH ÷ COST_PER_LIFE_SAVED | Unit: x | Click to view details, calculation & sources\">2.9kx (95% CI: 2.5kx-3.3kx)</a>"
"misallocation_factor_death_vs_saving_latex": "$$\n\\begin{gathered}\nk_{misalloc} \\\\\n= \\frac{Cost_{war,total}}{Deaths_{conflict} \\times Cost_{life,RD}} \\\\\n= \\frac{\\$11.4T}{245{,}000 \\times \\$16.1K} \\\\\n= 2{,}890\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDeaths_{conflict} \\\\\n= Deaths_{combat} + Deaths_{state} + Deaths_{terror} \\\\\n= 234{,}000 + 2{,}700 + 8{,}300 \\\\\n= 245{,}000\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,total} \\\\\n= Cost_{war,direct} + Cost_{war,indirect} \\\\\n= \\$7.66T + \\$3.7T \\\\\n= \\$11.4T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,direct} \\\\\n= Loss_{life,conflict} + Damage_{infra,total} \\\\\n+ Disruption_{trade} + Spending_{mil} \\\\\n= \\$2.45T + \\$1.88T + \\$616B + \\$2.72T \\\\\n= \\$7.66T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{life,conflict} \\\\\n= Cost_{combat,human} + Cost_{state,human} \\\\\n+ Cost_{terror,human} \\\\\n= \\$2.34T + \\$27B + \\$83B \\\\\n= \\$2.45T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{combat,human} \\\\\n= Deaths_{combat} \\times VSL \\\\\n= 234{,}000 \\times \\$10M \\\\\n= \\$2.34T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{state,human} \\\\\n= Deaths_{state} \\times VSL \\\\\n= 2{,}700 \\times \\$10M \\\\\n= \\$27B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{terror,human} \\\\\n= Deaths_{terror} \\times VSL \\\\\n= 8{,}300 \\times \\$10M \\\\\n= \\$83B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDamage_{infra,total} \\\\\n= Damage_{comms} + Damage_{edu} + Damage_{energy} \\\\\n+ Damage_{health} + Damage_{transport} + Damage_{water} \\\\\n= \\$298B + \\$234B + \\$422B + \\$166B + \\$487B + \\$268B \\\\\n= \\$1.88T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDisruption_{trade} \\\\\n= Disruption_{currency} + Disruption_{energy} \\\\\n+ Disruption_{shipping} + Disruption_{supply} \\\\\n= \\$57.4B + \\$125B + \\$247B + \\$187B \\\\\n= \\$616B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,indirect} \\\\\n= Damage_{env} + Loss_{growth,mil} + Loss_{capital,conflict} \\\\\n+ Cost_{psych} + Cost_{refugee} + Cost_{vet} \\\\\n= \\$100B + \\$2.72T + \\$300B + \\$232B + \\$150B + \\$200B \\\\\n= \\$3.7T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{life,RD} \\\\\n= \\frac{Spending_{RD}}{Lives_{RD,ann}} \\\\\n= \\frac{\\$67.5B}{4.2M} \\\\\n= \\$16.1K\n\\end{gathered}\n$$"
"money_printer_war_deaths": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-money_printer_war_deaths\" class=\"parameter-link\" data-source-ref=\"crs-war-costs-2010\" data-source-type=\"definition\" data-confidence=\"medium\" title=\"Cumulative deaths from 6 wars funded by money printing: Napoleonic (5M), Civil War (750K), WWI (20M), WWII (60M), Korea (3M), Vietnam (3M), post-9/11 (4.5M). Mid-range estimates; conservative total exceeds 110M. | ~ Medium confidence | Dist: Fixed | Unit: deaths | Click to view details, calculation & sources\">97 million deaths</a>"
"money_printer_war_deaths_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-money_printer_war_deaths\" class=\"parameter-link\" data-source-ref=\"crs-war-costs-2010\" data-source-type=\"definition\" data-confidence=\"medium\" title=\"Cumulative deaths from 6 wars funded by money printing: Napoleonic (5M), Civil War (750K), WWI (20M), WWII (60M), Korea (3M), Vietnam (3M), post-9/11 (4.5M). Mid-range estimates; conservative total exceeds 110M. | ~ Medium confidence | Dist: Fixed | Unit: deaths | Click to view details, calculation & sources\">97 million</a>"
"months_per_year": "<span class=\"parameter-link\" title=\"Parameter: MONTHS_PER_YEAR\">12</span>"
"mrna_therapeutic_combinations": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-mrna_therapeutic_combinations\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"mRNA therapeutic combinations (protein replacement, vaccines, enzyme delivery) | Calculated from 2 inputs | ✓ High confidence | Formula: PROTEINS × DISEASES | Unit: combinations | Click to view details, calculation & sources\">20 million combinations</a>"
"mrna_therapeutic_combinations_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-mrna_therapeutic_combinations\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"mRNA therapeutic combinations (protein replacement, vaccines, enzyme delivery) | Calculated from 2 inputs | ✓ High confidence | Formula: PROTEINS × DISEASES | Unit: combinations | Click to view details, calculation & sources\">20 million</a>"
"mrna_therapeutic_combinations_latex": "$$\n\\begin{gathered}\nCombos_{mRNA} \\\\\n= N_{genes} \\times N_{diseases,trial} \\\\\n= 20{,}000 \\times 1{,}000 \\\\\n= 20M\n\\end{gathered}\n$$"
"nato_defense_spending_annual": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-nato_defense_spending_annual\" class=\"parameter-link\" data-source-ref=\"sipri2024\" data-source-type=\"external\" data-confidence=\"high\" title=\"Total NATO member defense spending in 2024. Source: SIPRI. | ✓ High confidence | Unit: USD | Click to view details, calculation & sources\">$1.51T</a>"
"nato_defense_spending_annual_cite": "@sipri2024"
"new_disease_first_treatments_per_year": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-new_disease_first_treatments_per_year\" class=\"parameter-link\" data-source-ref=\"diseases-getting-first-treatment-annually\" data-source-type=\"external\" data-confidence=\"low\" title=\"Number of diseases that receive their FIRST effective treatment each year under current system. ~9 rare diseases/year (based on 40 years of ODA: 350 with treatment ÷ 40 years), plus ~5-10 common diseases. Note: FDA approves ~50 drugs/year, but most are for diseases that already have treatments. | ? Low confidence | 95% CI: [8 diseases/year, 30 diseases/year] | Dist: Lognormal | Unit: diseases/year | Click to view details, calculation & sources\">15 diseases/year (95% CI: 8 diseases/year-30 diseases/year)</a>"
"new_disease_first_treatments_per_year_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-new_disease_first_treatments_per_year\" class=\"parameter-link\" data-source-ref=\"diseases-getting-first-treatment-annually\" data-source-type=\"external\" data-confidence=\"low\" title=\"Number of diseases that receive their FIRST effective treatment each year under current system. ~9 rare diseases/year (based on 40 years of ODA: 350 with treatment ÷ 40 years), plus ~5-10 common diseases. Note: FDA approves ~50 drugs/year, but most are for diseases that already have treatments. | ? Low confidence | 95% CI: [8 diseases/year, 30 diseases/year] | Dist: Lognormal | Unit: diseases/year | Click to view details, calculation & sources\">15 (95% CI: 8-30)</a>"
"new_disease_first_treatments_per_year_cite": "@diseases-getting-first-treatment-annually"
"nih_annual_budget": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-nih_annual_budget\" class=\"parameter-link\" data-source-ref=\"nih-budget-fy2025\" data-source-type=\"external\" data-confidence=\"high\" title=\"NIH annual budget (FY2024/2025) | ✓ High confidence | 95% CI: [$45B, $50B] | Unit: USD | Click to view details, calculation & sources\">$47B (95% CI: $45B-$50B)</a>"
"nih_annual_budget_cite": "@nih-budget-fy2025"
"nih_clinical_trials_spending_pct": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-nih_clinical_trials_spending_pct\" class=\"parameter-link\" data-source-ref=\"nih-clinical-trials-spending-pct-3-3\" data-source-type=\"external\" data-confidence=\"high\" title=\"Percentage of NIH budget spent on clinical trials (3.3%) | ✓ High confidence | 95% CI: [2%, 5%] | Dist: Beta | Unit: percentage | Click to view details, calculation & sources\">3.3% (95% CI: 2%-5%)</a>"
"nih_clinical_trials_spending_pct_cite": "@nih-clinical-trials-spending-pct-3-3"
"nih_standard_research_cost_per_qaly": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-nih_standard_research_cost_per_qaly\" class=\"parameter-link\" data-source-ref=\"standard-medical-research-roi\" data-source-type=\"external\" data-confidence=\"medium\" title=\"Typical cost per QALY for standard NIH-funded medical research portfolio. Reflects the inefficiency of traditional RCTs and basic research-heavy allocation. See confidence_interval for range; ICER uses higher thresholds for value-based pricing. | ~ Medium confidence | 95% CI: [$20K, $100K] | Dist: Lognormal | Unit: USD/QALY | Click to view details, calculation & sources\">$50K (95% CI: $20K-$100K)</a>"
"nih_standard_research_cost_per_qaly_cite": "@standard-medical-research-roi"
"nih_traditional_trial_max_efficiency_pct": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-nih_traditional_trial_max_efficiency_pct\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Maximum efficiency of NIH traditional Phase 3 trials relative to pragmatic trials, expressed as a percentage. Calculated as pragmatic cost / traditional cost. This is a CEILING on NIH trial efficiency because: (1) only 3.3% of NIH budget goes to clinical trials at all, and (2) the other 96.7% funds basic research with far lower marginal value when thousands of safe compounds already await testing. | Calculated from 2 inputs | ~ Medium confidence | Formula: DFDA_PRAGMATIC_COST ÷ TRADITIONAL_PHASE3_COST | Unit: percent | Click to view details, calculation & sources\">2.27% (95% CI: 1.12%-2.54%)</a>"
"nih_traditional_trial_max_efficiency_pct_latex": "$$\n\\begin{gathered}\n\\eta_{NIH,max} \\\\\n= \\frac{Cost_{pragmatic,pt}}{Cost_{P3,pt}} \\\\\n= \\frac{\\$929}{\\$41K} \\\\\n= 2.27\\%\n\\end{gathered}\n$$"
"npv_discount_rate_standard": "<span class=\"parameter-definition\" title=\"Standard discount rate for NPV analysis (3% annual, social discount rate) | Unit: rate | Core definition\">3%</span>"
"npv_time_horizon_years": "<span class=\"parameter-definition\" title=\"Standard time horizon for NPV analysis | Unit: years | Core definition\">10 years</span>"
"npv_time_horizon_years_nounit": "<span class=\"parameter-definition\" title=\"Standard time horizon for NPV analysis | Unit: years | Core definition\">10</span>"
"nuclear_overkill_factor": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-nuclear_overkill_factor\" class=\"parameter-link\" data-source-ref=\"nuclear-extinction\" data-source-type=\"definition\" data-confidence=\"medium\" title=\"How many times the global nuclear arsenal can kill Earth's entire population. Based on total potential deaths from existing arsenals (~158.4B) divided by global population (~8B). See nuclear-weapon-cost-and-casualties appendix. | ~ Medium confidence | Dist: Fixed | Unit: x | Click to view details, calculation & sources\">20x</a>"
"oxford_recovery_trial_duration_months": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-oxford_recovery_trial_duration_months\" class=\"parameter-link\" data-source-ref=\"recovery-trial-82x-cost-reduction\" data-source-type=\"external\" data-confidence=\"high\" title=\"Oxford RECOVERY trial duration (found life-saving treatment in 3 months) | ✓ High confidence | Dist: Fixed | Unit: months | Click to view details, calculation & sources\">3 months</a>"
"oxford_recovery_trial_duration_months_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-oxford_recovery_trial_duration_months\" class=\"parameter-link\" data-source-ref=\"recovery-trial-82x-cost-reduction\" data-source-type=\"external\" data-confidence=\"high\" title=\"Oxford RECOVERY trial duration (found life-saving treatment in 3 months) | ✓ High confidence | Dist: Fixed | Unit: months | Click to view details, calculation & sources\">3</a>"
"oxford_recovery_trial_duration_months_cite": "@recovery-trial-82x-cost-reduction"
"patient_willingness_trial_participation_pct": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-patient_willingness_trial_participation_pct\" class=\"parameter-link\" data-source-ref=\"patient-willingness-clinical-trials\" data-source-type=\"external\" data-confidence=\"medium\" title=\"Patient willingness to participate in drug trials (44.8% in surveys, 88% when actually approached) | ~ Medium confidence | 95% CI: [40%, 50%] | Dist: Normal (SE: 2.5%) | Unit: percentage | Click to view details, calculation & sources\">44.8% (95% CI: 40%-50%)</a>"
"patient_willingness_trial_participation_pct_cite": "@patient-willingness-clinical-trials"
"peace_dividend_annual_societal_benefit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-peace_dividend_annual_societal_benefit\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Annual peace dividend from 1% reduction in total war costs (theoretical maximum at ε=1.0) | Calculated from 2 inputs | ✓ High confidence | Formula: TOTAL_WAR_COST × 1% × ε (baseline ε=1.0) | Unit: USD/year | Click to view details, calculation & sources\">$114B (95% CI: $90.1B-$141B)</a>"
"peace_dividend_annual_societal_benefit_latex": "$$\n\\begin{gathered}\nBenefit_{peace,soc} \\\\\n= Cost_{war,total} \\times Reduce_{treaty} \\\\\n= \\$11.4T \\times 1\\% \\\\\n= \\$114B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,total} \\\\\n= Cost_{war,direct} + Cost_{war,indirect} \\\\\n= \\$7.66T + \\$3.7T \\\\\n= \\$11.4T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,direct} \\\\\n= Loss_{life,conflict} + Damage_{infra,total} \\\\\n+ Disruption_{trade} + Spending_{mil} \\\\\n= \\$2.45T + \\$1.88T + \\$616B + \\$2.72T \\\\\n= \\$7.66T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{life,conflict} \\\\\n= Cost_{combat,human} + Cost_{state,human} \\\\\n+ Cost_{terror,human} \\\\\n= \\$2.34T + \\$27B + \\$83B \\\\\n= \\$2.45T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{combat,human} \\\\\n= Deaths_{combat} \\times VSL \\\\\n= 234{,}000 \\times \\$10M \\\\\n= \\$2.34T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{state,human} \\\\\n= Deaths_{state} \\times VSL \\\\\n= 2{,}700 \\times \\$10M \\\\\n= \\$27B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{terror,human} \\\\\n= Deaths_{terror} \\times VSL \\\\\n= 8{,}300 \\times \\$10M \\\\\n= \\$83B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDamage_{infra,total} \\\\\n= Damage_{comms} + Damage_{edu} + Damage_{energy} \\\\\n+ Damage_{health} + Damage_{transport} + Damage_{water} \\\\\n= \\$298B + \\$234B + \\$422B + \\$166B + \\$487B + \\$268B \\\\\n= \\$1.88T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDisruption_{trade} \\\\\n= Disruption_{currency} + Disruption_{energy} \\\\\n+ Disruption_{shipping} + Disruption_{supply} \\\\\n= \\$57.4B + \\$125B + \\$247B + \\$187B \\\\\n= \\$616B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,indirect} \\\\\n= Damage_{env} + Loss_{growth,mil} + Loss_{capital,conflict} \\\\\n+ Cost_{psych} + Cost_{refugee} + Cost_{vet} \\\\\n= \\$100B + \\$2.72T + \\$300B + \\$232B + \\$150B + \\$200B \\\\\n= \\$3.7T\n\\end{gathered}\n$$"
"peace_dividend_conflict_elasticity": "<span class=\"parameter-definition\" title=\"Conflict reduction elasticity: how much conflict costs decrease per 1% military spending cut. ε=0: no effect (spending cuts don't reduce conflict). ε=0.5: moderate linkage (conservative). ε=1.0: proportional (baseline assumption). ε>1.0: shared enemy amplification (redirecting to disease creates unity). | Unit: ratio | Core definition\">1 (95% CI: 0.25-1.5)</span>"
"peace_dividend_conflict_reduction": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-peace_dividend_conflict_reduction\" class=\"parameter-link\" data-source-ref=\"calculated\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Conflict reduction benefits from 1% less military spending (lower confidence - assumes proportional relationship) | Calculated from 2 inputs | ? Low confidence | Formula: PEACE_DIVIDEND_ANNUAL_SOCIETAL_BENEFIT - TREATY_ANNUAL_FUNDING | Unit: USD/year | Click to view details, calculation & sources\">$86.4B (95% CI: $62.9B-$113B)</a>"
"peace_dividend_conflict_reduction_latex": "$$\n\\begin{gathered}\nSavings_{conflict} \\\\\n= Benefit_{peace,soc} - Funding_{treaty} \\\\\n= \\$114B - \\$27.2B \\\\\n= \\$86.4B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nBenefit_{peace,soc} \\\\\n= Cost_{war,total} \\times Reduce_{treaty} \\\\\n= \\$11.4T \\times 1\\% \\\\\n= \\$114B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,total} \\\\\n= Cost_{war,direct} + Cost_{war,indirect} \\\\\n= \\$7.66T + \\$3.7T \\\\\n= \\$11.4T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,direct} \\\\\n= Loss_{life,conflict} + Damage_{infra,total} \\\\\n+ Disruption_{trade} + Spending_{mil} \\\\\n= \\$2.45T + \\$1.88T + \\$616B + \\$2.72T \\\\\n= \\$7.66T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{life,conflict} \\\\\n= Cost_{combat,human} + Cost_{state,human} \\\\\n+ Cost_{terror,human} \\\\\n= \\$2.34T + \\$27B + \\$83B \\\\\n= \\$2.45T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{combat,human} \\\\\n= Deaths_{combat} \\times VSL \\\\\n= 234{,}000 \\times \\$10M \\\\\n= \\$2.34T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{state,human} \\\\\n= Deaths_{state} \\times VSL \\\\\n= 2{,}700 \\times \\$10M \\\\\n= \\$27B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{terror,human} \\\\\n= Deaths_{terror} \\times VSL \\\\\n= 8{,}300 \\times \\$10M \\\\\n= \\$83B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDamage_{infra,total} \\\\\n= Damage_{comms} + Damage_{edu} + Damage_{energy} \\\\\n+ Damage_{health} + Damage_{transport} + Damage_{water} \\\\\n= \\$298B + \\$234B + \\$422B + \\$166B + \\$487B + \\$268B \\\\\n= \\$1.88T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDisruption_{trade} \\\\\n= Disruption_{currency} + Disruption_{energy} \\\\\n+ Disruption_{shipping} + Disruption_{supply} \\\\\n= \\$57.4B + \\$125B + \\$247B + \\$187B \\\\\n= \\$616B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,indirect} \\\\\n= Damage_{env} + Loss_{growth,mil} + Loss_{capital,conflict} \\\\\n+ Cost_{psych} + Cost_{refugee} + Cost_{vet} \\\\\n= \\$100B + \\$2.72T + \\$300B + \\$232B + \\$150B + \\$200B \\\\\n= \\$3.7T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nFunding_{treaty} \\\\\n= Spending_{mil} \\times Reduce_{treaty} \\\\\n= \\$2.72T \\times 1\\% \\\\\n= \\$27.2B\n\\end{gathered}\n$$"
"peace_dividend_direct_costs": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-peace_dividend_direct_costs\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Annual savings from 1% reduction in direct war costs | Calculated from 2 inputs | ✓ High confidence | Formula: DIRECT_COSTS × 1% | Unit: USD/year | Click to view details, calculation & sources\">$76.6B (95% CI: $61.4B-$94B)</a>"
"peace_dividend_direct_costs_latex": "$$\n\\begin{gathered}\nSavings_{direct} \\\\\n= Cost_{war,direct} \\times Reduce_{treaty} \\\\\n= \\$7.66T \\times 1\\% \\\\\n= \\$76.6B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,direct} \\\\\n= Loss_{life,conflict} + Damage_{infra,total} \\\\\n+ Disruption_{trade} + Spending_{mil} \\\\\n= \\$2.45T + \\$1.88T + \\$616B + \\$2.72T \\\\\n= \\$7.66T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{life,conflict} \\\\\n= Cost_{combat,human} + Cost_{state,human} \\\\\n+ Cost_{terror,human} \\\\\n= \\$2.34T + \\$27B + \\$83B \\\\\n= \\$2.45T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{combat,human} \\\\\n= Deaths_{combat} \\times VSL \\\\\n= 234{,}000 \\times \\$10M \\\\\n= \\$2.34T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{state,human} \\\\\n= Deaths_{state} \\times VSL \\\\\n= 2{,}700 \\times \\$10M \\\\\n= \\$27B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{terror,human} \\\\\n= Deaths_{terror} \\times VSL \\\\\n= 8{,}300 \\times \\$10M \\\\\n= \\$83B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDamage_{infra,total} \\\\\n= Damage_{comms} + Damage_{edu} + Damage_{energy} \\\\\n+ Damage_{health} + Damage_{transport} + Damage_{water} \\\\\n= \\$298B + \\$234B + \\$422B + \\$166B + \\$487B + \\$268B \\\\\n= \\$1.88T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDisruption_{trade} \\\\\n= Disruption_{currency} + Disruption_{energy} \\\\\n+ Disruption_{shipping} + Disruption_{supply} \\\\\n= \\$57.4B + \\$125B + \\$247B + \\$187B \\\\\n= \\$616B\n\\end{gathered}\n$$"
"peace_dividend_direct_fiscal_savings": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-peace_dividend_direct_fiscal_savings\" class=\"parameter-link\" data-source-ref=\"sipri2024\" data-source-type=\"definition\" data-confidence=\"high\" title=\"Direct fiscal savings from 1% military spending reduction (high confidence) | ✓ High confidence | Formula: TREATY_ANNUAL_FUNDING | Unit: USD/year | Click to view details, calculation & sources\">$27.2B</a>"
"peace_dividend_environmental": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-peace_dividend_environmental\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Annual savings from 1% reduction in environmental damage | Calculated from 2 inputs | ✓ High confidence | Formula: ENVIRONMENTAL_DAMAGE × 1% | Unit: USD/year | Click to view details, calculation & sources\">$1B (95% CI: $732M-$1.32B)</a>"
"peace_dividend_environmental_latex": "$$\n\\begin{gathered}\nSavings_{env} \\\\\n= Damage_{env} \\times Reduce_{treaty} \\\\\n= \\$100B \\times 1\\% \\\\\n= \\$1B\n\\end{gathered}\n$$"
"peace_dividend_human_casualties": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-peace_dividend_human_casualties\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Annual savings from 1% reduction in human casualties | Calculated from 2 inputs | ✓ High confidence | Formula: HUMAN_LIFE_LOSSES × 1% | Unit: USD/year | Click to view details, calculation & sources\">$24.5B (95% CI: $13.1B-$37.5B)</a>"
"peace_dividend_human_casualties_latex": "$$\n\\begin{gathered}\nSavings_{casualties} \\\\\n= Loss_{life,conflict} \\times Reduce_{treaty} \\\\\n= \\$2.45T \\times 1\\% \\\\\n= \\$24.5B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{life,conflict} \\\\\n= Cost_{combat,human} + Cost_{state,human} \\\\\n+ Cost_{terror,human} \\\\\n= \\$2.34T + \\$27B + \\$83B \\\\\n= \\$2.45T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{combat,human} \\\\\n= Deaths_{combat} \\times VSL \\\\\n= 234{,}000 \\times \\$10M \\\\\n= \\$2.34T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{state,human} \\\\\n= Deaths_{state} \\times VSL \\\\\n= 2{,}700 \\times \\$10M \\\\\n= \\$27B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{terror,human} \\\\\n= Deaths_{terror} \\times VSL \\\\\n= 8{,}300 \\times \\$10M \\\\\n= \\$83B\n\\end{gathered}\n$$"
"peace_dividend_indirect_costs": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-peace_dividend_indirect_costs\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Annual savings from 1% reduction in indirect war costs | Calculated from 2 inputs | ✓ High confidence | Formula: INDIRECT_COSTS × 1% | Unit: USD/year | Click to view details, calculation & sources\">$37B (95% CI: $27.1B-$48.7B)</a>"
"peace_dividend_indirect_costs_latex": "$$\n\\begin{gathered}\nSavings_{indirect} \\\\\n= Cost_{war,indirect} \\times Reduce_{treaty} \\\\\n= \\$3.7T \\times 1\\% \\\\\n= \\$37B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,indirect} \\\\\n= Damage_{env} + Loss_{growth,mil} + Loss_{capital,conflict} \\\\\n+ Cost_{psych} + Cost_{refugee} + Cost_{vet} \\\\\n= \\$100B + \\$2.72T + \\$300B + \\$232B + \\$150B + \\$200B \\\\\n= \\$3.7T\n\\end{gathered}\n$$"
"peace_dividend_infrastructure": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-peace_dividend_infrastructure\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Annual savings from 1% reduction in infrastructure destruction | Calculated from 2 inputs | ✓ High confidence | Formula: INFRASTRUCTURE_DESTRUCTION × 1% | Unit: USD/year | Click to view details, calculation & sources\">$18.8B (95% CI: $13.7B-$24.7B)</a>"
"peace_dividend_infrastructure_latex": "$$\n\\begin{gathered}\nSavings_{infra} \\\\\n= Damage_{infra,total} \\times Reduce_{treaty} \\\\\n= \\$1.88T \\times 1\\% \\\\\n= \\$18.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDamage_{infra,total} \\\\\n= Damage_{comms} + Damage_{edu} + Damage_{energy} \\\\\n+ Damage_{health} + Damage_{transport} + Damage_{water} \\\\\n= \\$298B + \\$234B + \\$422B + \\$166B + \\$487B + \\$268B \\\\\n= \\$1.88T\n\\end{gathered}\n$$"
"peace_dividend_lost_economic_growth": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-peace_dividend_lost_economic_growth\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Annual savings from 1% reduction in lost economic growth | Calculated from 2 inputs | ✓ High confidence | Formula: LOST_ECONOMIC_GROWTH × 1% | Unit: USD/year | Click to view details, calculation & sources\">$27.2B (95% CI: $19.9B-$35.8B)</a>"
"peace_dividend_lost_economic_growth_latex": "$$\n\\begin{gathered}\nSavings_{growth} \\\\\n= Loss_{growth,mil} \\times Reduce_{treaty} \\\\\n= \\$2.72T \\times 1\\% \\\\\n= \\$27.2B\n\\end{gathered}\n$$"
"peace_dividend_lost_human_capital": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-peace_dividend_lost_human_capital\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Annual savings from 1% reduction in lost human capital | Calculated from 2 inputs | ✓ High confidence | Formula: LOST_HUMAN_CAPITAL × 1% | Unit: USD/year | Click to view details, calculation & sources\">$3B (95% CI: $2.2B-$3.95B)</a>"
"peace_dividend_lost_human_capital_latex": "$$\n\\begin{gathered}\nSavings_{capital} \\\\\n= Loss_{capital,conflict} \\times Reduce_{treaty} \\\\\n= \\$300B \\times 1\\% \\\\\n= \\$3B\n\\end{gathered}\n$$"
"peace_dividend_ptsd": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-peace_dividend_ptsd\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Annual savings from 1% reduction in PTSD and mental health costs | Calculated from 2 inputs | ✓ High confidence | Formula: PTSD_COSTS × 1% | Unit: USD/year | Click to view details, calculation & sources\">$2.32B (95% CI: $1.7B-$3.06B)</a>"
"peace_dividend_ptsd_latex": "$$\n\\begin{gathered}\nSavings_{PTSD} \\\\\n= Cost_{psych} \\times Reduce_{treaty} \\\\\n= \\$232B \\times 1\\% \\\\\n= \\$2.32B\n\\end{gathered}\n$$"
"peace_dividend_refugee_support": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-peace_dividend_refugee_support\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Annual savings from 1% reduction in refugee support costs | Calculated from 2 inputs | ✓ High confidence | Formula: REFUGEE_SUPPORT × 1% | Unit: USD/year | Click to view details, calculation & sources\">$1.5B (95% CI: $1.1B-$1.98B)</a>"
"peace_dividend_refugee_support_latex": "$$\n\\begin{gathered}\nSavings_{refugee} \\\\\n= Cost_{refugee} \\times Reduce_{treaty} \\\\\n= \\$150B \\times 1\\% \\\\\n= \\$1.5B\n\\end{gathered}\n$$"
"peace_dividend_trade_disruption": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-peace_dividend_trade_disruption\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Annual savings from 1% reduction in trade disruption | Calculated from 2 inputs | ✓ High confidence | Formula: TRADE_DISRUPTION × 1% | Unit: USD/year | Click to view details, calculation & sources\">$6.16B (95% CI: $4.5B-$8.12B)</a>"
"peace_dividend_trade_disruption_latex": "$$\n\\begin{gathered}\nSavings_{trade} \\\\\n= Disruption_{trade} \\times Reduce_{treaty} \\\\\n= \\$616B \\times 1\\% \\\\\n= \\$6.16B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDisruption_{trade} \\\\\n= Disruption_{currency} + Disruption_{energy} \\\\\n+ Disruption_{shipping} + Disruption_{supply} \\\\\n= \\$57.4B + \\$125B + \\$247B + \\$187B \\\\\n= \\$616B\n\\end{gathered}\n$$"
"peace_dividend_veteran_healthcare": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-peace_dividend_veteran_healthcare\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Annual savings from 1% reduction in veteran healthcare costs | Calculated from 2 inputs | ✓ High confidence | Formula: VETERAN_HEALTHCARE × 1% | Unit: USD/year | Click to view details, calculation & sources\">$2B (95% CI: $1.46B-$2.63B)</a>"
"peace_dividend_veteran_healthcare_latex": "$$\n\\begin{gathered}\nSavings_{vet} \\\\\n= Cost_{vet} \\times Reduce_{treaty} \\\\\n= \\$200B \\times 1\\% \\\\\n= \\$2B\n\\end{gathered}\n$$"
"peace_trajectory_total_differential_20yr": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-peace_trajectory_total_differential_20yr\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Total 20-year value of the peace trajectory: research funding redirected to medicine plus war externality costs avoided. The full differential between the IAB trajectory and the current trajectory. Does not include existential risk reduction. | Calculated from 2 inputs | ✓ High confidence | Formula: TREATY_CUMULATIVE_20YR_WITH_RATCHET + WAR_COSTS_SAVED_PEACE_TRAJECTORY_20YR | Unit: USD | Click to view details, calculation & sources\">$16.3T (95% CI: $13.6T-$19.5T)</a>"
"peace_trajectory_total_differential_20yr_latex": "$$\n\\begin{gathered}\nV_{peace,20yr} \\\\\n= Fund_{20yr,ratchet} + Savings_{war,20yr} \\\\\n= \\$3.16T + \\$13.2T \\\\\n= \\$16.3T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nFund_{20yr,ratchet} \\\\\n= Spending_{mil} \\times 1.16 \\\\\n= \\$2.72T \\times 1.16 \\\\\n= \\$3.16T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSavings_{war,20yr} \\\\\n= Cost_{war,total} \\times 1.16 \\\\\n= \\$11.4T \\times 1.16 \\\\\n= \\$13.2T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,total} \\\\\n= Cost_{war,direct} + Cost_{war,indirect} \\\\\n= \\$7.66T + \\$3.7T \\\\\n= \\$11.4T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,direct} \\\\\n= Loss_{life,conflict} + Damage_{infra,total} \\\\\n+ Disruption_{trade} + Spending_{mil} \\\\\n= \\$2.45T + \\$1.88T + \\$616B + \\$2.72T \\\\\n= \\$7.66T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{life,conflict} \\\\\n= Cost_{combat,human} + Cost_{state,human} \\\\\n+ Cost_{terror,human} \\\\\n= \\$2.34T + \\$27B + \\$83B \\\\\n= \\$2.45T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{combat,human} \\\\\n= Deaths_{combat} \\times VSL \\\\\n= 234{,}000 \\times \\$10M \\\\\n= \\$2.34T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{state,human} \\\\\n= Deaths_{state} \\times VSL \\\\\n= 2{,}700 \\times \\$10M \\\\\n= \\$27B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{terror,human} \\\\\n= Deaths_{terror} \\times VSL \\\\\n= 8{,}300 \\times \\$10M \\\\\n= \\$83B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDamage_{infra,total} \\\\\n= Damage_{comms} + Damage_{edu} + Damage_{energy} \\\\\n+ Damage_{health} + Damage_{transport} + Damage_{water} \\\\\n= \\$298B + \\$234B + \\$422B + \\$166B + \\$487B + \\$268B \\\\\n= \\$1.88T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDisruption_{trade} \\\\\n= Disruption_{currency} + Disruption_{energy} \\\\\n+ Disruption_{shipping} + Disruption_{supply} \\\\\n= \\$57.4B + \\$125B + \\$247B + \\$187B \\\\\n= \\$616B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,indirect} \\\\\n= Damage_{env} + Loss_{growth,mil} + Loss_{capital,conflict} \\\\\n+ Cost_{psych} + Cost_{refugee} + Cost_{vet} \\\\\n= \\$100B + \\$2.72T + \\$300B + \\$232B + \\$150B + \\$200B \\\\\n= \\$3.7T\n\\end{gathered}\n$$"
"personal_lifetime_wealth": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-personal_lifetime_wealth\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Personal lifetime wealth from life extension valued at standard QALY rate. Simple formula: years of life gained × economic value per healthy year. Uncertainty in LIFE_EXTENSION_YEARS (5-100 year range, median 20) propagates through Monte Carlo. | Calculated from 2 inputs | ? Low confidence | Formula: LIFE_EXTENSION_YEARS × STANDARD_ECONOMIC_QALY_VALUE_USD | Unit: USD | Click to view details, calculation & sources\">$3M (95% CI: $259K-$12.1M)</a>"
"personal_lifetime_wealth_latex": "$$\n\\begin{gathered}\nWealth_{lifetime} \\\\\n= T_{extend} \\times Value_{QALY} \\\\\n= 20 \\times \\$150K \\\\\n= \\$3M\n\\end{gathered}\n$$"
"per_capita_chronic_disease_cost": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-per_capita_chronic_disease_cost\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"US per capita chronic disease cost | Calculated from 2 inputs | ✓ High confidence | Formula: US_CHRONIC_DISEASE_SPENDING ÷ US_POPULATION | Unit: USD/person/year | Click to view details, calculation & sources\">$12.2K (95% CI: $10.3K-$14.3K)</a>"
"per_capita_chronic_disease_cost_latex": "$$\n\\begin{gathered}\nCost_{chronic,pc} \\\\\n= \\frac{Spending_{chronic,US}}{Pop_{US}} \\\\\n= \\frac{\\$4.1T}{335M} \\\\\n= \\$12.2K\n\\end{gathered}\n$$"
"per_capita_mental_health_cost": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-per_capita_mental_health_cost\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"US per capita mental health cost | Calculated from 2 inputs | ✓ High confidence | Formula: US_MENTAL_HEALTH_COST ÷ US_POPULATION | Unit: USD/person/year | Click to view details, calculation & sources\">$1.04K (95% CI: $832-$1.28K)</a>"
"per_capita_mental_health_cost_latex": "$$\n\\begin{gathered}\nCost_{mental,pc} \\\\\n= \\frac{Cost_{mental,US}}{Pop_{US}} \\\\\n= \\frac{\\$350B}{335M} \\\\\n= \\$1.04K\n\\end{gathered}\n$$"
"pharma_drug_development_cost_current": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-pharma_drug_development_cost_current\" class=\"parameter-link\" data-source-ref=\"drug-development-cost\" data-source-type=\"external\" data-peer-reviewed=\"true\" data-confidence=\"high\" title=\"Average cost to develop one drug in current system | ✓ High confidence | \U0001F4CA Peer-reviewed | 95% CI: [$1.5B, $4B] | Dist: Lognormal (SE: $500M) | Unit: USD | Click to view details, calculation & sources\">$2.6B (95% CI: $1.5B-$4B)</a>"
"pharma_drug_development_cost_current_cite": "@drug-development-cost"
"pharma_drug_revenue_average_current": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-pharma_drug_revenue_average_current\" class=\"parameter-link\" data-source-ref=\"pharma-drug-revenue-average\" data-source-type=\"external\" data-peer-reviewed=\"true\" data-confidence=\"high\" title=\"Median lifetime revenue per successful drug (study of 361 FDA-approved drugs 1995-2014, median follow-up 13.2 years) | ✓ High confidence | \U0001F4CA Peer-reviewed | Unit: USD | Click to view details, calculation & sources\">$6.7B</a>"
"pharma_drug_revenue_average_current_cite": "@pharma-drug-revenue-average"
"pharma_life_years_saved_annual": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-pharma_life_years_saved_annual\" class=\"parameter-link\" data-source-ref=\"lichtenberg-life-years-saved-2019\" data-source-type=\"external\" data-confidence=\"medium\" title=\"Annual life-years saved by pharmaceutical innovations globally. Lichtenberg (2019, NBER WP 25483) found that drugs launched after 1981 saved 148.7M life-years in 2013 across 22 countries using 3-way fixed-effects regression (disease-country-year). 95% CI [79.4M, 239.8M] propagated from Table 2 regression standard errors (β₀₋₁₁=-0.031±0.008, β₁₂₊=-0.057±0.013). | ~ Medium confidence | 95% CI: [79.4 million life-years, 240 million life-years] | Dist: Lognormal | Unit: life-years | Click to view details, calculation & sources\">149 million life-years (95% CI: 79.4 million life-years-240 million life-years)</a>"
"pharma_life_years_saved_annual_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-pharma_life_years_saved_annual\" class=\"parameter-link\" data-source-ref=\"lichtenberg-life-years-saved-2019\" data-source-type=\"external\" data-confidence=\"medium\" title=\"Annual life-years saved by pharmaceutical innovations globally. Lichtenberg (2019, NBER WP 25483) found that drugs launched after 1981 saved 148.7M life-years in 2013 across 22 countries using 3-way fixed-effects regression (disease-country-year). 95% CI [79.4M, 239.8M] propagated from Table 2 regression standard errors (β₀₋₁₁=-0.031±0.008, β₁₂₊=-0.057±0.013). | ~ Medium confidence | 95% CI: [79.4 million life-years, 240 million life-years] | Dist: Lognormal | Unit: life-years | Click to view details, calculation & sources\">149 million (95% CI: 79.4 million-240 million)</a>"
"pharma_life_years_saved_annual_cite": "@lichtenberg-life-years-saved-2019"
"pharma_lives_saved_annual": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-pharma_lives_saved_annual\" class=\"parameter-link\" data-source-ref=\"lichtenberg-life-years-saved-2019\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Annual lives saved by pharmaceutical interventions globally. Derived from Lichtenberg (2019) finding of 148.7M life-years saved, divided by assumed 12-year average life extension per beneficiary. Note: Life-years is the primary metric; lives is an approximation for intuitive communication. | Calculated from 2 inputs | ? Low confidence | Formula: PHARMA_LIFE_YEARS_SAVED_ANNUAL ÷ AVG_LIFE_EXTENSION_PER_BENEFICIARY | Unit: deaths | Click to view details, calculation & sources\">12.4 million deaths (95% CI: 7.6 million deaths-18.6 million deaths)</a>"
"pharma_lives_saved_annual_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-pharma_lives_saved_annual\" class=\"parameter-link\" data-source-ref=\"lichtenberg-life-years-saved-2019\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Annual lives saved by pharmaceutical interventions globally. Derived from Lichtenberg (2019) finding of 148.7M life-years saved, divided by assumed 12-year average life extension per beneficiary. Note: Life-years is the primary metric; lives is an approximation for intuitive communication. | Calculated from 2 inputs | ? Low confidence | Formula: PHARMA_LIFE_YEARS_SAVED_ANNUAL ÷ AVG_LIFE_EXTENSION_PER_BENEFICIARY | Unit: deaths | Click to view details, calculation & sources\">12.4 million (95% CI: 7.6 million-18.6 million)</a>"
"pharma_lives_saved_annual_latex": "$$\n\\begin{gathered}\nLives_{saved,annual} \\\\\n= \\frac{LY_{saved,annual}}{T_{ext}} \\\\\n= \\frac{149M}{12} \\\\\n= 12.4M\n\\end{gathered}\n$$"
"pharma_phase_2_3_cost_barrier": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-pharma_phase_2_3_cost_barrier\" class=\"parameter-link\" data-source-ref=\"drug-development-cost\" data-source-type=\"definition\" data-confidence=\"high\" title=\"Average Phase 2/3 efficacy testing cost per drug that pharma must fund (~60% of total drug development cost) | ✓ High confidence | Dist: Normal (SE: $200M) | Unit: USD | Click to view details, calculation & sources\">$1.56B (95% CI: $1.23B-$1.89B)</a>"
"pharma_roi_current_system_pct": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-pharma_roi_current_system_pct\" class=\"parameter-link\" data-source-ref=\"pharma-roi-current\" data-source-type=\"external\" data-peer-reviewed=\"true\" data-confidence=\"high\" title=\"ROI for pharma R&D (2022 historic low from Deloitte study of top 20 pharma companies, down from 6.8% in 2021, recovered to 5.9% in 2024) | ✓ High confidence | \U0001F4CA Peer-reviewed | Unit: percentage | Click to view details, calculation & sources\">1.2%</a>"
"pharma_roi_current_system_pct_cite": "@pharma-roi-current"
"pharma_success_rate_current_pct": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-pharma_success_rate_current_pct\" class=\"parameter-link\" data-source-ref=\"drug-trial-success-rate-12-pct\" data-source-type=\"external\" data-peer-reviewed=\"true\" data-confidence=\"high\" title=\"Percentage of drugs that reach market in current system | ✓ High confidence | \U0001F4CA Peer-reviewed | Unit: percentage | Click to view details, calculation & sources\">10%</a>"
"pharma_success_rate_current_pct_cite": "@drug-trial-success-rate-12-pct"
"phase_1_passed_compounds_global": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-phase_1_passed_compounds_global\" class=\"parameter-link\" data-source-ref=\"bio-clinical-development-2021\" data-source-type=\"external\" data-confidence=\"high\" title=\"Investigational compounds that have passed Phase I globally (midpoint of 5,000-10,000 range) | ✓ High confidence | 95% CI: [5 thousand compounds, 10 thousand compounds] | Dist: Uniform | Unit: compounds | Click to view details, calculation & sources\">7.5 thousand compounds (95% CI: 5 thousand compounds-10 thousand compounds)</a>"
"phase_1_passed_compounds_global_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-phase_1_passed_compounds_global\" class=\"parameter-link\" data-source-ref=\"bio-clinical-development-2021\" data-source-type=\"external\" data-confidence=\"high\" title=\"Investigational compounds that have passed Phase I globally (midpoint of 5,000-10,000 range) | ✓ High confidence | 95% CI: [5 thousand compounds, 10 thousand compounds] | Dist: Uniform | Unit: compounds | Click to view details, calculation & sources\">7.5 thousand (95% CI: 5 thousand-10 thousand)</a>"
"phase_1_passed_compounds_global_cite": "@bio-clinical-development-2021"
"phase_1_safety_duration_years": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-phase_1_safety_duration_years\" class=\"parameter-link\" data-source-ref=\"bio-clinical-development-2021\" data-source-type=\"external\" data-peer-reviewed=\"true\" data-confidence=\"high\" title=\"Phase I safety trial duration | ✓ High confidence | \U0001F4CA Peer-reviewed | Updated: 2021 | Unit: years | Click to view details, calculation & sources\">2.3 years</a>"
"phase_1_safety_duration_years_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-phase_1_safety_duration_years\" class=\"parameter-link\" data-source-ref=\"bio-clinical-development-2021\" data-source-type=\"external\" data-peer-reviewed=\"true\" data-confidence=\"high\" title=\"Phase I safety trial duration | ✓ High confidence | \U0001F4CA Peer-reviewed | Updated: 2021 | Unit: years | Click to view details, calculation & sources\">2.3</a>"
"phase_1_safety_duration_years_cite": "@bio-clinical-development-2021"
"phase_2_3_clinical_trial_cost_pct": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-phase_2_3_clinical_trial_cost_pct\" class=\"parameter-link\" data-source-ref=\"global-clinical-trials-market-2024\" data-source-type=\"external\" data-confidence=\"high\" title=\"Percentage of total clinical trial spending on Phase 2/3 efficacy testing (Phase 2: 24% + Phase 3: 45%) | ✓ High confidence | Dist: Normal (SE: 5%) | Unit: percentage | Click to view details, calculation & sources\">69% (95% CI: 61%-77%)</a>"
"phase_2_3_clinical_trial_cost_pct_cite": "@global-clinical-trials-market-2024"
"phase_3_trial_cost_min": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-phase_3_trial_cost_min\" class=\"parameter-link\" data-source-ref=\"phase-3-cost-per-trial-range\" data-source-type=\"external\" data-confidence=\"high\" title=\"Phase 3 trial total cost (minimum) | ✓ High confidence | Unit: USD/trial | Click to view details, calculation & sources\">$20M</a>"
"phase_3_trial_cost_min_cite": "@phase-3-cost-per-trial-range"
"pmc_pragmatic_trial_median_cost_per_patient": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-pmc_pragmatic_trial_median_cost_per_patient\" class=\"parameter-link\" data-source-ref=\"pmc-pragmatic-trial-cost\" data-source-type=\"external\" data-confidence=\"high\" title=\"Median cost per patient in embedded pragmatic clinical trials (Ramsberg & Platt 2018: 108 trials reviewed, 64 with cost data). IQR: $19-$478 (2015 USD). | ✓ High confidence | 95% CI: [$19, $478] | Dist: Lognormal | Unit: USD/patient | Click to view details, calculation & sources\">$97 (95% CI: $19-$478)</a>"
"pmc_pragmatic_trial_median_cost_per_patient_cite": "@pmc-pragmatic-trial-cost"
"polio_vaccination_roi": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-polio_vaccination_roi\" class=\"parameter-link\" data-source-ref=\"polio-vaccination-roi\" data-source-type=\"external\" data-confidence=\"high\" title=\"Return on investment from sustaining polio vaccination assets and integrating into expanded immunization programs | ✓ High confidence | Unit: ratio | Click to view details, calculation & sources\">39</a>"
"polio_vaccination_roi_cite": "@polio-vaccination-roi"
"political_dysfunction_global_efficiency_score": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-political_dysfunction_global_efficiency_score\" class=\"parameter-link\" data-source-ref=\"political-dysfunction-tax-paper-2025\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Global Governance Efficiency Score from Political Dysfunction Tax paper. E = Adjusted W_real / W_max, where W_real = GDP - waste, W_max = W_real + opportunity cost. Paper calculates 30-52% efficiency (using $110.9T adjusted / $211.9T maximum). This means civilization operates at roughly half its technological potential. | Calculated from 2 inputs | ? Low confidence | Formula: POLITICAL_DYSFUNCTION_GLOBAL_REALIZED_WELFARE_ADJUSTED / POLITICAL_DYSFUNCTION_GLOBAL_THEORETICAL_MAX_WELFARE | Unit: percent | Click to view details, calculation & sources\">51.9% (95% CI: 35.9%-57%)</a>"
"political_dysfunction_global_efficiency_score_latex": "$$\n\\begin{gathered}\nE_{gov} \\\\\n= \\frac{W_{real}}{W_{max}} \\\\\n= \\frac{\\$109T}{\\$210T} \\\\\n= 51.9\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nW_{real} \\\\\n= GDP_{global} - W_{waste} \\\\\n= \\$115T - \\$6.2T \\\\\n= \\$109T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nW_{waste} \\\\\n= W_{total,US} + W_{ff,global} \\\\\n= \\$4.9T + \\$1.3T \\\\\n= \\$6.2T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nW_{total,US} \\\\\n= W_{raw,US} \\times \\delta_{overlap} \\\\\n= \\$4.9T \\times 1 \\\\\n= \\$4.9T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nW_{raw,US} \\\\\n= W_{health} + W_{housing} + W_{military} + W_{regulatory} \\\\\n+ W_{tax} + W_{corporate} + W_{tariffs} + W_{drugs} \\\\\n+ W_{fossil} + W_{agriculture} \\\\\n= \\$1.2T + \\$1.4T + \\$615B + \\$580B + \\$546B + \\$181B + \\$160B \\\\\n+ \\$90B + \\$50B + \\$75B \\\\\n= \\$4.9T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nW_{max} = W_{real} + O_{total} = \\$109T + \\$101T = \\$210T\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nO_{total} \\\\\n= O_{health} + O_{science} + O_{lead} + O_{migration} \\\\\n= \\$34T + \\$4T + \\$6T + \\$57T \\\\\n= \\$101T\n\\end{gathered}\n$$"
"political_dysfunction_global_fossil_fuel_subsidies": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-political_dysfunction_global_fossil_fuel_subsidies\" class=\"parameter-link\" data-source-ref=\"political-dysfunction-tax-paper-2025\" data-source-type=\"external\" data-confidence=\"high\" title=\"Global explicit fossil fuel subsidies (governments undercharging for energy supply costs). IMF 2022 estimate. These subsidies actively encourage consumption of negative-externality goods, working against climate goals. Note: IMF implicit subsidies (externalities) are much larger (~$7T). | ✓ High confidence | 95% CI: [$1.1T, $1.5T] | Dist: Normal (SE: $100B) | Unit: USD | Click to view details, calculation & sources\">$1.3T (95% CI: $1.1T-$1.5T)</a>"
"political_dysfunction_global_fossil_fuel_subsidies_cite": "@political-dysfunction-tax-paper-2025"
"political_dysfunction_global_health_opportunity_cost": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-political_dysfunction_global_health_opportunity_cost\" class=\"parameter-link\" data-source-ref=\"political-dysfunction-tax-paper-2025\" data-source-type=\"external\" data-confidence=\"low\" title=\"Annual opportunity cost of slow-motion regulatory environment for health innovation. Murphy-Topel (2006) valued cancer cure at $50T (inflation-adjusted ~$100T in 2025). Longevity dividend of 1 extra year = $38T globally. PCTs could accelerate cures by 10+ years; NPV of 10-year delay at 3% discount = ~$25T. Conservative estimate: $34T annually in lives lost and healthspan denied. | ? Low confidence | 95% CI: [$20T, $80T] | Dist: Lognormal (SE: $15T) | Unit: USD | Click to view details, calculation & sources\">$34T (95% CI: $20T-$80T)</a>"
"political_dysfunction_global_health_opportunity_cost_cite": "@political-dysfunction-tax-paper-2025"
"political_dysfunction_global_lead_opportunity_cost": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-political_dysfunction_global_lead_opportunity_cost\" class=\"parameter-link\" data-source-ref=\"political-dysfunction-tax-paper-2025\" data-source-type=\"external\" data-confidence=\"high\" title=\"Global cost of lead exposure: World Bank/Lancet estimate. 765 million IQ points lost annually, 5.5 million premature CVD deaths. Cost to eliminate lead from paint, spices, batteries is trivial compared to damage. This is an arbitrage opportunity of immense scale that governance has failed to execute. | ✓ High confidence | 95% CI: [$4T, $8T] | Dist: Normal (SE: $1T) | Unit: USD | Click to view details, calculation & sources\">$6T (95% CI: $4T-$8T)</a>"
"political_dysfunction_global_lead_opportunity_cost_cite": "@political-dysfunction-tax-paper-2025"
"political_dysfunction_global_migration_opportunity_cost": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-political_dysfunction_global_migration_opportunity_cost\" class=\"parameter-link\" data-source-ref=\"political-dysfunction-tax-paper-2025\" data-source-type=\"external\" data-confidence=\"low\" title=\"Unrealized output from migration restrictions. Clemens (2011) calculated eliminating labor mobility barriers could increase global GDP by 50-150%. At $115T global GDP, lower bound = $57T; upper bound = $170T. Even 5% workforce mobility would generate trillions, exceeding all foreign aid ever given. This is the largest single distortion in the global economy. | ? Low confidence | 95% CI: [$57T, $170T] | Dist: Lognormal (SE: $30T) | Unit: USD | Click to view details, calculation & sources\">$57T (95% CI: $57T-$170T)</a>"
"political_dysfunction_global_migration_opportunity_cost_cite": "@political-dysfunction-tax-paper-2025"
"political_dysfunction_global_opportunity_cost_pct_gdp": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-political_dysfunction_global_opportunity_cost_pct_gdp\" class=\"parameter-link\" data-source-ref=\"political-dysfunction-tax-paper-2025\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Global opportunity cost as percentage of global GDP. $101T / $115T = ~88% of current GDP in unrealized potential. This represents the 'buried multipliers' of the global economy. | Calculated from 2 inputs | ? Low confidence | Formula: POLITICAL_DYSFUNCTION_GLOBAL_OPPORTUNITY_COST_TOTAL / GLOBAL_GDP_2025 | Unit: percent | Click to view details, calculation & sources\">87.8% (95% CI: 72.5%-166%)</a>"
"political_dysfunction_global_opportunity_cost_pct_gdp_latex": "$$\n\\begin{gathered}\nO_{\\%GDP} \\\\\n= \\frac{O_{total}}{GDP_{global}} \\\\\n= \\frac{\\$101T}{\\$115T} \\\\\n= 87.8\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nO_{total} \\\\\n= O_{health} + O_{science} + O_{lead} + O_{migration} \\\\\n= \\$34T + \\$4T + \\$6T + \\$57T \\\\\n= \\$101T\n\\end{gathered}\n$$"
"political_dysfunction_global_opportunity_cost_total": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-political_dysfunction_global_opportunity_cost_total\" class=\"parameter-link\" data-source-ref=\"political-dysfunction-tax-paper-2025\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Total global opportunity cost from governance failures: health innovation delays ($34T), underfunded science ($4T), lead poisoning ($6T), migration restrictions ($57T). Sum: $101T annually in unrealized potential. | Calculated from 4 inputs | ? Low confidence | Formula: HEALTH + SCIENCE + LEAD + MIGRATION | Unit: USD | Click to view details, calculation & sources\">$101T (95% CI: $83.3T-$191T)</a>"
"political_dysfunction_global_opportunity_cost_total_latex": "$$\n\\begin{gathered}\nO_{total} \\\\\n= O_{health} + O_{science} + O_{lead} + O_{migration} \\\\\n= \\$34T + \\$4T + \\$6T + \\$57T \\\\\n= \\$101T\n\\end{gathered}\n$$"
"political_dysfunction_global_realized_welfare_adjusted": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-political_dysfunction_global_realized_welfare_adjusted\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Adjusted realized welfare after subtracting measured governance waste from global GDP. | Calculated from 2 inputs | ~ Medium confidence | Formula: GLOBAL_GDP_2025 - POLITICAL_DYSFUNCTION_GLOBAL_WASTE_TOTAL | Unit: USD | Click to view details, calculation & sources\">$109T (95% CI: $107T-$110T)</a>"
"political_dysfunction_global_realized_welfare_adjusted_latex": "$$\n\\begin{gathered}\nW_{real} \\\\\n= GDP_{global} - W_{waste} \\\\\n= \\$115T - \\$6.2T \\\\\n= \\$109T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nW_{waste} \\\\\n= W_{total,US} + W_{ff,global} \\\\\n= \\$4.9T + \\$1.3T \\\\\n= \\$6.2T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nW_{total,US} \\\\\n= W_{raw,US} \\times \\delta_{overlap} \\\\\n= \\$4.9T \\times 1 \\\\\n= \\$4.9T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nW_{raw,US} \\\\\n= W_{health} + W_{housing} + W_{military} + W_{regulatory} \\\\\n+ W_{tax} + W_{corporate} + W_{tariffs} + W_{drugs} \\\\\n+ W_{fossil} + W_{agriculture} \\\\\n= \\$1.2T + \\$1.4T + \\$615B + \\$580B + \\$546B + \\$181B + \\$160B \\\\\n+ \\$90B + \\$50B + \\$75B \\\\\n= \\$4.9T\n\\end{gathered}\n$$"
"political_dysfunction_global_science_opportunity_cost": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-political_dysfunction_global_science_opportunity_cost\" class=\"parameter-link\" data-source-ref=\"political-dysfunction-tax-paper-2025\" data-source-type=\"external\" data-confidence=\"low\" title=\"Annual opportunity cost from underfunding high-ROI science (fusion, AI safety). Human Genome Project: $3.8B cost, $796B-1T impact (141:1 ROI). Fusion DEMO plant: $5-10B could solve energy/climate permanently. AI safety: <5% of capabilities spending despite existential stakes. Reallocating $200B from military waste at 20x multiplier = $4T foregone growth. | ? Low confidence | 95% CI: [$2T, $10T] | Dist: Lognormal (SE: $2T) | Unit: USD | Click to view details, calculation & sources\">$4T (95% CI: $2T-$10T)</a>"
"political_dysfunction_global_science_opportunity_cost_cite": "@political-dysfunction-tax-paper-2025"
"political_dysfunction_global_theoretical_max_welfare": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-political_dysfunction_global_theoretical_max_welfare\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Conservative theoretical maximum welfare under opportunity-cost recapture assumptions. | Calculated from 2 inputs | ? Low confidence | Formula: POLITICAL_DYSFUNCTION_GLOBAL_REALIZED_WELFARE_ADJUSTED + POLITICAL_DYSFUNCTION_GLOBAL_OPPORTUNITY_COST_TOTAL | Unit: USD | Click to view details, calculation & sources\">$210T (95% CI: $194T-$298T)</a>"
"political_dysfunction_global_theoretical_max_welfare_latex": "$$\nW_{max} = W_{real} + O_{total} = \\$109T + \\$101T = \\$210T\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nW_{real} \\\\\n= GDP_{global} - W_{waste} \\\\\n= \\$115T - \\$6.2T \\\\\n= \\$109T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nW_{waste} \\\\\n= W_{total,US} + W_{ff,global} \\\\\n= \\$4.9T + \\$1.3T \\\\\n= \\$6.2T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nW_{total,US} \\\\\n= W_{raw,US} \\times \\delta_{overlap} \\\\\n= \\$4.9T \\times 1 \\\\\n= \\$4.9T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nW_{raw,US} \\\\\n= W_{health} + W_{housing} + W_{military} + W_{regulatory} \\\\\n+ W_{tax} + W_{corporate} + W_{tariffs} + W_{drugs} \\\\\n+ W_{fossil} + W_{agriculture} \\\\\n= \\$1.2T + \\$1.4T + \\$615B + \\$580B + \\$546B + \\$181B + \\$160B \\\\\n+ \\$90B + \\$50B + \\$75B \\\\\n= \\$4.9T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nO_{total} \\\\\n= O_{health} + O_{science} + O_{lead} + O_{migration} \\\\\n= \\$34T + \\$4T + \\$6T + \\$57T \\\\\n= \\$101T\n\\end{gathered}\n$$"
"political_dysfunction_global_waste_total": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-political_dysfunction_global_waste_total\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Global waste deduction used in Political Dysfunction Tax efficiency accounting. Combines US governance waste estimate with global explicit fossil-fuel subsidies. | Calculated from 2 inputs | ~ Medium confidence | Formula: US_GOV_WASTE_TOTAL + POLITICAL_DYSFUNCTION_GLOBAL_FOSSIL_FUEL_SUBSIDIES | Unit: USD | Click to view details, calculation & sources\">$6.2T (95% CI: $4.75T-$7.97T)</a>"
"political_dysfunction_global_waste_total_latex": "$$\n\\begin{gathered}\nW_{waste} \\\\\n= W_{total,US} + W_{ff,global} \\\\\n= \\$4.9T + \\$1.3T \\\\\n= \\$6.2T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nW_{total,US} \\\\\n= W_{raw,US} \\times \\delta_{overlap} \\\\\n= \\$4.9T \\times 1 \\\\\n= \\$4.9T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nW_{raw,US} \\\\\n= W_{health} + W_{housing} + W_{military} + W_{regulatory} \\\\\n+ W_{tax} + W_{corporate} + W_{tariffs} + W_{drugs} \\\\\n+ W_{fossil} + W_{agriculture} \\\\\n= \\$1.2T + \\$1.4T + \\$615B + \\$580B + \\$546B + \\$181B + \\$160B \\\\\n+ \\$90B + \\$50B + \\$75B \\\\\n= \\$4.9T\n\\end{gathered}\n$$"
"political_dysfunction_tax_per_household_of_four_annual": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-political_dysfunction_tax_per_household_of_four_annual\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Annual household burden for a 4-person household implied by global Political Dysfunction Tax. | Calculated from 1 input | ? Low confidence | Formula: POLITICAL_DYSFUNCTION_TAX_PER_PERSON_ANNUAL × 4 | Unit: USD/year | Click to view details, calculation & sources\">$50.5K (95% CI: $42.6K-$93.7K)</a>"
"political_dysfunction_tax_per_household_of_four_annual_latex": "$$\nT_{pd,hh4} = T_{pd,pc} \\times 4 = \\$12.6K \\times 4 = \\$50.5K\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{pd,pc} \\\\\n= \\frac{O_{total}}{Pop_{global}} \\\\\n= \\frac{\\$101T}{8B} \\\\\n= \\$12.6K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nO_{total} \\\\\n= O_{health} + O_{science} + O_{lead} + O_{migration} \\\\\n= \\$34T + \\$4T + \\$6T + \\$57T \\\\\n= \\$101T\n\\end{gathered}\n$$"
"political_dysfunction_tax_per_person_annual": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-political_dysfunction_tax_per_person_annual\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Annual per-person burden implied by global Political Dysfunction Tax opportunity costs. | Calculated from 2 inputs | ? Low confidence | Formula: POLITICAL_DYSFUNCTION_GLOBAL_OPPORTUNITY_COST_TOTAL ÷ GLOBAL_POPULATION_2024 | Unit: USD/year | Click to view details, calculation & sources\">$12.6K (95% CI: $10.6K-$23.4K)</a>"
"political_dysfunction_tax_per_person_annual_latex": "$$\n\\begin{gathered}\nT_{pd,pc} \\\\\n= \\frac{O_{total}}{Pop_{global}} \\\\\n= \\frac{\\$101T}{8B} \\\\\n= \\$12.6K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nO_{total} \\\\\n= O_{health} + O_{science} + O_{lead} + O_{migration} \\\\\n= \\$34T + \\$4T + \\$6T + \\$57T \\\\\n= \\$101T\n\\end{gathered}\n$$"
"political_success_probability": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-political_success_probability\" class=\"parameter-link\" data-source-ref=\"icbl-ottawa-treaty\" data-source-type=\"external\" data-confidence=\"low\" title=\"Estimated probability of treaty ratification and sustained implementation. Central estimate 1% is conservative. This assumes 99% chance of failure.  | ? Low confidence | 95% CI: [0.1%, 10%] | Dist: Beta (SE: 2%) | Unit: rate | Click to view details, calculation & sources\">1% (95% CI: 0.1%-10%)</a>"
"political_success_probability_cite": "@icbl-ottawa-treaty"
"politician_post_office_career_value": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-politician_post_office_career_value\" class=\"parameter-link\" data-source-ref=\"opensecrets-revolving-door\" data-source-type=\"external\" data-confidence=\"medium\" title=\"Net present value of post-office career premium for average congressperson (10 years x $1M/year premium). Based on documented cases: Gephardt $7M/year, Daschle $2M+/year. | ~ Medium confidence | 95% CI: [$5M, $20M] | Unit: USD | Click to view details, calculation & sources\">$10M (95% CI: $5M-$20M)</a>"
"politician_post_office_career_value_cite": "@opensecrets-revolving-door"
"post_1962_drug_approval_reduction_pct": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-post_1962_drug_approval_reduction_pct\" class=\"parameter-link\" data-source-ref=\"post-1962-drug-approval-drop\" data-source-type=\"external\" data-confidence=\"high\" title=\"Reduction in new drug approvals after 1962 Kefauver-Harris Amendment (70% drop from 43→17 drugs/year) | ✓ High confidence | Updated: 1962-1970 | Unit: percentage | Click to view details, calculation & sources\">70%</a>"
"post_1962_drug_approval_reduction_pct_cite": "@post-1962-drug-approval-drop"
"post_ww2_military_cut_pct": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-post_ww2_military_cut_pct\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Percentage US military spending cut after WW2 (1945-1947, inflation-adjusted: $1,420B to $176B in constant 2024 dollars) | Calculated from 2 inputs | ✓ High confidence | Formula: 1 - (US_MILITARY_SPENDING_1947 / US_MILITARY_SPENDING_1945_PEAK) | Unit: percent | Click to view details, calculation & sources\">87.6%</a>"
"post_ww2_military_cut_pct_latex": "$$\n\\begin{gathered}\nCut_{WW2} \\\\\n= 1 - \\frac{Spending_{US,1947}}{Spending_{US,1945}} \\\\\n= 1 - \\frac{\\$176B}{\\$1.42T} \\\\\n= 87.6\\%\n\\end{gathered}\n$$"
"pragmatic_trial_cost_per_qaly": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-pragmatic_trial_cost_per_qaly\" class=\"parameter-link\" data-source-ref=\"recovery-trial-82x-cost-reduction\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Cost per QALY for pragmatic platform trials, calculated from RECOVERY trial data. Uses global impact methodology: trial cost divided by total QALYs from downstream adoption. This measures research efficiency (discovery value), not clinical intervention ICER. | Calculated from 2 inputs | ~ Medium confidence | Formula: TRIAL_COST ÷ TOTAL_QALYS_GENERATED | Unit: USD/QALY | Click to view details, calculation & sources\">$4 (95% CI: $1.71-$10)</a>"
"pragmatic_trial_cost_per_qaly_latex": "$$\n\\begin{gathered}\nCost_{pragmatic,QALY} \\\\\n= \\frac{Cost_{RECOVERY}}{QALY_{RECOVERY}} \\\\\n= \\frac{\\$20M}{5M} \\\\\n= \\$4\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nQALY_{RECOVERY} \\\\\n= Lives_{RECOVERY} \\times QALY_{COVID} \\\\\n= 1M \\times 5 \\\\\n= 5M\n\\end{gathered}\n$$"
"pre_1962_drug_development_cost_1980_usd": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-pre_1962_drug_development_cost_1980_usd\" class=\"parameter-link\" data-source-ref=\"pre-1962-drug-costs-baily-1972\" data-source-type=\"external\" data-peer-reviewed=\"true\" data-confidence=\"high\" title=\"Average drug development cost before 1962 FDA efficacy regulations, adjusted to 1980 dollars (Baily 1972) | ✓ High confidence | \U0001F4CA Peer-reviewed | 95% CI: [$5.2M, $7.8M] | Dist: Lognormal | Unit: USD_1980 | Click to view details, calculation & sources\">$6.5M (95% CI: $5.2M-$7.8M)</a>"
"pre_1962_drug_development_cost_1980_usd_cite": "@pre-1962-drug-costs-baily-1972"
"pre_1962_drug_development_cost_2024_usd": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-pre_1962_drug_development_cost_2024_usd\" class=\"parameter-link\" data-source-ref=\"pre-1962-drug-costs-baily-1972\" data-source-type=\"external\" data-peer-reviewed=\"true\" data-confidence=\"high\" title=\"Pre-1962 drug development cost adjusted to 2024 dollars ($6.5M × 3.80 = $24.7M, CPI-adjusted from Baily 1972) | ✓ High confidence | \U0001F4CA Peer-reviewed | 95% CI: [$19.5M, $30M] | Dist: Lognormal | Unit: USD | Click to view details, calculation & sources\">$24.7M (95% CI: $19.5M-$30M)</a>"
"pre_1962_drug_development_cost_2024_usd_cite": "@pre-1962-drug-costs-baily-1972"
"pre_1962_physician_count": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-pre_1962_physician_count\" class=\"parameter-link\" data-source-ref=\"pre-1962-physician-trials\" data-source-type=\"external\" data-confidence=\"low\" title=\"Estimated physicians conducting real-world efficacy trials pre-1962 (unverified estimate) | ? Low confidence | Unit: physicians | Click to view details, calculation & sources\">144 thousand physicians</a>"
"pre_1962_physician_count_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-pre_1962_physician_count\" class=\"parameter-link\" data-source-ref=\"pre-1962-physician-trials\" data-source-type=\"external\" data-confidence=\"low\" title=\"Estimated physicians conducting real-world efficacy trials pre-1962 (unverified estimate) | ? Low confidence | Unit: physicians | Click to view details, calculation & sources\">144 thousand</a>"
"pre_1962_physician_count_cite": "@pre-1962-physician-trials"
"pre_1962_validation_years": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-pre_1962_validation_years\" class=\"parameter-link\" data-source-ref=\"life-expectancy-increase-pre-1962\" data-source-type=\"definition\" data-confidence=\"high\" title=\"Years of empirical validation for physician-led pragmatic trials (1883-1960) | ✓ High confidence | Formula: 1960 - 1883 | Unit: years | Click to view details, calculation & sources\">77 years</a>"
"pre_1962_validation_years_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-pre_1962_validation_years\" class=\"parameter-link\" data-source-ref=\"life-expectancy-increase-pre-1962\" data-source-type=\"definition\" data-confidence=\"high\" title=\"Years of empirical validation for physician-led pragmatic trials (1883-1960) | ✓ High confidence | Formula: 1960 - 1883 | Unit: years | Click to view details, calculation & sources\">77</a>"
"prize_pool_annual_return": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-prize_pool_annual_return\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Canonical annual return used for PRIZE pool growth. Venture gross return + scale compression + crowd allocation alpha + home bias elimination. This is the structural pool return before contingent macro feedback loops. | Calculated from 4 inputs | ✓ High confidence | Formula: VENTURE_GROSS_RETURN + SCALE_COMPRESSION_FACTOR + WISHOCRATIC_CROWD_ALPHA + HOME_BIAS_ALPHA | Unit: percent | Click to view details, calculation & sources\">17.4% (95% CI: 10.6%-23.9%)</a>"
"prize_pool_annual_return_latex": "$$\n\\begin{gathered}\nr_{pool} \\\\\n= r_{VC,gross} + \\Delta r_{scale} + \\alpha_{crowd} \\\\\n+ \\alpha_{home} \\\\\n= 17\\% + -2.5\\% + 2.08\\% + 0.8\\% \\\\\n= 17.4\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\alpha_{crowd} \\\\\n= S_{alloc} \\times (Acc_{crowd} - Acc_{expert}) \\\\\n= 8\\% \\times (91\\% - 65\\%) \\\\\n= 2.08\\%\n\\end{gathered}\n$$"
"prize_pool_horizon_multiple": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-prize_pool_horizon_multiple\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Compound multiple for PRIZE pool growth over the resolution horizon (tied to the destructive economy 50% threshold year). | Calculated from 3 inputs | ✓ High confidence | Formula: (1 + PRIZE_POOL_ANNUAL_RETURN) ^ (DESTRUCTIVE_ECONOMY_50PCT_YEAR - DESTRUCTIVE_ECONOMY_BASE_YEAR) | Unit: x | Click to view details, calculation & sources\">11.1x (95% CI: 4.5x-24.9x)</a>"
"prize_pool_horizon_multiple_latex": "$$\nM_{pool} = (1 + r_{pool}) ^{Y_{50\\%} - Y_0}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nr_{pool} \\\\\n= r_{VC,gross} + \\Delta r_{scale} + \\alpha_{crowd} \\\\\n+ \\alpha_{home} \\\\\n= 17\\% + -2.5\\% + 2.08\\% + 0.8\\% \\\\\n= 17.4\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\alpha_{crowd} \\\\\n= S_{alloc} \\times (Acc_{crowd} - Acc_{expert}) \\\\\n= 8\\% \\times (91\\% - 65\\%) \\\\\n= 2.08\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nY_{50\\%} \\\\\n= Y_0 \\\\\n+ \\frac{\\ln\\left(0.50 / \\text{DESTRUCTIVE\\_PCT\\_GDP}\\right)}{\\ln\\left(1 + \\text{DESTRUCTIVE\\_GROWTH} - \\text{GDP\\_GROWTH}\\right)}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nr_{destruct:GDP} \\\\\n= \\frac{Cost_{destruct}}{GDP_{global}} \\\\\n= \\frac{\\$13.2T}{\\$115T} \\\\\n= 11.5\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{destruct} \\\\\n= Spending_{mil} + Cost_{cyber} \\\\\n= \\$2.72T + \\$10.5T \\\\\n= \\$13.2T\n\\end{gathered}\n$$"
"prize_pool_participation_rate": "<span class=\"parameter-definition\" title=\"Fraction of global investable financial assets that flow into the PRIZE pool. 1% central estimate parallels the 1% Treaty ask: 1% of your weapons money, 1% of your savings. | Unit: percent | Core definition\">1% (95% CI: 0.1%-10%)</span>"
"prize_pool_retirement_equivalent_principal": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-prize_pool_retirement_equivalent_principal\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Secondary PRIZE seed benchmark: initial principal required so that the pool can make two referred votes retirement-equivalent on success at the modeled global coordination target. This is a stronger-incentive visible-pool benchmark, not the minimum capital required to make 50% participation credible. | Calculated from 3 inputs | ✓ High confidence | Formula: GLOBAL_COORDINATION_TARGET_SUPPORTERS × RETIREMENT_EQUIVALENT_CLAIM_VALUE_TARGET / PRIZE_POOL_HORIZON_MULTIPLE | Unit: USD | Click to view details, calculation & sources\">$1.8T (95% CI: $1.04T-$3.35T)</a>"
"prize_pool_retirement_equivalent_principal_latex": "$$\n\\begin{gathered}\nP_{retire-eq} \\\\\n= N_{coord} \\times \\frac{V_{claim,target}}{M_{pool}}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{coord} \\\\\n= Pop_{global} \\times R_{coord} \\\\\n= 8B \\times 50\\% \\\\\n= 4B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nV_{claim,target} \\\\\n= V_{2claims,target} \\times 0.5 \\\\\n= \\$9.98K \\times 0.5 \\\\\n= \\$4.99K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nV_{2claims,target} \\\\\n= S_{annual,pc} \\times M_{retire} \\\\\n= \\$3.88K \\times 2.57 \\\\\n= \\$9.98K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nS_{annual,pc} \\\\\n= \\frac{S_{annual}}{Pop_{global}} \\\\\n= \\frac{\\$31.1T}{8B} \\\\\n= \\$3.88K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nS_{annual} \\\\\n= s_{global} \\times GDP_{global} \\\\\n= 27\\% \\times \\$115T \\\\\n= \\$31.1T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nM_{retire} = (1 + r_{retire}) ^{Y_{50\\%} - Y_0}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nY_{50\\%} \\\\\n= Y_0 \\\\\n+ \\frac{\\ln\\left(0.50 / \\text{DESTRUCTIVE\\_PCT\\_GDP}\\right)}{\\ln\\left(1 + \\text{DESTRUCTIVE\\_GROWTH} - \\text{GDP\\_GROWTH}\\right)}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nr_{destruct:GDP} \\\\\n= \\frac{Cost_{destruct}}{GDP_{global}} \\\\\n= \\frac{\\$13.2T}{\\$115T} \\\\\n= 11.5\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{destruct} \\\\\n= Spending_{mil} + Cost_{cyber} \\\\\n= \\$2.72T + \\$10.5T \\\\\n= \\$13.2T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nM_{pool} = (1 + r_{pool}) ^{Y_{50\\%} - Y_0}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nr_{pool} \\\\\n= r_{VC,gross} + \\Delta r_{scale} + \\alpha_{crowd} \\\\\n+ \\alpha_{home} \\\\\n= 17\\% + -2.5\\% + 2.08\\% + 0.8\\% \\\\\n= 17.4\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\alpha_{crowd} \\\\\n= S_{alloc} \\times (Acc_{crowd} - Acc_{expert}) \\\\\n= 8\\% \\times (91\\% - 65\\%) \\\\\n= 2.08\\%\n\\end{gathered}\n$$"
"prize_pool_size": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-prize_pool_size\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Terminal PRIZE pool size: global investable assets × participation rate × compound multiple over the resolution horizon. | Calculated from 3 inputs | ✓ High confidence | Formula: GLOBAL_INVESTABLE_ASSETS × PRIZE_POOL_PARTICIPATION_RATE × PRIZE_POOL_HORIZON_MULTIPLE | Unit: USD | Click to view details, calculation & sources\">$33.7T (95% CI: $1.37T-$286T)</a>"
"prize_pool_size_latex": "$$\n\\begin{gathered}\nPool \\\\\n= Assets_{invest} \\times R_{pool} \\times M_{pool} \\\\\n= \\$305T \\times 1\\% \\times 11.1 \\\\\n= \\$33.7T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nM_{pool} = (1 + r_{pool}) ^{Y_{50\\%} - Y_0}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nr_{pool} \\\\\n= r_{VC,gross} + \\Delta r_{scale} + \\alpha_{crowd} \\\\\n+ \\alpha_{home} \\\\\n= 17\\% + -2.5\\% + 2.08\\% + 0.8\\% \\\\\n= 17.4\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\alpha_{crowd} \\\\\n= S_{alloc} \\times (Acc_{crowd} - Acc_{expert}) \\\\\n= 8\\% \\times (91\\% - 65\\%) \\\\\n= 2.08\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nY_{50\\%} \\\\\n= Y_0 \\\\\n+ \\frac{\\ln\\left(0.50 / \\text{DESTRUCTIVE\\_PCT\\_GDP}\\right)}{\\ln\\left(1 + \\text{DESTRUCTIVE\\_GROWTH} - \\text{GDP\\_GROWTH}\\right)}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nr_{destruct:GDP} \\\\\n= \\frac{Cost_{destruct}}{GDP_{global}} \\\\\n= \\frac{\\$13.2T}{\\$115T} \\\\\n= 11.5\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{destruct} \\\\\n= Spending_{mil} + Cost_{cyber} \\\\\n= \\$2.72T + \\$10.5T \\\\\n= \\$13.2T\n\\end{gathered}\n$$"
"qalys_per_covid_death_averted": "<span class=\"parameter-definition\" title=\"Average QALYs gained per COVID death averted. Conservative estimate reflecting older age distribution of COVID mortality. See confidence_interval for range. | Unit: QALYs/death | Core definition\">5 QALYs/death (95% CI: 3 QALYs/death-10 QALYs/death)</span>"
"qalys_per_covid_death_averted_nounit": "<span class=\"parameter-definition\" title=\"Average QALYs gained per COVID death averted. Conservative estimate reflecting older age distribution of COVID mortality. See confidence_interval for range. | Unit: QALYs/death | Core definition\">5 (95% CI: 3-10)</span>"
"rare_diseases_count_global": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-rare_diseases_count_global\" class=\"parameter-link\" data-source-ref=\"95-pct-diseases-no-treatment\" data-source-type=\"external\" data-confidence=\"high\" title=\"Total number of rare diseases globally | ✓ High confidence | 95% CI: [6 thousand diseases, 10 thousand diseases] | Dist: Normal | Unit: diseases | Click to view details, calculation & sources\">7 thousand diseases (95% CI: 6 thousand diseases-10 thousand diseases)</a>"
"rare_diseases_count_global_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-rare_diseases_count_global\" class=\"parameter-link\" data-source-ref=\"95-pct-diseases-no-treatment\" data-source-type=\"external\" data-confidence=\"high\" title=\"Total number of rare diseases globally | ✓ High confidence | 95% CI: [6 thousand diseases, 10 thousand diseases] | Dist: Normal | Unit: diseases | Click to view details, calculation & sources\">7 thousand (95% CI: 6 thousand-10 thousand)</a>"
"rare_diseases_count_global_cite": "@95-pct-diseases-no-treatment"
"rd_spillover_multiplier": "<span class=\"parameter-definition\" title=\"R&D spillover multiplier: each $1 in directed medical research produces $2 in adjacent sector GDP growth (biotech, AI, computing, materials science, manufacturing). Conservative estimate; military R&D spillover produced the internet, GPS, jet engines. Medical R&D spillover already produced CRISPR, mRNA platforms, AI protein folding. | Unit: x | Core definition\">2x (95% CI: 1.5x-2.5x)</span>"
"recovery_trial_cost_per_patient": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-recovery_trial_cost_per_patient\" class=\"parameter-link\" data-source-ref=\"recovery-cost-500\" data-source-type=\"external\" data-confidence=\"high\" title=\"RECOVERY trial cost per patient. Note: RECOVERY was an outlier - hospital-based during COVID emergency, minimal extra procedures, existing NHS infrastructure, streamlined consent. Replicating this globally will be harder. | ✓ High confidence | 95% CI: [$400, $2.5K] | Dist: Lognormal | Unit: USD/patient | Click to view details, calculation & sources\">$500 (95% CI: $400-$2.5K)</a>"
"recovery_trial_cost_per_patient_cite": "@recovery-cost-500"
"recovery_trial_cost_reduction_factor": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-recovery_trial_cost_reduction_factor\" class=\"parameter-link\" data-source-ref=\"recovery-trial-82x-cost-reduction\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Cost reduction factor demonstrated by RECOVERY trial (traditional Phase 3 cost / RECOVERY cost per patient) | Calculated from 2 inputs | ✓ High confidence | Formula: TRADITIONAL_PHASE3_COST / RECOVERY_COST | Unit: multiplier | Click to view details, calculation & sources\">82x (95% CI: 50x-94.1x)</a>"
"recovery_trial_cost_reduction_factor_latex": "$$\n\\begin{gathered}\nk_{RECOVERY} \\\\\n= \\frac{Cost_{P3,pt}}{Cost_{RECOVERY,pt}} \\\\\n= \\frac{\\$41K}{\\$500} \\\\\n= 82\n\\end{gathered}\n$$"
"recovery_trial_global_lives_saved": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-recovery_trial_global_lives_saved\" class=\"parameter-link\" data-source-ref=\"recovery-trial-1m-lives-saved\" data-source-type=\"external\" data-confidence=\"medium\" title=\"Estimated lives saved globally by RECOVERY trial's dexamethasone discovery. NHS England estimate (March 2021). Based on Águas et al. Nature Communications 2021 methodology applying RECOVERY trial mortality reductions (36% ventilated, 18% oxygen) to global COVID hospitalizations. Wide uncertainty range reflects extrapolation assumptions. | ~ Medium confidence | 95% CI: [500 thousand lives, 2 million lives] | Dist: Lognormal | Unit: lives | Click to view details, calculation & sources\">1 million lives (95% CI: 500 thousand lives-2 million lives)</a>"
"recovery_trial_global_lives_saved_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-recovery_trial_global_lives_saved\" class=\"parameter-link\" data-source-ref=\"recovery-trial-1m-lives-saved\" data-source-type=\"external\" data-confidence=\"medium\" title=\"Estimated lives saved globally by RECOVERY trial's dexamethasone discovery. NHS England estimate (March 2021). Based on Águas et al. Nature Communications 2021 methodology applying RECOVERY trial mortality reductions (36% ventilated, 18% oxygen) to global COVID hospitalizations. Wide uncertainty range reflects extrapolation assumptions. | ~ Medium confidence | 95% CI: [500 thousand lives, 2 million lives] | Dist: Lognormal | Unit: lives | Click to view details, calculation & sources\">1 million (95% CI: 500 thousand-2 million)</a>"
"recovery_trial_global_lives_saved_cite": "@recovery-trial-1m-lives-saved"
"recovery_trial_total_cost": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-recovery_trial_total_cost\" class=\"parameter-link\" data-source-ref=\"recovery-trial-82x-cost-reduction\" data-source-type=\"external\" data-confidence=\"high\" title=\"Total cost of UK RECOVERY trial. Enrolled tens of thousands of patients across multiple treatment arms. Discovered dexamethasone reduces COVID mortality by ~1/3 in severe cases. | ✓ High confidence | 95% CI: [$15M, $25M] | Dist: Lognormal | Unit: USD | Click to view details, calculation & sources\">$20M (95% CI: $15M-$25M)</a>"
"recovery_trial_total_cost_cite": "@recovery-trial-82x-cost-reduction"
"recovery_trial_total_qalys_generated": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-recovery_trial_total_qalys_generated\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Total QALYs generated by RECOVERY trial's discoveries (lives saved × QALYs per life). Uses global impact methodology: counts all downstream health gains from the discovery. | Calculated from 2 inputs | ~ Medium confidence | Formula: LIVES_SAVED × QALYS_PER_DEATH_AVERTED | Unit: QALYs | Click to view details, calculation & sources\">5 million QALYs (95% CI: 1.51 million QALYs-14.3 million QALYs)</a>"
"recovery_trial_total_qalys_generated_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-recovery_trial_total_qalys_generated\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Total QALYs generated by RECOVERY trial's discoveries (lives saved × QALYs per life). Uses global impact methodology: counts all downstream health gains from the discovery. | Calculated from 2 inputs | ~ Medium confidence | Formula: LIVES_SAVED × QALYS_PER_DEATH_AVERTED | Unit: QALYs | Click to view details, calculation & sources\">5 million (95% CI: 1.51 million-14.3 million)</a>"
"recovery_trial_total_qalys_generated_latex": "$$\n\\begin{gathered}\nQALY_{RECOVERY} \\\\\n= Lives_{RECOVERY} \\times QALY_{COVID} \\\\\n= 1M \\times 5 \\\\\n= 5M\n\\end{gathered}\n$$"
"regulatory_delay_mean_age_of_death": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-regulatory_delay_mean_age_of_death\" class=\"parameter-link\" data-source-ref=\"who-global-health-estimates-2024\" data-source-type=\"external\" data-peer-reviewed=\"true\" data-confidence=\"medium\" title=\"Mean age of preventable death from post-safety efficacy testing regulatory delay (Phase 2-4) | ~ Medium confidence | \U0001F4CA Peer-reviewed | Dist: Normal (SE: 3 years) | Unit: years | Click to view details, calculation & sources\">62 years (95% CI: 57 years-66.9 years)</a>"
"regulatory_delay_mean_age_of_death_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-regulatory_delay_mean_age_of_death\" class=\"parameter-link\" data-source-ref=\"who-global-health-estimates-2024\" data-source-type=\"external\" data-peer-reviewed=\"true\" data-confidence=\"medium\" title=\"Mean age of preventable death from post-safety efficacy testing regulatory delay (Phase 2-4) | ~ Medium confidence | \U0001F4CA Peer-reviewed | Dist: Normal (SE: 3 years) | Unit: years | Click to view details, calculation & sources\">62 (95% CI: 57-66.9)</a>"
"regulatory_delay_mean_age_of_death_cite": "@who-global-health-estimates-2024"
"regulatory_delay_suffering_period_years": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-regulatory_delay_suffering_period_years\" class=\"parameter-link\" data-source-ref=\"who-global-health-estimates-2024\" data-source-type=\"external\" data-peer-reviewed=\"true\" data-confidence=\"medium\" title=\"Pre-death suffering period during post-safety efficacy testing delay (average years lived with untreated condition while awaiting Phase 2-4 completion) | ~ Medium confidence | \U0001F4CA Peer-reviewed | 95% CI: [4 years, 9 years] | Dist: Lognormal | Unit: years | Click to view details, calculation & sources\">6 years (95% CI: 4 years-9 years)</a>"
"regulatory_delay_suffering_period_years_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-regulatory_delay_suffering_period_years\" class=\"parameter-link\" data-source-ref=\"who-global-health-estimates-2024\" data-source-type=\"external\" data-peer-reviewed=\"true\" data-confidence=\"medium\" title=\"Pre-death suffering period during post-safety efficacy testing delay (average years lived with untreated condition while awaiting Phase 2-4 completion) | ~ Medium confidence | \U0001F4CA Peer-reviewed | 95% CI: [4 years, 9 years] | Dist: Lognormal | Unit: years | Click to view details, calculation & sources\">6 (95% CI: 4-9)</a>"
"regulatory_delay_suffering_period_years_cite": "@who-global-health-estimates-2024"
"retirement_equivalent_2_claims_target_payout": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-retirement_equivalent_2_claims_target_payout\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Target success-side payout for two referred votes: what one representative annual savings contribution would become in a conventional retirement account by PRIZE resolution. | Calculated from 2 inputs | ✓ High confidence | Formula: GLOBAL_ANNUAL_SAVINGS_PER_CAPITA × CONVENTIONAL_RETIREMENT_HORIZON_MULTIPLE | Unit: USD | Click to view details, calculation & sources\">$9.98K (95% CI: $7.7K-$12.7K)</a>"
"retirement_equivalent_2_claims_target_payout_latex": "$$\n\\begin{gathered}\nV_{2claims,target} \\\\\n= S_{annual,pc} \\times M_{retire} \\\\\n= \\$3.88K \\times 2.57 \\\\\n= \\$9.98K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nS_{annual,pc} \\\\\n= \\frac{S_{annual}}{Pop_{global}} \\\\\n= \\frac{\\$31.1T}{8B} \\\\\n= \\$3.88K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nS_{annual} \\\\\n= s_{global} \\times GDP_{global} \\\\\n= 27\\% \\times \\$115T \\\\\n= \\$31.1T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nM_{retire} = (1 + r_{retire}) ^{Y_{50\\%} - Y_0}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nY_{50\\%} \\\\\n= Y_0 \\\\\n+ \\frac{\\ln\\left(0.50 / \\text{DESTRUCTIVE\\_PCT\\_GDP}\\right)}{\\ln\\left(1 + \\text{DESTRUCTIVE\\_GROWTH} - \\text{GDP\\_GROWTH}\\right)}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nr_{destruct:GDP} \\\\\n= \\frac{Cost_{destruct}}{GDP_{global}} \\\\\n= \\frac{\\$13.2T}{\\$115T} \\\\\n= 11.5\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{destruct} \\\\\n= Spending_{mil} + Cost_{cyber} \\\\\n= \\$2.72T + \\$10.5T \\\\\n= \\$13.2T\n\\end{gathered}\n$$"
"retirement_equivalent_claim_value_target": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-retirement_equivalent_claim_value_target\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Target value of one referred-voter claim when two claims are meant to match the conventional-retirement future value of one representative annual savings contribution. | Calculated from 1 input | ✓ High confidence | Formula: RETIREMENT_EQUIVALENT_2_CLAIMS_TARGET_PAYOUT / 2 | Unit: USD | Click to view details, calculation & sources\">$4.99K (95% CI: $3.85K-$6.37K)</a>"
"retirement_equivalent_claim_value_target_latex": "$$\n\\begin{gathered}\nV_{claim,target} \\\\\n= V_{2claims,target} \\times 0.5 \\\\\n= \\$9.98K \\times 0.5 \\\\\n= \\$4.99K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nV_{2claims,target} \\\\\n= S_{annual,pc} \\times M_{retire} \\\\\n= \\$3.88K \\times 2.57 \\\\\n= \\$9.98K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nS_{annual,pc} \\\\\n= \\frac{S_{annual}}{Pop_{global}} \\\\\n= \\frac{\\$31.1T}{8B} \\\\\n= \\$3.88K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nS_{annual} \\\\\n= s_{global} \\times GDP_{global} \\\\\n= 27\\% \\times \\$115T \\\\\n= \\$31.1T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nM_{retire} = (1 + r_{retire}) ^{Y_{50\\%} - Y_0}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nY_{50\\%} \\\\\n= Y_0 \\\\\n+ \\frac{\\ln\\left(0.50 / \\text{DESTRUCTIVE\\_PCT\\_GDP}\\right)}{\\ln\\left(1 + \\text{DESTRUCTIVE\\_GROWTH} - \\text{GDP\\_GROWTH}\\right)}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nr_{destruct:GDP} \\\\\n= \\frac{Cost_{destruct}}{GDP_{global}} \\\\\n= \\frac{\\$13.2T}{\\$115T} \\\\\n= 11.5\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{destruct} \\\\\n= Spending_{mil} + Cost_{cyber} \\\\\n= \\$2.72T + \\$10.5T \\\\\n= \\$13.2T\n\\end{gathered}\n$$"
"safe_compounds_count": "<span class=\"parameter-definition\" title=\"Total safe compounds available for repurposing (FDA-approved + GRAS substances, midpoint of 7,000-12,000 range) | Unit: compounds | Core definition\">9.5 thousand compounds (95% CI: 7 thousand compounds-12 thousand compounds)</span>"
"safe_compounds_count_nounit": "<span class=\"parameter-definition\" title=\"Total safe compounds available for repurposing (FDA-approved + GRAS substances, midpoint of 7,000-12,000 range) | Unit: compounds | Core definition\">9.5 thousand (95% CI: 7 thousand-12 thousand)</span>"
"scale_compression_factor": "<span class=\"parameter-definition\" title=\"Diminishing-returns drag as the venture market expands ~15x (current global VC ~$300B/yr; Prize Fund deploys ~$4.7T/yr). More capital chasing deals compresses returns. Partially offset by market expansion (every viable idea gets funded, oligopolies face real competition). Point estimate is moderate; CI spans optimistic to pessimistic. | Unit: percent | Core definition\">-2.5% (95% CI: -5%--1%)</span>"
"seconds_per_minute": "<span class=\"parameter-link\" title=\"Parameter: SECONDS_PER_MINUTE\">60</span>"
"seconds_per_year": "<span class=\"parameter-link\" title=\"31,536,000\">31.5 million</span>"
"sept_11_deaths": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-sept_11_deaths\" class=\"parameter-link\" data-source-ref=\"september-11-memorial\" data-source-type=\"external\" data-confidence=\"high\" title=\"Total deaths in the September 11, 2001 attacks. 2,977 victims (excluding 19 hijackers). Used as a reference point for scale comparisons. | ✓ High confidence | Dist: Fixed | Unit: people | Click to view details, calculation & sources\">2.98 thousand people</a>"
"sept_11_deaths_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-sept_11_deaths\" class=\"parameter-link\" data-source-ref=\"september-11-memorial\" data-source-type=\"external\" data-confidence=\"high\" title=\"Total deaths in the September 11, 2001 attacks. 2,977 victims (excluding 19 hijackers). Used as a reference point for scale comparisons. | ✓ High confidence | Dist: Fixed | Unit: people | Click to view details, calculation & sources\">2.98 thousand</a>"
"sept_11_deaths_cite": "@september-11-memorial"
"sharing_breakeven_one_in_treaty": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-sharing_breakeven_one_in_treaty\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Breakeven probability expressed as '1 in N'. Forwarding has positive expected value if you believe there is at least a 1-in-N chance the plan works. For context, lightning strike odds are ~1 in 1.2 million. | Calculated from 1 input | ✓ High confidence | Formula: 1 / SHARING_BREAKEVEN_PROBABILITY_TREATY | Unit: ratio | Click to view details, calculation & sources\">58.1M (95% CI: 17.2M-167M)</a>"
"sharing_breakeven_one_in_treaty_latex": "$$\nN_{breakeven} = P_{breakeven} = 0 = 58.1M\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nP_{breakeven} \\\\\n= \\frac{C_{share}}{\\Delta Y_{lifetime,treaty}} \\\\\n= \\frac{\\$0.0599}{\\$3.48M} \\\\\n= 0\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nC_{share} \\\\\n= t_{share} \\times \\bar{w}_{hour} \\times 0.0167 \\\\\n= 0.5 \\times \\$7.19 \\times 0.0167 \\\\\n= \\$0.0599\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{w}_{hour} \\\\\n= \\frac{\\bar{y}_{0}}{H_{work}} \\\\\n= \\frac{\\$14.4K}{2{,}000} \\\\\n= \\$7.19\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{y}_{0} \\\\\n= \\frac{GDP_{global}}{Pop_{global}} \\\\\n= \\frac{\\$115T}{8B} \\\\\n= \\$14.4K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\Delta Y_{lifetime,treaty} \\\\\n= Y_{cum,treaty} - Y_{cum,earth} \\\\\n= \\$4.58M - \\$1.1M \\\\\n= \\$3.48M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nY_{cum,treaty} \\\\\n= \\bar{y}_0 \\cdot \\frac{(1+g_{pc,treaty})((1+g_{pc,treaty})^{20}-1)}{g_{pc,treaty}} \\\\\n+ \\bar{y}_{treaty,20} \\cdot \\frac{(1+g_{pc,base})((1+g_{pc,base})^{T_{remaining}-20}-1)}{g_{pc,base}}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{y}_{treaty,20} \\\\\n= \\frac{GDP_{treaty,20}}{Pop_{2045}} \\\\\n= \\frac{\\$919T}{9.2B} \\\\\n= \\$99.9K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nGDP_{treaty,20} \\\\\n= GDP_{global} \\times (1 + g_{base} + g_{redirect,treaty,20} \\\\\n+ g_{peace,treaty,20} + g_{cyber,treaty,20} \\\\\n+ g_{health,treaty,20})^{20}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{redirect,treaty,20} \\\\\n= \\bar{s}_{treaty,20} \\times \\Delta g_{30\\%} \\times m_{spillover} \\times 1.67 \\\\\n= 5.8\\% \\times 5.5\\% \\times 2 \\times 1.67 \\\\\n= 1.06\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{peace,treaty,20} \\\\\n= \\left(\\frac{Benefit_{peace,soc}}{GDP_{global}}\\right) \\times \\left(\\frac{\\bar{s}_{treaty,20}}{Reduce_{treaty}}\\right) \\times \\varepsilon_{conflict}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nBenefit_{peace,soc} \\\\\n= Cost_{war,total} \\times Reduce_{treaty} \\\\\n= \\$11.4T \\times 1\\% \\\\\n= \\$114B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,total} \\\\\n= Cost_{war,direct} + Cost_{war,indirect} \\\\\n= \\$7.66T + \\$3.7T \\\\\n= \\$11.4T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,direct} \\\\\n= Loss_{life,conflict} + Damage_{infra,total} \\\\\n+ Disruption_{trade} + Spending_{mil} \\\\\n= \\$2.45T + \\$1.88T + \\$616B + \\$2.72T \\\\\n= \\$7.66T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{life,conflict} \\\\\n= Cost_{combat,human} + Cost_{state,human} \\\\\n+ Cost_{terror,human} \\\\\n= \\$2.34T + \\$27B + \\$83B \\\\\n= \\$2.45T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDamage_{infra,total} \\\\\n= Damage_{comms} + Damage_{edu} + Damage_{energy} \\\\\n+ Damage_{health} + Damage_{transport} + Damage_{water} \\\\\n= \\$298B + \\$234B + \\$422B + \\$166B + \\$487B + \\$268B \\\\\n= \\$1.88T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDisruption_{trade} \\\\\n= Disruption_{currency} + Disruption_{energy} \\\\\n+ Disruption_{shipping} + Disruption_{supply} \\\\\n= \\$57.4B + \\$125B + \\$247B + \\$187B \\\\\n= \\$616B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,indirect} \\\\\n= Damage_{env} + Loss_{growth,mil} + Loss_{capital,conflict} \\\\\n+ Cost_{psych} + Cost_{refugee} + Cost_{vet} \\\\\n= \\$100B + \\$2.72T + \\$300B + \\$232B + \\$150B + \\$200B \\\\\n= \\$3.7T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{cyber,treaty,20} \\\\\n= \\left(\\frac{Cost_{cyber}}{GDP_{global}}\\right) \\times \\bar{s}_{treaty,20} \\times \\varepsilon_{conflict}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{health,treaty,20} \\\\\n= ((1 + f_{cure,20,treaty} \\times d_{disease} \\\\\n+ \\left(\\frac{Loss_{lag}}{GDP_{global}}\\right))^{\\frac{1}{20}}) - 1\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nf_{cure,20,treaty} \\\\\n= \\min\\left(1.0, Treatments_{new,ann} \\times (3 \\times min(k_{capacity} \\times 1, k_{capacity,max}) \\\\\n+ 4 \\times min(k_{capacity} \\times 2, k_{capacity,max}) \\\\\n+ 5 \\times min(k_{capacity} \\times 5, k_{capacity,max}) \\\\\n+ 8 \\times min(k_{capacity} \\times 10, k_{capacity,max})) / N_{untreated}\\right)\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity,max} \\\\\n= \\frac{N_{willing}}{Slots_{curr}} \\\\\n= \\frac{1.08B}{1.9M} \\\\\n= 566\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{willing} \\\\\n= N_{patients} \\times Pct_{willing} \\\\\n= 2.4B \\times 44.8\\% \\\\\n= 1.08B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{lag} \\\\\n= Deaths_{lag,total} \\times (LE_{global} - Age_{death,delay}) \\times Value_{QALY} \\\\\n= 102M \\times (79 - 62) \\times \\$150K \\\\\n= \\$259T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDeaths_{lag,total} \\\\\n= Lives_{saved,annual} \\times T_{lag} \\\\\n= 12.4M \\times 8.2 \\\\\n= 102M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLives_{saved,annual} \\\\\n= \\frac{LY_{saved,annual}}{T_{ext}} \\\\\n= \\frac{149M}{12} \\\\\n= 12.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{y}_{base,20} \\\\\n= \\frac{GDP_{base,20}}{Pop_{2045}} \\\\\n= \\frac{\\$188T}{9.2B} \\\\\n= \\$20.5K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nGDP_{base,20} = GDP_{global} \\times (1 + g_{base})^{20}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{remaining} \\\\\n= LE_{global} - Age_{median} \\\\\n= 79 - 30.5 \\\\\n= 48.5\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nY_{cum,earth} \\\\\n= \\bar{y}_0 \\cdot \\frac{(1+g_{pc,base})((1+g_{pc,base})^{T_{remaining}}-1)}{g_{pc,base}}\n\\end{gathered}\n$$"
"sharing_breakeven_probability_treaty": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-sharing_breakeven_probability_treaty\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Minimum probability that the plan works for forwarding to have positive expected value. EV > 0 when P(works) > cost_of_sharing / gain_if_works. Below this probability, not forwarding is rational. Above it, forwarding dominates. For context, the odds of being struck by lightning are ~1 in 1.2 million. | Calculated from 2 inputs | ✓ High confidence | Formula: SHARING_OPPORTUNITY_COST / TREATY_TRAJECTORY_LIFETIME_INCOME_GAIN_PER_CAPITA | Unit: probability | Click to view details, calculation & sources\">1.72e-08 probability (95% CI: 5.97e-09 probability-5.81e-08 probability)</a>"
"sharing_breakeven_probability_treaty_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-sharing_breakeven_probability_treaty\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Minimum probability that the plan works for forwarding to have positive expected value. EV > 0 when P(works) > cost_of_sharing / gain_if_works. Below this probability, not forwarding is rational. Above it, forwarding dominates. For context, the odds of being struck by lightning are ~1 in 1.2 million. | Calculated from 2 inputs | ✓ High confidence | Formula: SHARING_OPPORTUNITY_COST / TREATY_TRAJECTORY_LIFETIME_INCOME_GAIN_PER_CAPITA | Unit: probability | Click to view details, calculation & sources\">1.72e-08 (95% CI: 5.97e-09-5.81e-08)</a>"
"sharing_breakeven_probability_treaty_latex": "$$\n\\begin{gathered}\nP_{breakeven} \\\\\n= \\frac{C_{share}}{\\Delta Y_{lifetime,treaty}} \\\\\n= \\frac{\\$0.0599}{\\$3.48M} \\\\\n= 0\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nC_{share} \\\\\n= t_{share} \\times \\bar{w}_{hour} \\times 0.0167 \\\\\n= 0.5 \\times \\$7.19 \\times 0.0167 \\\\\n= \\$0.0599\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{w}_{hour} \\\\\n= \\frac{\\bar{y}_{0}}{H_{work}} \\\\\n= \\frac{\\$14.4K}{2{,}000} \\\\\n= \\$7.19\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{y}_{0} \\\\\n= \\frac{GDP_{global}}{Pop_{global}} \\\\\n= \\frac{\\$115T}{8B} \\\\\n= \\$14.4K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\Delta Y_{lifetime,treaty} \\\\\n= Y_{cum,treaty} - Y_{cum,earth} \\\\\n= \\$4.58M - \\$1.1M \\\\\n= \\$3.48M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nY_{cum,treaty} \\\\\n= \\bar{y}_0 \\cdot \\frac{(1+g_{pc,treaty})((1+g_{pc,treaty})^{20}-1)}{g_{pc,treaty}} \\\\\n+ \\bar{y}_{treaty,20} \\cdot \\frac{(1+g_{pc,base})((1+g_{pc,base})^{T_{remaining}-20}-1)}{g_{pc,base}}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{y}_{treaty,20} \\\\\n= \\frac{GDP_{treaty,20}}{Pop_{2045}} \\\\\n= \\frac{\\$919T}{9.2B} \\\\\n= \\$99.9K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nGDP_{treaty,20} \\\\\n= GDP_{global} \\times (1 + g_{base} + g_{redirect,treaty,20} \\\\\n+ g_{peace,treaty,20} + g_{cyber,treaty,20} \\\\\n+ g_{health,treaty,20})^{20}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{redirect,treaty,20} \\\\\n= \\bar{s}_{treaty,20} \\times \\Delta g_{30\\%} \\times m_{spillover} \\times 1.67 \\\\\n= 5.8\\% \\times 5.5\\% \\times 2 \\times 1.67 \\\\\n= 1.06\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{peace,treaty,20} \\\\\n= \\left(\\frac{Benefit_{peace,soc}}{GDP_{global}}\\right) \\times \\left(\\frac{\\bar{s}_{treaty,20}}{Reduce_{treaty}}\\right) \\times \\varepsilon_{conflict}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nBenefit_{peace,soc} \\\\\n= Cost_{war,total} \\times Reduce_{treaty} \\\\\n= \\$11.4T \\times 1\\% \\\\\n= \\$114B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,total} \\\\\n= Cost_{war,direct} + Cost_{war,indirect} \\\\\n= \\$7.66T + \\$3.7T \\\\\n= \\$11.4T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,direct} \\\\\n= Loss_{life,conflict} + Damage_{infra,total} \\\\\n+ Disruption_{trade} + Spending_{mil} \\\\\n= \\$2.45T + \\$1.88T + \\$616B + \\$2.72T \\\\\n= \\$7.66T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{life,conflict} \\\\\n= Cost_{combat,human} + Cost_{state,human} \\\\\n+ Cost_{terror,human} \\\\\n= \\$2.34T + \\$27B + \\$83B \\\\\n= \\$2.45T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{combat,human} \\\\\n= Deaths_{combat} \\times VSL \\\\\n= 234{,}000 \\times \\$10M \\\\\n= \\$2.34T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{state,human} \\\\\n= Deaths_{state} \\times VSL \\\\\n= 2{,}700 \\times \\$10M \\\\\n= \\$27B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{terror,human} \\\\\n= Deaths_{terror} \\times VSL \\\\\n= 8{,}300 \\times \\$10M \\\\\n= \\$83B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDamage_{infra,total} \\\\\n= Damage_{comms} + Damage_{edu} + Damage_{energy} \\\\\n+ Damage_{health} + Damage_{transport} + Damage_{water} \\\\\n= \\$298B + \\$234B + \\$422B + \\$166B + \\$487B + \\$268B \\\\\n= \\$1.88T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDisruption_{trade} \\\\\n= Disruption_{currency} + Disruption_{energy} \\\\\n+ Disruption_{shipping} + Disruption_{supply} \\\\\n= \\$57.4B + \\$125B + \\$247B + \\$187B \\\\\n= \\$616B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,indirect} \\\\\n= Damage_{env} + Loss_{growth,mil} + Loss_{capital,conflict} \\\\\n+ Cost_{psych} + Cost_{refugee} + Cost_{vet} \\\\\n= \\$100B + \\$2.72T + \\$300B + \\$232B + \\$150B + \\$200B \\\\\n= \\$3.7T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{cyber,treaty,20} \\\\\n= \\left(\\frac{Cost_{cyber}}{GDP_{global}}\\right) \\times \\bar{s}_{treaty,20} \\times \\varepsilon_{conflict}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{health,treaty,20} \\\\\n= ((1 + f_{cure,20,treaty} \\times d_{disease} \\\\\n+ \\left(\\frac{Loss_{lag}}{GDP_{global}}\\right))^{\\frac{1}{20}}) - 1\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nf_{cure,20,treaty} \\\\\n= \\min\\left(1.0, Treatments_{new,ann} \\times (3 \\times min(k_{capacity} \\times 1, k_{capacity,max}) \\\\\n+ 4 \\times min(k_{capacity} \\times 2, k_{capacity,max}) \\\\\n+ 5 \\times min(k_{capacity} \\times 5, k_{capacity,max}) \\\\\n+ 8 \\times min(k_{capacity} \\times 10, k_{capacity,max})) / N_{untreated}\\right)\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity,max} \\\\\n= \\frac{N_{willing}}{Slots_{curr}} \\\\\n= \\frac{1.08B}{1.9M} \\\\\n= 566\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{willing} \\\\\n= N_{patients} \\times Pct_{willing} \\\\\n= 2.4B \\times 44.8\\% \\\\\n= 1.08B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{lag} \\\\\n= Deaths_{lag,total} \\times (LE_{global} - Age_{death,delay}) \\times Value_{QALY} \\\\\n= 102M \\times (79 - 62) \\times \\$150K \\\\\n= \\$259T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDeaths_{lag,total} \\\\\n= Lives_{saved,annual} \\times T_{lag} \\\\\n= 12.4M \\times 8.2 \\\\\n= 102M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLives_{saved,annual} \\\\\n= \\frac{LY_{saved,annual}}{T_{ext}} \\\\\n= \\frac{149M}{12} \\\\\n= 12.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{y}_{base,20} \\\\\n= \\frac{GDP_{base,20}}{Pop_{2045}} \\\\\n= \\frac{\\$188T}{9.2B} \\\\\n= \\$20.5K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nGDP_{base,20} = GDP_{global} \\times (1 + g_{base})^{20}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{remaining} \\\\\n= LE_{global} - Age_{median} \\\\\n= 79 - 30.5 \\\\\n= 48.5\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nY_{cum,earth} \\\\\n= \\bar{y}_0 \\cdot \\frac{(1+g_{pc,base})((1+g_{pc,base})^{T_{remaining}}-1)}{g_{pc,base}}\n\\end{gathered}\n$$"
"sharing_opportunity_cost": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-sharing_opportunity_cost\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Dollar cost of 30 seconds at global average hourly income. The maximum downside of forwarding the message if the plan is impossible. | Calculated from 2 inputs | ✓ High confidence | Formula: (SHARING_TIME_MINUTES / 60) * GLOBAL_AVG_HOURLY_INCOME | Unit: USD | Click to view details, calculation & sources\">$0.06 (95% CI: $0.059-$0.061)</a>"
"sharing_opportunity_cost_latex": "$$\n\\begin{gathered}\nC_{share} \\\\\n= t_{share} \\times \\bar{w}_{hour} \\times 0.0167 \\\\\n= 0.5 \\times \\$7.19 \\times 0.0167 \\\\\n= \\$0.0599\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{w}_{hour} \\\\\n= \\frac{\\bar{y}_{0}}{H_{work}} \\\\\n= \\frac{\\$14.4K}{2{,}000} \\\\\n= \\$7.19\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{y}_{0} \\\\\n= \\frac{GDP_{global}}{Pop_{global}} \\\\\n= \\frac{\\$115T}{8B} \\\\\n= \\$14.4K\n\\end{gathered}\n$$"
"sharing_time_minutes": "<span class=\"parameter-definition\" title=\"Time to copy, paste, and send the recruitment message. 30 seconds. | Unit: minutes | Core definition\">0.5 minutes</span>"
"sharing_time_minutes_nounit": "<span class=\"parameter-definition\" title=\"Time to copy, paste, and send the recruitment message. 30 seconds. | Unit: minutes | Core definition\">0.5</span>"
"sharing_upside_downside_ratio_treaty": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-sharing_upside_downside_ratio_treaty\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Raw ratio of upside (lifetime income gain if plan works) to downside (cost of sharing if plan is impossible). Not expected value; see SHARING_BREAKEVEN_PROBABILITY_TREATY for the probability threshold that makes forwarding rational. | Calculated from 2 inputs | ✓ High confidence | Formula: TREATY_TRAJECTORY_LIFETIME_INCOME_GAIN_PER_CAPITA / SHARING_OPPORTUNITY_COST | Unit: x | Click to view details, calculation & sources\">58.1Mx (95% CI: 17.2Mx-167.4Mx)</a>"
"sharing_upside_downside_ratio_treaty_latex": "$$\n\\begin{gathered}\nk_{upside:downside} \\\\\n= \\frac{\\Delta Y_{lifetime,treaty}}{C_{share}} \\\\\n= \\frac{\\$3.48M}{\\$0.0599} \\\\\n= 58.1M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\Delta Y_{lifetime,treaty} \\\\\n= Y_{cum,treaty} - Y_{cum,earth} \\\\\n= \\$4.58M - \\$1.1M \\\\\n= \\$3.48M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nY_{cum,treaty} \\\\\n= \\bar{y}_0 \\cdot \\frac{(1+g_{pc,treaty})((1+g_{pc,treaty})^{20}-1)}{g_{pc,treaty}} \\\\\n+ \\bar{y}_{treaty,20} \\cdot \\frac{(1+g_{pc,base})((1+g_{pc,base})^{T_{remaining}-20}-1)}{g_{pc,base}}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{y}_{0} \\\\\n= \\frac{GDP_{global}}{Pop_{global}} \\\\\n= \\frac{\\$115T}{8B} \\\\\n= \\$14.4K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{y}_{treaty,20} \\\\\n= \\frac{GDP_{treaty,20}}{Pop_{2045}} \\\\\n= \\frac{\\$919T}{9.2B} \\\\\n= \\$99.9K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nGDP_{treaty,20} \\\\\n= GDP_{global} \\times (1 + g_{base} + g_{redirect,treaty,20} \\\\\n+ g_{peace,treaty,20} + g_{cyber,treaty,20} \\\\\n+ g_{health,treaty,20})^{20}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{redirect,treaty,20} \\\\\n= \\bar{s}_{treaty,20} \\times \\Delta g_{30\\%} \\times m_{spillover} \\times 1.67 \\\\\n= 5.8\\% \\times 5.5\\% \\times 2 \\times 1.67 \\\\\n= 1.06\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{peace,treaty,20} \\\\\n= \\left(\\frac{Benefit_{peace,soc}}{GDP_{global}}\\right) \\times \\left(\\frac{\\bar{s}_{treaty,20}}{Reduce_{treaty}}\\right) \\times \\varepsilon_{conflict}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nBenefit_{peace,soc} \\\\\n= Cost_{war,total} \\times Reduce_{treaty} \\\\\n= \\$11.4T \\times 1\\% \\\\\n= \\$114B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,total} \\\\\n= Cost_{war,direct} + Cost_{war,indirect} \\\\\n= \\$7.66T + \\$3.7T \\\\\n= \\$11.4T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,direct} \\\\\n= Loss_{life,conflict} + Damage_{infra,total} \\\\\n+ Disruption_{trade} + Spending_{mil} \\\\\n= \\$2.45T + \\$1.88T + \\$616B + \\$2.72T \\\\\n= \\$7.66T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{life,conflict} \\\\\n= Cost_{combat,human} + Cost_{state,human} \\\\\n+ Cost_{terror,human} \\\\\n= \\$2.34T + \\$27B + \\$83B \\\\\n= \\$2.45T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{combat,human} \\\\\n= Deaths_{combat} \\times VSL \\\\\n= 234{,}000 \\times \\$10M \\\\\n= \\$2.34T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{state,human} \\\\\n= Deaths_{state} \\times VSL \\\\\n= 2{,}700 \\times \\$10M \\\\\n= \\$27B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{terror,human} \\\\\n= Deaths_{terror} \\times VSL \\\\\n= 8{,}300 \\times \\$10M \\\\\n= \\$83B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDamage_{infra,total} \\\\\n= Damage_{comms} + Damage_{edu} + Damage_{energy} \\\\\n+ Damage_{health} + Damage_{transport} + Damage_{water} \\\\\n= \\$298B + \\$234B + \\$422B + \\$166B + \\$487B + \\$268B \\\\\n= \\$1.88T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDisruption_{trade} \\\\\n= Disruption_{currency} + Disruption_{energy} \\\\\n+ Disruption_{shipping} + Disruption_{supply} \\\\\n= \\$57.4B + \\$125B + \\$247B + \\$187B \\\\\n= \\$616B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,indirect} \\\\\n= Damage_{env} + Loss_{growth,mil} + Loss_{capital,conflict} \\\\\n+ Cost_{psych} + Cost_{refugee} + Cost_{vet} \\\\\n= \\$100B + \\$2.72T + \\$300B + \\$232B + \\$150B + \\$200B \\\\\n= \\$3.7T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{cyber,treaty,20} \\\\\n= \\left(\\frac{Cost_{cyber}}{GDP_{global}}\\right) \\times \\bar{s}_{treaty,20} \\times \\varepsilon_{conflict}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{health,treaty,20} \\\\\n= ((1 + f_{cure,20,treaty} \\times d_{disease} \\\\\n+ \\left(\\frac{Loss_{lag}}{GDP_{global}}\\right))^{\\frac{1}{20}}) - 1\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nf_{cure,20,treaty} \\\\\n= \\min\\left(1.0, Treatments_{new,ann} \\times (3 \\times min(k_{capacity} \\times 1, k_{capacity,max}) \\\\\n+ 4 \\times min(k_{capacity} \\times 2, k_{capacity,max}) \\\\\n+ 5 \\times min(k_{capacity} \\times 5, k_{capacity,max}) \\\\\n+ 8 \\times min(k_{capacity} \\times 10, k_{capacity,max})) / N_{untreated}\\right)\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity,max} \\\\\n= \\frac{N_{willing}}{Slots_{curr}} \\\\\n= \\frac{1.08B}{1.9M} \\\\\n= 566\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{willing} \\\\\n= N_{patients} \\times Pct_{willing} \\\\\n= 2.4B \\times 44.8\\% \\\\\n= 1.08B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{lag} \\\\\n= Deaths_{lag,total} \\times (LE_{global} - Age_{death,delay}) \\times Value_{QALY} \\\\\n= 102M \\times (79 - 62) \\times \\$150K \\\\\n= \\$259T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDeaths_{lag,total} \\\\\n= Lives_{saved,annual} \\times T_{lag} \\\\\n= 12.4M \\times 8.2 \\\\\n= 102M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLives_{saved,annual} \\\\\n= \\frac{LY_{saved,annual}}{T_{ext}} \\\\\n= \\frac{149M}{12} \\\\\n= 12.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{y}_{base,20} \\\\\n= \\frac{GDP_{base,20}}{Pop_{2045}} \\\\\n= \\frac{\\$188T}{9.2B} \\\\\n= \\$20.5K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nGDP_{base,20} = GDP_{global} \\times (1 + g_{base})^{20}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{remaining} \\\\\n= LE_{global} - Age_{median} \\\\\n= 79 - 30.5 \\\\\n= 48.5\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nY_{cum,earth} \\\\\n= \\bar{y}_0 \\cdot \\frac{(1+g_{pc,base})((1+g_{pc,base})^{T_{remaining}}-1)}{g_{pc,base}}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nC_{share} \\\\\n= t_{share} \\times \\bar{w}_{hour} \\times 0.0167 \\\\\n= 0.5 \\times \\$7.19 \\times 0.0167 \\\\\n= \\$0.0599\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{w}_{hour} \\\\\n= \\frac{\\bar{y}_{0}}{H_{work}} \\\\\n= \\frac{\\$14.4K}{2{,}000} \\\\\n= \\$7.19\n\\end{gathered}\n$$"
"singapore_gdp_per_capita_ppp": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-singapore_gdp_per_capita_ppp\" class=\"parameter-link\" data-source-ref=\"worldbank-singapore-gdp\" data-source-type=\"external\" data-confidence=\"high\" title=\"Singapore GDP per capita (PPP-adjusted). Among highest in world, demonstrating that lean government can coexist with prosperity. | ✓ High confidence | Dist: Fixed | Unit: USD | Click to view details, calculation & sources\">$105K</a>"
"singapore_gdp_per_capita_ppp_cite": "@worldbank-singapore-gdp"
"singapore_govt_spending_pct_gdp": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-singapore_govt_spending_pct_gdp\" class=\"parameter-link\" data-source-ref=\"imf-singapore-spending\" data-source-type=\"external\" data-confidence=\"high\" title=\"Singapore government spending as percentage of GDP. Less than HALF the US rate (15% vs 38%) yet achieves excellent outcomes through efficiency. | ✓ High confidence | Dist: Fixed | Unit: percent | Click to view details, calculation & sources\">1500%</a>"
"singapore_govt_spending_pct_gdp_cite": "@imf-singapore-spending"
"singapore_life_expectancy": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-singapore_life_expectancy\" class=\"parameter-link\" data-source-ref=\"who-life-expectancy\" data-source-type=\"external\" data-confidence=\"high\" title=\"Singapore life expectancy at birth. 6.6 years LONGER than US (84.1 vs 77.5) despite government spending at less than half the rate. | ✓ High confidence | Dist: Fixed | Unit: years | Click to view details, calculation & sources\">84.1 years</a>"
"singapore_life_expectancy_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-singapore_life_expectancy\" class=\"parameter-link\" data-source-ref=\"who-life-expectancy\" data-source-type=\"external\" data-confidence=\"high\" title=\"Singapore life expectancy at birth. 6.6 years LONGER than US (84.1 vs 77.5) despite government spending at less than half the rate. | ✓ High confidence | Dist: Fixed | Unit: years | Click to view details, calculation & sources\">84.1</a>"
"singapore_life_expectancy_cite": "@who-life-expectancy"
"smallpox_eradication_roi": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-smallpox_eradication_roi\" class=\"parameter-link\" data-source-ref=\"smallpox-eradication-roi\" data-source-type=\"external\" data-confidence=\"high\" title=\"Return on investment from smallpox eradication campaign | ✓ High confidence | Unit: ratio | Click to view details, calculation & sources\">280</a>"
"smallpox_eradication_roi_cite": "@smallpox-eradication-roi"
"smallpox_eradication_total_benefit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-smallpox_eradication_total_benefit\" class=\"parameter-link\" data-source-ref=\"smallpox-eradication-roi\" data-source-type=\"external\" data-confidence=\"high\" title=\"Total economic benefit from smallpox eradication campaign | ✓ High confidence | Unit: USD | Click to view details, calculation & sources\">$1.42B</a>"
"smallpox_eradication_total_benefit_cite": "@smallpox-eradication-roi"
"smoking_cessation_annual_benefit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-smoking_cessation_annual_benefit\" class=\"parameter-link\" data-source-ref=\"life-expectancy-gains-smoking-reduction\" data-source-type=\"external\" data-confidence=\"high\" title=\"Estimated annual global economic benefit from smoking cessation programs | ✓ High confidence | Unit: USD/year | Click to view details, calculation & sources\">$12B</a>"
"smoking_cessation_annual_benefit_cite": "@life-expectancy-gains-smoking-reduction"
"standard_economic_qaly_value_usd": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-standard_economic_qaly_value_usd\" class=\"parameter-link\" data-source-ref=\"qaly-value\" data-source-type=\"external\" data-confidence=\"high\" title=\"Standard economic value per QALY | ✓ High confidence | Dist: Normal (SE: $30K) | Unit: USD/QALY | Click to view details, calculation & sources\">$150K (95% CI: $100K-$199K)</a>"
"standard_economic_qaly_value_usd_cite": "@qaly-value"
"standard_qalys_per_life_saved": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-standard_qalys_per_life_saved\" class=\"parameter-link\" data-source-ref=\"qaly-value\" data-source-type=\"external\" data-confidence=\"high\" title=\"Standard QALYs per life saved (WHO life tables) | ✓ High confidence | Dist: Normal (SE: 7 QALYs/life) | Unit: QALYs/life | Click to view details, calculation & sources\">35 QALYs/life (95% CI: 23.3 QALYs/life-46.5 QALYs/life)</a>"
"standard_qalys_per_life_saved_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-standard_qalys_per_life_saved\" class=\"parameter-link\" data-source-ref=\"qaly-value\" data-source-type=\"external\" data-confidence=\"high\" title=\"Standard QALYs per life saved (WHO life tables) | ✓ High confidence | Dist: Normal (SE: 7 QALYs/life) | Unit: QALYs/life | Click to view details, calculation & sources\">35 (95% CI: 23.3-46.5)</a>"
"standard_qalys_per_life_saved_cite": "@qaly-value"
"status_quo_avg_years_to_first_treatment": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-status_quo_avg_years_to_first_treatment\" class=\"parameter-link\" data-source-ref=\"status-quo-cure-timeline-estimate\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Average years until first treatment discovered for a typical disease under current system. At current discovery rates, the average disease waits half the total exploration time (~443/2 = ~222 years). | Calculated from 1 input | ? Low confidence | Formula: STATUS_QUO_QUEUE_CLEARANCE_YEARS ÷ 2 | Unit: years | Click to view details, calculation & sources\">222 years (95% CI: 162 years-356 years)</a>"
"status_quo_avg_years_to_first_treatment_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-status_quo_avg_years_to_first_treatment\" class=\"parameter-link\" data-source-ref=\"status-quo-cure-timeline-estimate\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Average years until first treatment discovered for a typical disease under current system. At current discovery rates, the average disease waits half the total exploration time (~443/2 = ~222 years). | Calculated from 1 input | ? Low confidence | Formula: STATUS_QUO_QUEUE_CLEARANCE_YEARS ÷ 2 | Unit: years | Click to view details, calculation & sources\">222 (95% CI: 162-356)</a>"
"status_quo_avg_years_to_first_treatment_latex": "$$\n\\begin{gathered}\nT_{first,SQ} \\\\\n= T_{queue,SQ} \\times 0.5 \\\\\n= 443 \\times 0.5 \\\\\n= 222\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{queue,SQ} \\\\\n= \\frac{N_{untreated}}{Treatments_{new,ann}} \\\\\n= \\frac{6{,}650}{15} \\\\\n= 443\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$"
"status_quo_queue_clearance_years": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-status_quo_queue_clearance_years\" class=\"parameter-link\" data-source-ref=\"status-quo-cure-timeline-estimate\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Years to explore the entire therapeutic search space under current system. At current discovery rate of ~15 diseases/year getting first treatments, finding treatments for all ~6,650 untreated diseases would take ~443 years. | Calculated from 2 inputs | ? Low confidence | Formula: DISEASES_WITHOUT_EFFECTIVE_TREATMENT ÷ NEW_DISEASE_FIRST_TREATMENTS_PER_YEAR | Unit: years | Click to view details, calculation & sources\">443 years (95% CI: 324 years-712 years)</a>"
"status_quo_queue_clearance_years_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-status_quo_queue_clearance_years\" class=\"parameter-link\" data-source-ref=\"status-quo-cure-timeline-estimate\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Years to explore the entire therapeutic search space under current system. At current discovery rate of ~15 diseases/year getting first treatments, finding treatments for all ~6,650 untreated diseases would take ~443 years. | Calculated from 2 inputs | ? Low confidence | Formula: DISEASES_WITHOUT_EFFECTIVE_TREATMENT ÷ NEW_DISEASE_FIRST_TREATMENTS_PER_YEAR | Unit: years | Click to view details, calculation & sources\">443 (95% CI: 324-712)</a>"
"status_quo_queue_clearance_years_latex": "$$\n\\begin{gathered}\nT_{queue,SQ} \\\\\n= \\frac{N_{untreated}}{Treatments_{new,ann}} \\\\\n= \\frac{6{,}650}{15} \\\\\n= 443\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$"
"sugar_subsidy_cost_per_person_annual": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-sugar_subsidy_cost_per_person_annual\" class=\"parameter-link\" data-source-ref=\"sugar-subsidies-cost\" data-source-type=\"external\" data-confidence=\"high\" title=\"Annual cost of sugar subsidies per person | ✓ High confidence | Unit: USD/person/year | Click to view details, calculation & sources\">$10</a>"
"sugar_subsidy_cost_per_person_annual_cite": "@sugar-subsidies-cost"
"switzerland_defense_spending_pct": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-switzerland_defense_spending_pct\" class=\"parameter-link\" data-source-ref=\"swiss-military-budget-0-7-pct-gdp\" data-source-type=\"external\" data-confidence=\"high\" title=\"Switzerland's defense spending as percentage of GDP (0.7%) | ✓ High confidence | Unit: rate | Click to view details, calculation & sources\">0.7%</a>"
"switzerland_defense_spending_pct_cite": "@swiss-military-budget-0-7-pct-gdp"
"switzerland_gdp_per_capita_k": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-switzerland_gdp_per_capita_k\" class=\"parameter-link\" data-source-ref=\"swiss-vs-us-gdp-per-capita\" data-source-type=\"external\" data-confidence=\"high\" title=\"Switzerland GDP per capita | ✓ High confidence | Unit: USD | Click to view details, calculation & sources\">$93K</a>"
"switzerland_gdp_per_capita_k_cite": "@swiss-vs-us-gdp-per-capita"
"switzerland_govt_spending_pct_gdp": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-switzerland_govt_spending_pct_gdp\" class=\"parameter-link\" data-source-ref=\"oecd-govt-spending\" data-source-type=\"external\" data-confidence=\"high\" title=\"Switzerland government spending as percentage of GDP. 3 percentage points LOWER than US (35% vs 38%) yet achieves dramatically better outcomes. | ✓ High confidence | Dist: Fixed | Unit: percent | Click to view details, calculation & sources\">3500%</a>"
"switzerland_govt_spending_pct_gdp_cite": "@oecd-govt-spending"
"switzerland_life_expectancy": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-switzerland_life_expectancy\" class=\"parameter-link\" data-source-ref=\"who-life-expectancy\" data-source-type=\"external\" data-confidence=\"high\" title=\"Switzerland life expectancy at birth. 6.5 years LONGER than US (84.0 vs 77.5) despite lower government spending as % of GDP. | ✓ High confidence | Dist: Fixed | Unit: years | Click to view details, calculation & sources\">84 years</a>"
"switzerland_life_expectancy_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-switzerland_life_expectancy\" class=\"parameter-link\" data-source-ref=\"who-life-expectancy\" data-source-type=\"external\" data-confidence=\"high\" title=\"Switzerland life expectancy at birth. 6.5 years LONGER than US (84.0 vs 77.5) despite lower government spending as % of GDP. | ✓ High confidence | Dist: Fixed | Unit: years | Click to view details, calculation & sources\">84</a>"
"switzerland_life_expectancy_cite": "@who-life-expectancy"
"switzerland_median_income_ppp": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-switzerland_median_income_ppp\" class=\"parameter-link\" data-source-ref=\"oecd-median-income\" data-source-type=\"external\" data-confidence=\"medium\" title=\"Switzerland median household income (PPP-adjusted). Higher than US when adjusted for cost of healthcare and other expenses. | ~ Medium confidence | Dist: Fixed | Unit: USD | Click to view details, calculation & sources\">$65K</a>"
"switzerland_median_income_ppp_cite": "@oecd-median-income"
"terrorism_deaths_911": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-terrorism_deaths_911\" class=\"parameter-link\" data-source-ref=\"chance-of-dying-from-terrorism-1-in-30m\" data-source-type=\"external\" data-confidence=\"high\" title=\"Deaths from 9/11 terrorist attacks | ✓ High confidence | Dist: Fixed | Unit: deaths | Click to view details, calculation & sources\">3 thousand deaths</a>"
"terrorism_deaths_911_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-terrorism_deaths_911\" class=\"parameter-link\" data-source-ref=\"chance-of-dying-from-terrorism-1-in-30m\" data-source-type=\"external\" data-confidence=\"high\" title=\"Deaths from 9/11 terrorist attacks | ✓ High confidence | Dist: Fixed | Unit: deaths | Click to view details, calculation & sources\">3 thousand</a>"
"terrorism_deaths_911_cite": "@chance-of-dying-from-terrorism-1-in-30m"
"tested_relationships_estimate": "<span class=\"parameter-definition\" title=\"Estimated drug-disease relationships actually tested (approved uses + repurposed + failed trials, midpoint of 15,000-50,000 range) | Unit: relationships | Core definition\">32.5 thousand relationships (95% CI: 15 thousand relationships-50 thousand relationships)</span>"
"tested_relationships_estimate_nounit": "<span class=\"parameter-definition\" title=\"Estimated drug-disease relationships actually tested (approved uses + repurposed + failed trials, midpoint of 15,000-50,000 range) | Unit: relationships | Core definition\">32.5 thousand (95% CI: 15 thousand-50 thousand)</span>"
"thalidomide_cases_worldwide": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-thalidomide_cases_worldwide\" class=\"parameter-link\" data-source-ref=\"thalidomide-scandal\" data-source-type=\"external\" data-confidence=\"medium\" title=\"Total thalidomide birth defect cases worldwide (1957-1962) | ~ Medium confidence | 95% CI: [10 thousand cases, 20 thousand cases] | Dist: Lognormal | Unit: cases | Click to view details, calculation & sources\">15 thousand cases (95% CI: 10 thousand cases-20 thousand cases)</a>"
"thalidomide_cases_worldwide_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-thalidomide_cases_worldwide\" class=\"parameter-link\" data-source-ref=\"thalidomide-scandal\" data-source-type=\"external\" data-confidence=\"medium\" title=\"Total thalidomide birth defect cases worldwide (1957-1962) | ~ Medium confidence | 95% CI: [10 thousand cases, 20 thousand cases] | Dist: Lognormal | Unit: cases | Click to view details, calculation & sources\">15 thousand (95% CI: 10 thousand-20 thousand)</a>"
"thalidomide_cases_worldwide_cite": "@thalidomide-scandal"
"thalidomide_dalys_per_event": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-thalidomide_dalys_per_event\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Total DALYs per US-scale thalidomide event (YLL + YLD) | Calculated from 2 inputs | ~ Medium confidence | Formula: YLL + YLD | Unit: DALYs | Click to view details, calculation & sources\">41.8 thousand DALYs (95% CI: 24.8 thousand DALYs-67.1 thousand DALYs)</a>"
"thalidomide_dalys_per_event_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-thalidomide_dalys_per_event\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Total DALYs per US-scale thalidomide event (YLL + YLD) | Calculated from 2 inputs | ~ Medium confidence | Formula: YLL + YLD | Unit: DALYs | Click to view details, calculation & sources\">41.8 thousand (95% CI: 24.8 thousand-67.1 thousand)</a>"
"thalidomide_dalys_per_event_latex": "$$\n\\begin{gathered}\nDALY_{thal} \\\\\n= YLD_{thal} + YLL_{thal} \\\\\n= 13{,}000 + 28{,}800 \\\\\n= 41{,}800\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nYLD_{thal} \\\\\n= DW_{thal} \\times N_{thal,survive} \\times LE_{thal} \\\\\n= 0.4 \\times 540 \\times 60 \\\\\n= 13{,}000\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{thal,survive} \\\\\n= N_{thal,US,prevent} \\times (1 - Rate_{thal,mort}) \\\\\n= 900 \\times (1 - 40\\%) \\\\\n= 540\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{thal,US,prevent} \\\\\n= N_{thal,global} \\times Pct_{US,1960} \\\\\n= 15{,}000 \\times 6\\% \\\\\n= 900\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nYLL_{thal} \\\\\n= Deaths_{thal} \\times 80 \\\\\n= 360 \\times 80 \\\\\n= 28{,}800\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDeaths_{thal} \\\\\n= Rate_{thal,mort} \\times N_{thal,US,prevent} \\\\\n= 40\\% \\times 900 \\\\\n= 360\n\\end{gathered}\n$$"
"thalidomide_deaths_per_event": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-thalidomide_deaths_per_event\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Deaths per US-scale thalidomide event | Calculated from 2 inputs | ~ Medium confidence | Formula: US_CASES × MORTALITY_RATE | Unit: deaths | Click to view details, calculation & sources\">360 deaths (95% CI: 223 deaths-556 deaths)</a>"
"thalidomide_deaths_per_event_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-thalidomide_deaths_per_event\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Deaths per US-scale thalidomide event | Calculated from 2 inputs | ~ Medium confidence | Formula: US_CASES × MORTALITY_RATE | Unit: deaths | Click to view details, calculation & sources\">360 (95% CI: 223-556)</a>"
"thalidomide_deaths_per_event_latex": "$$\n\\begin{gathered}\nDeaths_{thal} \\\\\n= Rate_{thal,mort} \\times N_{thal,US,prevent} \\\\\n= 40\\% \\times 900 \\\\\n= 360\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{thal,US,prevent} \\\\\n= N_{thal,global} \\times Pct_{US,1960} \\\\\n= 15{,}000 \\times 6\\% \\\\\n= 900\n\\end{gathered}\n$$"
"thalidomide_disability_weight": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-thalidomide_disability_weight\" class=\"parameter-link\" data-source-ref=\"thalidomide-survivors-health\" data-source-type=\"external\" data-confidence=\"medium\" title=\"Disability weight for thalidomide survivors (limb deformities, organ damage) | ~ Medium confidence | 95% CI: [0.32:1, 0.48:1] | Dist: Lognormal | Unit: ratio | Click to view details, calculation & sources\">0.4 (95% CI: 0.32-0.48)</a>"
"thalidomide_disability_weight_cite": "@thalidomide-survivors-health"
"thalidomide_mortality_rate": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-thalidomide_mortality_rate\" class=\"parameter-link\" data-source-ref=\"thalidomide-scandal\" data-source-type=\"external\" data-confidence=\"high\" title=\"Mortality rate for thalidomide-affected infants (died within first year) | ✓ High confidence | 95% CI: [35%, 45%] | Dist: Lognormal | Unit: percentage | Click to view details, calculation & sources\">40% (95% CI: 35%-45%)</a>"
"thalidomide_mortality_rate_cite": "@thalidomide-scandal"
"thalidomide_survivors_per_event": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-thalidomide_survivors_per_event\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Survivors per US-scale thalidomide event | Calculated from 2 inputs | ~ Medium confidence | Formula: US_CASES × (1 - MORTALITY_RATE) | Unit: cases | Click to view details, calculation & sources\">540 cases (95% CI: 399 cases-698 cases)</a>"
"thalidomide_survivors_per_event_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-thalidomide_survivors_per_event\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Survivors per US-scale thalidomide event | Calculated from 2 inputs | ~ Medium confidence | Formula: US_CASES × (1 - MORTALITY_RATE) | Unit: cases | Click to view details, calculation & sources\">540 (95% CI: 399-698)</a>"
"thalidomide_survivors_per_event_latex": "$$\n\\begin{gathered}\nN_{thal,survive} \\\\\n= N_{thal,US,prevent} \\times (1 - Rate_{thal,mort}) \\\\\n= 900 \\times (1 - 40\\%) \\\\\n= 540\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{thal,US,prevent} \\\\\n= N_{thal,global} \\times Pct_{US,1960} \\\\\n= 15{,}000 \\times 6\\% \\\\\n= 900\n\\end{gathered}\n$$"
"thalidomide_survivor_lifespan": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-thalidomide_survivor_lifespan\" class=\"parameter-link\" data-source-ref=\"thalidomide-survivors-health\" data-source-type=\"external\" data-confidence=\"medium\" title=\"Average lifespan for thalidomide survivors | ~ Medium confidence | 95% CI: [50 years, 70 years] | Dist: Lognormal | Unit: years | Click to view details, calculation & sources\">60 years (95% CI: 50 years-70 years)</a>"
"thalidomide_survivor_lifespan_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-thalidomide_survivor_lifespan\" class=\"parameter-link\" data-source-ref=\"thalidomide-survivors-health\" data-source-type=\"external\" data-confidence=\"medium\" title=\"Average lifespan for thalidomide survivors | ~ Medium confidence | 95% CI: [50 years, 70 years] | Dist: Lognormal | Unit: years | Click to view details, calculation & sources\">60 (95% CI: 50-70)</a>"
"thalidomide_survivor_lifespan_cite": "@thalidomide-survivors-health"
"thalidomide_us_cases_prevented": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-thalidomide_us_cases_prevented\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Estimated US thalidomide cases prevented by FDA rejection | Calculated from 2 inputs | ~ Medium confidence | Formula: WORLDWIDE_CASES × US_POPULATION_SHARE | Unit: cases | Click to view details, calculation & sources\">900 cases (95% CI: 622 cases-1.25 thousand cases)</a>"
"thalidomide_us_cases_prevented_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-thalidomide_us_cases_prevented\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Estimated US thalidomide cases prevented by FDA rejection | Calculated from 2 inputs | ~ Medium confidence | Formula: WORLDWIDE_CASES × US_POPULATION_SHARE | Unit: cases | Click to view details, calculation & sources\">900 (95% CI: 622-1.25 thousand)</a>"
"thalidomide_us_cases_prevented_latex": "$$\n\\begin{gathered}\nN_{thal,US,prevent} \\\\\n= N_{thal,global} \\times Pct_{US,1960} \\\\\n= 15{,}000 \\times 6\\% \\\\\n= 900\n\\end{gathered}\n$$"
"thalidomide_us_population_share_1960": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-thalidomide_us_population_share_1960\" class=\"parameter-link\" data-source-ref=\"us-census-world-population-1960\" data-source-type=\"external\" data-confidence=\"high\" title=\"US share of world population in 1960 | ✓ High confidence | 95% CI: [5.5%, 6.5%] | Dist: Lognormal | Unit: percentage | Click to view details, calculation & sources\">6% (95% CI: 6%-6%)</a>"
"thalidomide_us_population_share_1960_cite": "@us-census-world-population-1960"
"thalidomide_yld_per_event": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-thalidomide_yld_per_event\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Years Lived with Disability per thalidomide event | Calculated from 3 inputs | ~ Medium confidence | Formula: SURVIVORS × LIFESPAN × DISABILITY_WEIGHT | Unit: years | Click to view details, calculation & sources\">13 thousand years (95% CI: 6.94 thousand years-22.6 thousand years)</a>"
"thalidomide_yld_per_event_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-thalidomide_yld_per_event\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Years Lived with Disability per thalidomide event | Calculated from 3 inputs | ~ Medium confidence | Formula: SURVIVORS × LIFESPAN × DISABILITY_WEIGHT | Unit: years | Click to view details, calculation & sources\">13 thousand (95% CI: 6.94 thousand-22.6 thousand)</a>"
"thalidomide_yld_per_event_latex": "$$\n\\begin{gathered}\nYLD_{thal} \\\\\n= DW_{thal} \\times N_{thal,survive} \\times LE_{thal} \\\\\n= 0.4 \\times 540 \\times 60 \\\\\n= 13{,}000\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{thal,survive} \\\\\n= N_{thal,US,prevent} \\times (1 - Rate_{thal,mort}) \\\\\n= 900 \\times (1 - 40\\%) \\\\\n= 540\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{thal,US,prevent} \\\\\n= N_{thal,global} \\times Pct_{US,1960} \\\\\n= 15{,}000 \\times 6\\% \\\\\n= 900\n\\end{gathered}\n$$"
"thalidomide_yll_per_event": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-thalidomide_yll_per_event\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Years of Life Lost per thalidomide event (infant deaths) | Calculated from 1 input | ~ Medium confidence | Formula: DEATHS × 80 years | Unit: years | Click to view details, calculation & sources\">28.8 thousand years (95% CI: 17.9 thousand years-44.5 thousand years)</a>"
"thalidomide_yll_per_event_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-thalidomide_yll_per_event\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Years of Life Lost per thalidomide event (infant deaths) | Calculated from 1 input | ~ Medium confidence | Formula: DEATHS × 80 years | Unit: years | Click to view details, calculation & sources\">28.8 thousand (95% CI: 17.9 thousand-44.5 thousand)</a>"
"thalidomide_yll_per_event_latex": "$$\n\\begin{gathered}\nYLL_{thal} \\\\\n= Deaths_{thal} \\times 80 \\\\\n= 360 \\times 80 \\\\\n= 28{,}800\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDeaths_{thal} \\\\\n= Rate_{thal,mort} \\times N_{thal,US,prevent} \\\\\n= 40\\% \\times 900 \\\\\n= 360\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{thal,US,prevent} \\\\\n= N_{thal,global} \\times Pct_{US,1960} \\\\\n= 15{,}000 \\times 6\\% \\\\\n= 900\n\\end{gathered}\n$$"
"total_research_funding_with_treaty": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-total_research_funding_with_treaty\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Total global research funding (baseline + 1% treaty funding) | Calculated from 2 inputs | ✓ High confidence | Formula: GLOBAL_MED_RESEARCH_SPENDING + TREATY_ANNUAL_FUNDING | Unit: USD | Click to view details, calculation & sources\">$94.7B (95% CI: $83.8B-$107B)</a>"
"total_research_funding_with_treaty_latex": "$$\n\\begin{gathered}\nFunding_{RD,total} \\\\\n= Spending_{RD} + Funding_{treaty} \\\\\n= \\$67.5B + \\$27.2B \\\\\n= \\$94.7B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nFunding_{treaty} \\\\\n= Spending_{mil} \\times Reduce_{treaty} \\\\\n= \\$2.72T \\times 1\\% \\\\\n= \\$27.2B\n\\end{gathered}\n$$"
"total_testable_therapeutic_combinations": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-total_testable_therapeutic_combinations\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Total testable therapeutic combinations (known safe compounds + emerging modalities) | Calculated from 2 inputs | ✓ High confidence | Formula: KNOWN_SAFE + EMERGING_MODALITIES | Unit: combinations | Click to view details, calculation & sources\">51.5 million combinations</a>"
"total_testable_therapeutic_combinations_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-total_testable_therapeutic_combinations\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Total testable therapeutic combinations (known safe compounds + emerging modalities) | Calculated from 2 inputs | ✓ High confidence | Formula: KNOWN_SAFE + EMERGING_MODALITIES | Unit: combinations | Click to view details, calculation & sources\">51.5 million</a>"
"total_testable_therapeutic_combinations_latex": "$$\n\\begin{gathered}\nN_{testable} \\\\\n= N_{combos} + N_{emerging} \\\\\n= 9.5M + 42M \\\\\n= 51.5M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{combos} \\\\\n= N_{safe} \\times N_{diseases,trial} \\\\\n= 9{,}500 \\times 1{,}000 \\\\\n= 9.5M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{emerging} \\\\\n= Combos_{gene} + Combos_{mRNA} + Combos_{epi} + Combos_{cell} \\\\\n= 20M + 20M + 1.5M + 500{,}000 \\\\\n= 42M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCombos_{gene} \\\\\n= N_{genes} \\times N_{diseases,trial} \\\\\n= 20{,}000 \\times 1{,}000 \\\\\n= 20M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCombos_{mRNA} \\\\\n= N_{genes} \\times N_{diseases,trial} \\\\\n= 20{,}000 \\times 1{,}000 \\\\\n= 20M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCombos_{epi} \\\\\n= N_{epi} \\times N_{diseases,trial} \\\\\n= 1{,}500 \\times 1{,}000 \\\\\n= 1.5M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCombos_{cell} \\\\\n= N_{cell} \\times N_{diseases,trial} \\\\\n= 500 \\times 1{,}000 \\\\\n= 500{,}000\n\\end{gathered}\n$$"
"traditional_phase3_cost_per_patient": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-traditional_phase3_cost_per_patient\" class=\"parameter-link\" data-source-ref=\"trial-costs-fda-study\" data-source-type=\"external\" data-confidence=\"high\" title=\"Phase 3 cost per patient (median from FDA study) | ✓ High confidence | 95% CI: [$20K, $120K] | Dist: Lognormal | Unit: USD/patient | Click to view details, calculation & sources\">$41K (95% CI: $20K-$120K)</a>"
"traditional_phase3_cost_per_patient_cite": "@trial-costs-fda-study"
"treatment_disability_reduction": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treatment_disability_reduction\" class=\"parameter-link\" data-source-ref=\"gbd-disability-weights\" data-source-type=\"external\" data-peer-reviewed=\"true\" data-confidence=\"medium\" title=\"Average disability weight reduction from pharmaceutical treatment. Untreated chronic disease averages 0.35 disability weight, treated disease averages 0.10, difference is 0.25. | ~ Medium confidence | \U0001F4CA Peer-reviewed | 95% CI: [0.15 weight, 0.35 weight] | Dist: Normal | Unit: weight | Click to view details, calculation & sources\">0.25 weight (95% CI: 0.15 weight-0.35 weight)</a>"
"treatment_disability_reduction_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treatment_disability_reduction\" class=\"parameter-link\" data-source-ref=\"gbd-disability-weights\" data-source-type=\"external\" data-peer-reviewed=\"true\" data-confidence=\"medium\" title=\"Average disability weight reduction from pharmaceutical treatment. Untreated chronic disease averages 0.35 disability weight, treated disease averages 0.10, difference is 0.25. | ~ Medium confidence | \U0001F4CA Peer-reviewed | 95% CI: [0.15 weight, 0.35 weight] | Dist: Normal | Unit: weight | Click to view details, calculation & sources\">0.25 (95% CI: 0.15-0.35)</a>"
"treatment_disability_reduction_cite": "@gbd-disability-weights"
"treaty_annual_funding": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_annual_funding\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Annual funding from 1% of global military spending redirected to DIH | Calculated from 2 inputs | ✓ High confidence | Formula: MILITARY_SPENDING × 1% | Unit: USD/year | Click to view details, calculation & sources\">$27.2B</a>"
"treaty_annual_funding_latex": "$$\n\\begin{gathered}\nFunding_{treaty} \\\\\n= Spending_{mil} \\times Reduce_{treaty} \\\\\n= \\$2.72T \\times 1\\% \\\\\n= \\$27.2B\n\\end{gathered}\n$$"
"treaty_benefit_multiplier_vs_vaccines": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_benefit_multiplier_vs_vaccines\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Treaty system benefit multiplier vs childhood vaccination programs | Calculated from 2 inputs | ✓ High confidence | Formula: TREATY_CONSERVATIVE_BENEFIT ÷ CHILDHOOD_VACCINATION_BENEFIT | Unit: x | Click to view details, calculation & sources\">11.5x (95% CI: 9x-16.1x)</a>"
"treaty_benefit_multiplier_vs_vaccines_latex": "$$\n\\begin{gathered}\nk_{treaty:vax} \\\\\n= \\frac{Benefit_{peace+RD}}{Benefit_{vax,ann}} \\\\\n= \\frac{\\$172B}{\\$15B} \\\\\n= 11.5\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nBenefit_{peace+RD} \\\\\n= Benefit_{peace,soc} + Benefit_{RD,ann} \\\\\n= \\$114B + \\$58.6B \\\\\n= \\$172B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nBenefit_{peace,soc} \\\\\n= Cost_{war,total} \\times Reduce_{treaty} \\\\\n= \\$11.4T \\times 1\\% \\\\\n= \\$114B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,total} \\\\\n= Cost_{war,direct} + Cost_{war,indirect} \\\\\n= \\$7.66T + \\$3.7T \\\\\n= \\$11.4T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,direct} \\\\\n= Loss_{life,conflict} + Damage_{infra,total} \\\\\n+ Disruption_{trade} + Spending_{mil} \\\\\n= \\$2.45T + \\$1.88T + \\$616B + \\$2.72T \\\\\n= \\$7.66T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{life,conflict} \\\\\n= Cost_{combat,human} + Cost_{state,human} \\\\\n+ Cost_{terror,human} \\\\\n= \\$2.34T + \\$27B + \\$83B \\\\\n= \\$2.45T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{combat,human} \\\\\n= Deaths_{combat} \\times VSL \\\\\n= 234{,}000 \\times \\$10M \\\\\n= \\$2.34T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{state,human} \\\\\n= Deaths_{state} \\times VSL \\\\\n= 2{,}700 \\times \\$10M \\\\\n= \\$27B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{terror,human} \\\\\n= Deaths_{terror} \\times VSL \\\\\n= 8{,}300 \\times \\$10M \\\\\n= \\$83B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDamage_{infra,total} \\\\\n= Damage_{comms} + Damage_{edu} + Damage_{energy} \\\\\n+ Damage_{health} + Damage_{transport} + Damage_{water} \\\\\n= \\$298B + \\$234B + \\$422B + \\$166B + \\$487B + \\$268B \\\\\n= \\$1.88T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDisruption_{trade} \\\\\n= Disruption_{currency} + Disruption_{energy} \\\\\n+ Disruption_{shipping} + Disruption_{supply} \\\\\n= \\$57.4B + \\$125B + \\$247B + \\$187B \\\\\n= \\$616B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,indirect} \\\\\n= Damage_{env} + Loss_{growth,mil} + Loss_{capital,conflict} \\\\\n+ Cost_{psych} + Cost_{refugee} + Cost_{vet} \\\\\n= \\$100B + \\$2.72T + \\$300B + \\$232B + \\$150B + \\$200B \\\\\n= \\$3.7T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nBenefit_{RD,ann} \\\\\n= Spending_{trials} \\times Reduce_{pct} \\\\\n= \\$60B \\times 97.7\\% \\\\\n= \\$58.6B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nReduce_{pct} \\\\\n= 1 - \\frac{Cost_{pragmatic,pt}}{Cost_{P3,pt}} \\\\\n= 1 - \\frac{\\$929}{\\$41K} \\\\\n= 97.7\\%\n\\end{gathered}\n$$"
"treaty_campaign_annual_cost_amortized": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_campaign_annual_cost_amortized\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Amortized annual campaign cost (total cost ÷ campaign duration) | Calculated from 2 inputs | ✓ High confidence | Formula: TOTAL_COST ÷ DURATION | Unit: USD/year | Click to view details, calculation & sources\">$250M (95% CI: $158M-$379M)</a>"
"treaty_campaign_annual_cost_amortized_latex": "$$\n\\begin{gathered}\nCost_{camp,amort} \\\\\n= \\frac{Cost_{campaign}}{T_{campaign}} \\\\\n= \\frac{\\$1B}{4} \\\\\n= \\$250M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{campaign} \\\\\n= Budget_{viral,base} + Budget_{lobby,treaty} \\\\\n+ Budget_{reserve} \\\\\n= \\$250M + \\$650M + \\$100M \\\\\n= \\$1B\n\\end{gathered}\n$$"
"treaty_campaign_budget_lobbying": "<span class=\"parameter-definition\" title=\"Political lobbying campaign: direct lobbying (US/EU/G20), Super PACs, opposition research, staff, legal/compliance. Budget exceeds combined pharma ($300M/year) and military-industrial complex ($150M/year) lobbying to ensure competitive positioning. Referendum relies on grassroots mobilization and earned media, while lobbying requires matching or exceeding opposition spending for political viability. | Unit: USD | Core definition\">$650M</span>"
"treaty_campaign_budget_reserve": "<span class=\"parameter-definition\" title=\"Reserve fund / contingency buffer (10% of total campaign cost). Using industry standard 10% for complex campaigns with potential for unforeseen legal challenges, opposition response, or regulatory delays. Conservative lower bound of $20M (2%) reflects transparent budget allocation and predictable referendum/lobbying costs. | Unit: USD | Core definition\">$100M</span>"
"treaty_campaign_duration_years": "<span class=\"parameter-definition\" title=\"Treaty campaign duration (3-5 year range, using midpoint) | Unit: years | Core definition\">4 years (95% CI: 3 years-5 years)</span>"
"treaty_campaign_duration_years_nounit": "<span class=\"parameter-definition\" title=\"Treaty campaign duration (3-5 year range, using midpoint) | Unit: years | Core definition\">4 (95% CI: 3-5)</span>"
"treaty_campaign_total_cost": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_campaign_total_cost\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Total treaty campaign cost (100% VICTORY Incentive Alignment Bonds) | Calculated from 3 inputs | ✓ High confidence | Formula: REFERENDUM + LOBBYING + RESERVE | Unit: USD | Click to view details, calculation & sources\">$1B</a>"
"treaty_campaign_total_cost_latex": "$$\n\\begin{gathered}\nCost_{campaign} \\\\\n= Budget_{viral,base} + Budget_{lobby,treaty} \\\\\n+ Budget_{reserve} \\\\\n= \\$250M + \\$650M + \\$100M \\\\\n= \\$1B\n\\end{gathered}\n$$"
"treaty_campaign_viral_referendum_base_case": "<span class=\"parameter-definition\" title=\"Viral referendum budget for 280M verified votes (base: $250M realistic with $0.50/vote avg, range: $150M optimistic $0.20/vote to $410M worst-case $1.05/vote). Components: platform ($35M), verification infrastructure (280M × friction × $0.18-0.20), tiered referral payments (varies by virality and marginal cost curve per diffusion theory), marketing seed ($5-15M). Based on PayPal referral economics ($18-36 inflation-adjusted) and biometric verification pricing ($0.15-0.25 at 300M+ scale). | Unit: USD | Core definition\">$250M</span>"
"treaty_campaign_voting_bloc_target": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_campaign_voting_bloc_target\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Target voting bloc size for campaign (3.5% of global population - critical mass for social change). Wide CI reflects uncertainty in applying Chenoweth's national threshold to global treaty adoption. | Calculated from 2 inputs | ✓ High confidence | Formula: GLOBAL_POPULATION × 3.5% | Unit: of people | Click to view details, calculation & sources\">280 million of people (95% CI: 84.2 million of people-639 million of people)</a>"
"treaty_campaign_voting_bloc_target_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_campaign_voting_bloc_target\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Target voting bloc size for campaign (3.5% of global population - critical mass for social change). Wide CI reflects uncertainty in applying Chenoweth's national threshold to global treaty adoption. | Calculated from 2 inputs | ✓ High confidence | Formula: GLOBAL_POPULATION × 3.5% | Unit: of people | Click to view details, calculation & sources\">280 million (95% CI: 84.2 million-639 million)</a>"
"treaty_campaign_voting_bloc_target_latex": "$$\n\\begin{gathered}\nN_{voters,target} \\\\\n= Pop_{global} \\times Threshold_{activism} \\\\\n= 8B \\times 3.5\\% \\\\\n= 280M\n\\end{gathered}\n$$"
"treaty_cost_per_daly_trial_capacity_plus_efficacy_lag": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_cost_per_daly_trial_capacity_plus_efficacy_lag\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Cost per DALY averted from elimination of efficacy lag plus earlier treatment discovery from increased trial throughput. Only counts campaign cost; ignores economic benefits from funding and R&D savings. | Calculated from 2 inputs | ✓ High confidence | Formula: CAMPAIGN_COST ÷ DALYS_TIMELINE_SHIFT | Unit: USD/DALY | Click to view details, calculation & sources\">$0.00177 (95% CI: $0.000715-$0.00412)</a>"
"treaty_cost_per_daly_trial_capacity_plus_efficacy_lag_latex": "$$\n\\begin{gathered}\nCost_{treaty,DALY} \\\\\n= \\frac{Cost_{campaign}}{DALYs_{max}} \\\\\n= \\frac{\\$1B}{565B} \\\\\n= \\$0.00177\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{campaign} \\\\\n= Budget_{viral,base} + Budget_{lobby,treaty} \\\\\n+ Budget_{reserve} \\\\\n= \\$250M + \\$650M + \\$100M \\\\\n= \\$1B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDALYs_{max} \\\\\n= DALYs_{global,ann} \\times Pct_{avoid,DALY} \\times T_{accel,max} \\\\\n= 2.88B \\times 92.6\\% \\times 212 \\\\\n= 565B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nT_{accel,max} = T_{accel} + T_{lag} = 204 + 8.2 = 212\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{accel} \\\\\n= T_{first,SQ} \\times \\left(1 - \\frac{1}{k_{capacity}}\\right) \\\\\n= 222 \\times \\left(1 - \\frac{1}{12.3}\\right) \\\\\n= 204\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{first,SQ} \\\\\n= T_{queue,SQ} \\times 0.5 \\\\\n= 443 \\times 0.5 \\\\\n= 222\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{queue,SQ} \\\\\n= \\frac{N_{untreated}}{Treatments_{new,ann}} \\\\\n= \\frac{6{,}650}{15} \\\\\n= 443\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$"
"treaty_cumulative_20yr_with_ratchet": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_cumulative_20yr_with_ratchet\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Cumulative treaty funding over 20 years with IAB ratchet expansion following roadmap timeline. Expansion driven by bondholder lobbying incentives (10% of treaty inflows). | Calculated from 1 input | ✓ High confidence | Formula: GLOBAL_MILITARY × (0.01×3 + 0.02×4 + 0.05×5 + 0.10×8) | Unit: USD | Click to view details, calculation & sources\">$3.16T</a>"
"treaty_cumulative_20yr_with_ratchet_latex": "$$\n\\begin{gathered}\nFund_{20yr,ratchet} \\\\\n= Spending_{mil} \\times 1.16 \\\\\n= \\$2.72T \\times 1.16 \\\\\n= \\$3.16T\n\\end{gathered}\n$$"
"treaty_cybercrime_recovery_gdp_growth_bonus_year_15": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_cybercrime_recovery_gdp_growth_bonus_year_15\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Annual GDP growth bonus by year 15 from reducing cybercrime drag as the treaty weakens the destructive economy feedback loop. | Calculated from 4 inputs | ✓ High confidence | Formula: (GLOBAL_CYBERCRIME_COST_ANNUAL_2025 ÷ GLOBAL_GDP_2025) × TREATY_EFFECTIVE_REALLOCATION_SHARE_YEAR_15 × PEACE_DIVIDEND_CONFLICT_ELASTICITY | Unit: rate | Click to view details, calculation & sources\">0.402%</a>"
"treaty_cybercrime_recovery_gdp_growth_bonus_year_15_latex": "$$\n\\begin{gathered}\ng_{cyber,treaty,15} \\\\\n= \\left(\\frac{Cost_{cyber}}{GDP_{global}}\\right) \\times \\bar{s}_{treaty,15} \\times \\varepsilon_{conflict}\n\\end{gathered}\n$$"
"treaty_cybercrime_recovery_gdp_growth_bonus_year_20": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_cybercrime_recovery_gdp_growth_bonus_year_20\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Annual GDP growth bonus by year 20 from reducing cybercrime drag as the treaty weakens the destructive economy feedback loop. | Calculated from 4 inputs | ✓ High confidence | Formula: (GLOBAL_CYBERCRIME_COST_ANNUAL_2025 ÷ GLOBAL_GDP_2025) × TREATY_EFFECTIVE_REALLOCATION_SHARE_YEAR_20 × PEACE_DIVIDEND_CONFLICT_ELASTICITY | Unit: rate | Click to view details, calculation & sources\">0.53%</a>"
"treaty_cybercrime_recovery_gdp_growth_bonus_year_20_latex": "$$\n\\begin{gathered}\ng_{cyber,treaty,20} \\\\\n= \\left(\\frac{Cost_{cyber}}{GDP_{global}}\\right) \\times \\bar{s}_{treaty,20} \\times \\varepsilon_{conflict}\n\\end{gathered}\n$$"
"treaty_disease_cure_fraction_15yr": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_disease_cure_fraction_15yr\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Treaty disease-cure fraction over 15 years under the optimistic treaty take-hold path. The initial 1% treaty expands to 2%, then 5%, then 10%, with trial-throughput scaling linearly with treaty funding until it hits the physical participant ceiling. Cumulative throughput is capped by the physical participant ceiling. | Calculated from 4 inputs | ✓ High confidence | Formula: min(1.0, NEW_DISEASE_FIRST_TREATMENTS_PER_YEAR × (3×min(DFDA_TRIAL_CAPACITY_MULTIPLIER×1, DFDA_MAX_TRIAL_CAPACITY_MULTIPLIER_PHYSICAL) + 4×min(DFDA_TRIAL_CAPACITY_MULTIPLIER×2, DFDA_MAX_TRIAL_CAPACITY_MULTIPLIER_PHYSICAL) + 5×min(DFDA_TRIAL_CAPACITY_MULTIPLIER×5, DFDA_MAX_TRIAL_CAPACITY_MULTIPLIER_PHYSICAL) + 3×min(DFDA_TRIAL_CAPACITY_MULTIPLIER×10, DFDA_MAX_TRIAL_CAPACITY_MULTIPLIER_PHYSICAL)) ÷ DISEASES_WITHOUT_EFFECTIVE_TREATMENT) | Unit: rate | Click to view details, calculation & sources\">100% (95% CI: 85.6%-100%)</a>"
"treaty_disease_cure_fraction_15yr_latex": "$$\n\\begin{gathered}\nf_{cure,15,treaty} \\\\\n= \\min\\left(1.0, Treatments_{new,ann} \\times (3 \\times min(k_{capacity} \\times 1, k_{capacity,max}) \\\\\n+ 4 \\times min(k_{capacity} \\times 2, k_{capacity,max}) \\\\\n+ 5 \\times min(k_{capacity} \\times 5, k_{capacity,max}) \\\\\n+ 3 \\times min(k_{capacity} \\times 10, k_{capacity,max})) / N_{untreated}\\right)\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity,max} \\\\\n= \\frac{N_{willing}}{Slots_{curr}} \\\\\n= \\frac{1.08B}{1.9M} \\\\\n= 566\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{willing} \\\\\n= N_{patients} \\times Pct_{willing} \\\\\n= 2.4B \\times 44.8\\% \\\\\n= 1.08B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$"
"treaty_disease_cure_fraction_20yr": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_disease_cure_fraction_20yr\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Treaty disease-cure fraction over 20 years under the optimistic treaty take-hold path. The initial 1% treaty expands to 2%, then 5%, then 10%, with trial-throughput scaling linearly with treaty funding until it hits the physical participant ceiling. Cumulative throughput is capped by the physical participant ceiling. | Calculated from 4 inputs | ✓ High confidence | Formula: min(1.0, NEW_DISEASE_FIRST_TREATMENTS_PER_YEAR × (3×min(DFDA_TRIAL_CAPACITY_MULTIPLIER×1, DFDA_MAX_TRIAL_CAPACITY_MULTIPLIER_PHYSICAL) + 4×min(DFDA_TRIAL_CAPACITY_MULTIPLIER×2, DFDA_MAX_TRIAL_CAPACITY_MULTIPLIER_PHYSICAL) + 5×min(DFDA_TRIAL_CAPACITY_MULTIPLIER×5, DFDA_MAX_TRIAL_CAPACITY_MULTIPLIER_PHYSICAL) + 8×min(DFDA_TRIAL_CAPACITY_MULTIPLIER×10, DFDA_MAX_TRIAL_CAPACITY_MULTIPLIER_PHYSICAL)) ÷ DISEASES_WITHOUT_EFFECTIVE_TREATMENT) | Unit: rate | Click to view details, calculation & sources\">100%</a>"
"treaty_disease_cure_fraction_20yr_latex": "$$\n\\begin{gathered}\nf_{cure,20,treaty} \\\\\n= \\min\\left(1.0, Treatments_{new,ann} \\times (3 \\times min(k_{capacity} \\times 1, k_{capacity,max}) \\\\\n+ 4 \\times min(k_{capacity} \\times 2, k_{capacity,max}) \\\\\n+ 5 \\times min(k_{capacity} \\times 5, k_{capacity,max}) \\\\\n+ 8 \\times min(k_{capacity} \\times 10, k_{capacity,max})) / N_{untreated}\\right)\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity,max} \\\\\n= \\frac{N_{willing}}{Slots_{curr}} \\\\\n= \\frac{1.08B}{1.9M} \\\\\n= 566\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{willing} \\\\\n= N_{patients} \\times Pct_{willing} \\\\\n= 2.4B \\times 44.8\\% \\\\\n= 1.08B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$"
"treaty_effective_reallocation_share_year_15": "<span class=\"parameter-definition\" title=\"Average military-to-medicine reallocation share over 15 years under the optimistic treaty take-hold path (1% for 3 years, 2% for 4 years, 5% for 5 years, 10% for 3 years). | Unit: rate | Core definition\">4.4%</span>"
"treaty_effective_reallocation_share_year_20": "<span class=\"parameter-definition\" title=\"Average military-to-medicine reallocation share over 20 years under the optimistic treaty take-hold path (1% for 3 years, 2% for 4 years, 5% for 5 years, 10% for 8 years). | Unit: rate | Core definition\">5.8%</span>"
"treaty_expected_cost_per_daly": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_expected_cost_per_daly\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Expected cost per DALY accounting for political success probability uncertainty. Monte Carlo samples from beta(0.1%, 10%) distribution. At the conservative 1% estimate, this is still more cost-effective than bed nets ($89.0/DALY). | Calculated from 2 inputs | ? Low confidence | Formula: CONDITIONAL_COST_PER_DALY ÷ POLITICAL_SUCCESS_PROBABILITY | Unit: USD/DALY | Click to view details, calculation & sources\">$0.177 (95% CI: $0.029-$3.2)</a>"
"treaty_expected_cost_per_daly_latex": "$$\n\\begin{gathered}\nE[Cost_{DALY}] \\\\\n= \\frac{Cost_{treaty,DALY}}{P_{success}} \\\\\n= \\frac{\\$0.00177}{1\\%} \\\\\n= \\$0.177\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{treaty,DALY} \\\\\n= \\frac{Cost_{campaign}}{DALYs_{max}} \\\\\n= \\frac{\\$1B}{565B} \\\\\n= \\$0.00177\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{campaign} \\\\\n= Budget_{viral,base} + Budget_{lobby,treaty} \\\\\n+ Budget_{reserve} \\\\\n= \\$250M + \\$650M + \\$100M \\\\\n= \\$1B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDALYs_{max} \\\\\n= DALYs_{global,ann} \\times Pct_{avoid,DALY} \\times T_{accel,max} \\\\\n= 2.88B \\times 92.6\\% \\times 212 \\\\\n= 565B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nT_{accel,max} = T_{accel} + T_{lag} = 204 + 8.2 = 212\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{accel} \\\\\n= T_{first,SQ} \\times \\left(1 - \\frac{1}{k_{capacity}}\\right) \\\\\n= 222 \\times \\left(1 - \\frac{1}{12.3}\\right) \\\\\n= 204\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{first,SQ} \\\\\n= T_{queue,SQ} \\times 0.5 \\\\\n= 443 \\times 0.5 \\\\\n= 222\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{queue,SQ} \\\\\n= \\frac{N_{untreated}}{Treatments_{new,ann}} \\\\\n= \\frac{6{,}650}{15} \\\\\n= 443\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$"
"treaty_expected_roi_trial_capacity_plus_efficacy_lag": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_expected_roi_trial_capacity_plus_efficacy_lag\" class=\"parameter-link\" data-source-ref=\"calculated\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Expected ROI for 1% treaty accounting for political success probability uncertainty. Monte Carlo samples POLITICAL_SUCCESS_PROBABILITY from beta(0.1%, 10%) distribution to generate full expected value distribution. Central value uses 1% probability. | Calculated from 2 inputs | ? Low confidence | Formula: TREATY_ROI_TRIAL_CAPACITY_PLUS_EFFICACY_LAG × POLITICAL_SUCCESS_PROBABILITY | Unit: ratio | Click to view details, calculation & sources\">848k (95% CI: 58.0k-4.76M)</a>"
"treaty_expected_roi_trial_capacity_plus_efficacy_lag_latex": "$$\n\\begin{gathered}\nE[ROI_{max}] \\\\\n= ROI_{max} \\times P_{success} \\\\\n= 84.8M \\times 1\\% \\\\\n= 848{,}000\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nROI_{max} \\\\\n= \\frac{Value_{max}}{Cost_{campaign}} \\\\\n= \\frac{\\$84800T}{\\$1B} \\\\\n= 84.8M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nValue_{max} \\\\\n= DALYs_{max} \\times Value_{QALY} \\\\\n= 565B \\times \\$150K \\\\\n= \\$84800T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDALYs_{max} \\\\\n= DALYs_{global,ann} \\times Pct_{avoid,DALY} \\times T_{accel,max} \\\\\n= 2.88B \\times 92.6\\% \\times 212 \\\\\n= 565B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nT_{accel,max} = T_{accel} + T_{lag} = 204 + 8.2 = 212\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{accel} \\\\\n= T_{first,SQ} \\times \\left(1 - \\frac{1}{k_{capacity}}\\right) \\\\\n= 222 \\times \\left(1 - \\frac{1}{12.3}\\right) \\\\\n= 204\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{first,SQ} \\\\\n= T_{queue,SQ} \\times 0.5 \\\\\n= 443 \\times 0.5 \\\\\n= 222\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{queue,SQ} \\\\\n= \\frac{N_{untreated}}{Treatments_{new,ann}} \\\\\n= \\frac{6{,}650}{15} \\\\\n= 443\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{campaign} \\\\\n= Budget_{viral,base} + Budget_{lobby,treaty} \\\\\n+ Budget_{reserve} \\\\\n= \\$250M + \\$650M + \\$100M \\\\\n= \\$1B\n\\end{gathered}\n$$"
"treaty_expected_vs_bed_nets_multiplier": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_expected_vs_bed_nets_multiplier\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Expected value multiplier vs bed nets (accounts for political uncertainty at 1% success rate) | Calculated from 2 inputs | ? Low confidence | Formula: BED_NETS_COST_PER_DALY ÷ TREATY_EXPECTED_COST_PER_DALY | Unit: x | Click to view details, calculation & sources\">503x (95% CI: 30x-3.0kx)</a>"
"treaty_expected_vs_bed_nets_multiplier_latex": "$$\n\\begin{gathered}\nE[k_{nets}] \\\\\n= \\frac{Cost_{nets}}{E[Cost_{DALY}]} \\\\\n= \\frac{\\$89}{\\$0.177} \\\\\n= 503\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nE[Cost_{DALY}] \\\\\n= \\frac{Cost_{treaty,DALY}}{P_{success}} \\\\\n= \\frac{\\$0.00177}{1\\%} \\\\\n= \\$0.177\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{treaty,DALY} \\\\\n= \\frac{Cost_{campaign}}{DALYs_{max}} \\\\\n= \\frac{\\$1B}{565B} \\\\\n= \\$0.00177\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{campaign} \\\\\n= Budget_{viral,base} + Budget_{lobby,treaty} \\\\\n+ Budget_{reserve} \\\\\n= \\$250M + \\$650M + \\$100M \\\\\n= \\$1B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDALYs_{max} \\\\\n= DALYs_{global,ann} \\times Pct_{avoid,DALY} \\times T_{accel,max} \\\\\n= 2.88B \\times 92.6\\% \\times 212 \\\\\n= 565B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nT_{accel,max} = T_{accel} + T_{lag} = 204 + 8.2 = 212\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{accel} \\\\\n= T_{first,SQ} \\times \\left(1 - \\frac{1}{k_{capacity}}\\right) \\\\\n= 222 \\times \\left(1 - \\frac{1}{12.3}\\right) \\\\\n= 204\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{first,SQ} \\\\\n= T_{queue,SQ} \\times 0.5 \\\\\n= 443 \\times 0.5 \\\\\n= 222\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{queue,SQ} \\\\\n= \\frac{N_{untreated}}{Treatments_{new,ann}} \\\\\n= \\frac{6{,}650}{15} \\\\\n= 443\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$"
"treaty_hale_gain_year_15": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_hale_gain_year_15\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"HALE improvement at year 15 under Treaty Trajectory. It includes both closing the current HALE gap from disease/disability and a conservative partial realization of longer-run longevity gains. | Calculated from 4 inputs | ✓ High confidence | Formula: TREATY_DISEASE_CURE_FRACTION_15YR × GLOBAL_HALE_GAP + TREATY_LONGEVITY_HALE_GAIN_YEAR_15 | Unit: years | Click to view details, calculation & sources\">21.7 years (95% CI: 15.6 years-30 years)</a>"
"treaty_hale_gain_year_15_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_hale_gain_year_15\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"HALE improvement at year 15 under Treaty Trajectory. It includes both closing the current HALE gap from disease/disability and a conservative partial realization of longer-run longevity gains. | Calculated from 4 inputs | ✓ High confidence | Formula: TREATY_DISEASE_CURE_FRACTION_15YR × GLOBAL_HALE_GAP + TREATY_LONGEVITY_HALE_GAIN_YEAR_15 | Unit: years | Click to view details, calculation & sources\">21.7 (95% CI: 15.6-30)</a>"
"treaty_hale_gain_year_15_latex": "$$\n\\begin{gathered}\n\\Delta HALE_{treaty,15} \\\\\n= f_{cure,15,treaty} \\times \\Delta_{HALE} \\\\\n+ \\Delta HALE_{treaty,longevity,15}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nf_{cure,15,treaty} \\\\\n= \\min\\left(1.0, Treatments_{new,ann} \\times (3 \\times min(k_{capacity} \\times 1, k_{capacity,max}) \\\\\n+ 4 \\times min(k_{capacity} \\times 2, k_{capacity,max}) \\\\\n+ 5 \\times min(k_{capacity} \\times 5, k_{capacity,max}) \\\\\n+ 3 \\times min(k_{capacity} \\times 10, k_{capacity,max})) / N_{untreated}\\right)\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity,max} \\\\\n= \\frac{N_{willing}}{Slots_{curr}} \\\\\n= \\frac{1.08B}{1.9M} \\\\\n= 566\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{willing} \\\\\n= N_{patients} \\times Pct_{willing} \\\\\n= 2.4B \\times 44.8\\% \\\\\n= 1.08B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\Delta HALE_{treaty,longevity,15} \\\\\n= T_{extend} \\times \\rho_{HALE,15} \\times f_{cure,15,treaty} \\\\\n= 20 \\times 30\\% \\times 100\\% \\\\\n= 6\n\\end{gathered}\n$$"
"treaty_hale_value_per_capita": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_hale_value_per_capita\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Economic value of Treaty Trajectory HALE gains at year 15 using the standard QALY value. | Calculated from 2 inputs | ✓ High confidence | Formula: TREATY_HALE_GAIN_YEAR_15 × STANDARD_ECONOMIC_QALY_VALUE_USD | Unit: USD/person | Click to view details, calculation & sources\">$3.26M (95% CI: $1.56M-$5.91M)</a>"
"treaty_hale_value_per_capita_latex": "$$\n\\begin{gathered}\nValue_{HALE,treaty} \\\\\n= \\Delta HALE_{treaty,15} \\times Value_{QALY} \\\\\n= 21.7 \\times \\$150K \\\\\n= \\$3.26M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\Delta HALE_{treaty,15} \\\\\n= f_{cure,15,treaty} \\times \\Delta_{HALE} \\\\\n+ \\Delta HALE_{treaty,longevity,15}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nf_{cure,15,treaty} \\\\\n= \\min\\left(1.0, Treatments_{new,ann} \\times (3 \\times min(k_{capacity} \\times 1, k_{capacity,max}) \\\\\n+ 4 \\times min(k_{capacity} \\times 2, k_{capacity,max}) \\\\\n+ 5 \\times min(k_{capacity} \\times 5, k_{capacity,max}) \\\\\n+ 3 \\times min(k_{capacity} \\times 10, k_{capacity,max})) / N_{untreated}\\right)\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity,max} \\\\\n= \\frac{N_{willing}}{Slots_{curr}} \\\\\n= \\frac{1.08B}{1.9M} \\\\\n= 566\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{willing} \\\\\n= N_{patients} \\times Pct_{willing} \\\\\n= 2.4B \\times 44.8\\% \\\\\n= 1.08B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\Delta HALE_{treaty,longevity,15} \\\\\n= T_{extend} \\times \\rho_{HALE,15} \\times f_{cure,15,treaty} \\\\\n= 20 \\times 30\\% \\times 100\\% \\\\\n= 6\n\\end{gathered}\n$$"
"treaty_health_recovery_gdp_growth_bonus_year_15": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_health_recovery_gdp_growth_bonus_year_15\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Annualized GDP growth bonus by year 15 from lower disease burden plus eliminating existing-drug efficacy lag under the treaty path. | Calculated from 4 inputs | ✓ High confidence | Formula: ((1 + TREATY_DISEASE_CURE_FRACTION_15YR × DISEASE_BURDEN_GDP_DRAG_PCT + (EXISTING_DRUGS_EFFICACY_LAG_ECONOMIC_LOSS ÷ GLOBAL_GDP_2025))^(1/15)) - 1 | Unit: rate | Click to view details, calculation & sources\">8.46% (95% CI: 3.72%-13.6%)</a>"
"treaty_health_recovery_gdp_growth_bonus_year_15_latex": "$$\n\\begin{gathered}\ng_{health,treaty,15} \\\\\n= ((1 + f_{cure,15,treaty} \\times d_{disease} \\\\\n+ \\left(\\frac{Loss_{lag}}{GDP_{global}}\\right))^{\\frac{1}{15}}) - 1\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nf_{cure,15,treaty} \\\\\n= \\min\\left(1.0, Treatments_{new,ann} \\times (3 \\times min(k_{capacity} \\times 1, k_{capacity,max}) \\\\\n+ 4 \\times min(k_{capacity} \\times 2, k_{capacity,max}) \\\\\n+ 5 \\times min(k_{capacity} \\times 5, k_{capacity,max}) \\\\\n+ 3 \\times min(k_{capacity} \\times 10, k_{capacity,max})) / N_{untreated}\\right)\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity,max} \\\\\n= \\frac{N_{willing}}{Slots_{curr}} \\\\\n= \\frac{1.08B}{1.9M} \\\\\n= 566\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{willing} \\\\\n= N_{patients} \\times Pct_{willing} \\\\\n= 2.4B \\times 44.8\\% \\\\\n= 1.08B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{lag} \\\\\n= Deaths_{lag,total} \\times (LE_{global} - Age_{death,delay}) \\times Value_{QALY} \\\\\n= 102M \\times (79 - 62) \\times \\$150K \\\\\n= \\$259T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDeaths_{lag,total} \\\\\n= Lives_{saved,annual} \\times T_{lag} \\\\\n= 12.4M \\times 8.2 \\\\\n= 102M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLives_{saved,annual} \\\\\n= \\frac{LY_{saved,annual}}{T_{ext}} \\\\\n= \\frac{149M}{12} \\\\\n= 12.4M\n\\end{gathered}\n$$"
"treaty_health_recovery_gdp_growth_bonus_year_20": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_health_recovery_gdp_growth_bonus_year_20\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Annualized GDP growth bonus by year 20 from lower disease burden plus eliminating existing-drug efficacy lag under the treaty path. | Calculated from 4 inputs | ✓ High confidence | Formula: ((1 + TREATY_DISEASE_CURE_FRACTION_20YR × DISEASE_BURDEN_GDP_DRAG_PCT + (EXISTING_DRUGS_EFFICACY_LAG_ECONOMIC_LOSS ÷ GLOBAL_GDP_2025))^(1/20)) - 1 | Unit: rate | Click to view details, calculation & sources\">6.28% (95% CI: 2.78%-10.1%)</a>"
"treaty_health_recovery_gdp_growth_bonus_year_20_latex": "$$\n\\begin{gathered}\ng_{health,treaty,20} \\\\\n= ((1 + f_{cure,20,treaty} \\times d_{disease} \\\\\n+ \\left(\\frac{Loss_{lag}}{GDP_{global}}\\right))^{\\frac{1}{20}}) - 1\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nf_{cure,20,treaty} \\\\\n= \\min\\left(1.0, Treatments_{new,ann} \\times (3 \\times min(k_{capacity} \\times 1, k_{capacity,max}) \\\\\n+ 4 \\times min(k_{capacity} \\times 2, k_{capacity,max}) \\\\\n+ 5 \\times min(k_{capacity} \\times 5, k_{capacity,max}) \\\\\n+ 8 \\times min(k_{capacity} \\times 10, k_{capacity,max})) / N_{untreated}\\right)\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity,max} \\\\\n= \\frac{N_{willing}}{Slots_{curr}} \\\\\n= \\frac{1.08B}{1.9M} \\\\\n= 566\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{willing} \\\\\n= N_{patients} \\times Pct_{willing} \\\\\n= 2.4B \\times 44.8\\% \\\\\n= 1.08B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{lag} \\\\\n= Deaths_{lag,total} \\times (LE_{global} - Age_{death,delay}) \\times Value_{QALY} \\\\\n= 102M \\times (79 - 62) \\times \\$150K \\\\\n= \\$259T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDeaths_{lag,total} \\\\\n= Lives_{saved,annual} \\times T_{lag} \\\\\n= 12.4M \\times 8.2 \\\\\n= 102M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLives_{saved,annual} \\\\\n= \\frac{LY_{saved,annual}}{T_{ext}} \\\\\n= \\frac{149M}{12} \\\\\n= 12.4M\n\\end{gathered}\n$$"
"treaty_lives_saved_annual_global": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_lives_saved_annual_global\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Annual lives saved from 1% reduction in conflict deaths | Calculated from 2 inputs | ✓ High confidence | Formula: TOTAL_DEATHS × REDUCTION_PCT | Unit: lives/year | Click to view details, calculation & sources\">2.45 thousand lives/year (95% CI: 1.94 thousand lives/year-3.02 thousand lives/year)</a>"
"treaty_lives_saved_annual_global_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_lives_saved_annual_global\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Annual lives saved from 1% reduction in conflict deaths | Calculated from 2 inputs | ✓ High confidence | Formula: TOTAL_DEATHS × REDUCTION_PCT | Unit: lives/year | Click to view details, calculation & sources\">2.45 thousand (95% CI: 1.94 thousand-3.02 thousand)</a>"
"treaty_lives_saved_annual_global_latex": "$$\n\\begin{gathered}\nLives_{treaty,ann} \\\\\n= Deaths_{conflict} \\times Reduce_{treaty} \\\\\n= 245{,}000 \\times 1\\% \\\\\n= 2{,}450\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDeaths_{conflict} \\\\\n= Deaths_{combat} + Deaths_{state} + Deaths_{terror} \\\\\n= 234{,}000 + 2{,}700 + 8{,}300 \\\\\n= 245{,}000\n\\end{gathered}\n$$"
"treaty_longevity_hale_gain_year_15": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_longevity_hale_gain_year_15\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Additional healthy years at year 15 from partial realization of longer-run treaty longevity gains. This removes the implicit cap at today's life expectancy while keeping year-15 realization conservative. | Calculated from 3 inputs | ✓ High confidence | Formula: LIFE_EXTENSION_YEARS × HALE_LONGEVITY_REALIZATION_SHARE_YEAR_15 × TREATY_DISEASE_CURE_FRACTION_15YR | Unit: years | Click to view details, calculation & sources\">6 years (95% CI: 0.778 years-15.6 years)</a>"
"treaty_longevity_hale_gain_year_15_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_longevity_hale_gain_year_15\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Additional healthy years at year 15 from partial realization of longer-run treaty longevity gains. This removes the implicit cap at today's life expectancy while keeping year-15 realization conservative. | Calculated from 3 inputs | ✓ High confidence | Formula: LIFE_EXTENSION_YEARS × HALE_LONGEVITY_REALIZATION_SHARE_YEAR_15 × TREATY_DISEASE_CURE_FRACTION_15YR | Unit: years | Click to view details, calculation & sources\">6 (95% CI: 0.778-15.6)</a>"
"treaty_longevity_hale_gain_year_15_latex": "$$\n\\begin{gathered}\n\\Delta HALE_{treaty,longevity,15} \\\\\n= T_{extend} \\times \\rho_{HALE,15} \\times f_{cure,15,treaty} \\\\\n= 20 \\times 30\\% \\times 100\\% \\\\\n= 6\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nf_{cure,15,treaty} \\\\\n= \\min\\left(1.0, Treatments_{new,ann} \\times (3 \\times min(k_{capacity} \\times 1, k_{capacity,max}) \\\\\n+ 4 \\times min(k_{capacity} \\times 2, k_{capacity,max}) \\\\\n+ 5 \\times min(k_{capacity} \\times 5, k_{capacity,max}) \\\\\n+ 3 \\times min(k_{capacity} \\times 10, k_{capacity,max})) / N_{untreated}\\right)\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity,max} \\\\\n= \\frac{N_{willing}}{Slots_{curr}} \\\\\n= \\frac{1.08B}{1.9M} \\\\\n= 566\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{willing} \\\\\n= N_{patients} \\times Pct_{willing} \\\\\n= 2.4B \\times 44.8\\% \\\\\n= 1.08B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$"
"treaty_peace_plus_rd_annual_benefits": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_peace_plus_rd_annual_benefits\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Basic annual benefits: peace dividend + Decentralized Framework for Drug Assessment R&D savings only (2 of 8 benefit categories, excludes regulatory delay value) | Calculated from 2 inputs | ✓ High confidence | Formula: PEACE_DIVIDEND + DFDA_RD_SAVINGS | Unit: USD/year | Click to view details, calculation & sources\">$172B (95% CI: $140B-$213B)</a>"
"treaty_peace_plus_rd_annual_benefits_latex": "$$\n\\begin{gathered}\nBenefit_{peace+RD} \\\\\n= Benefit_{peace,soc} + Benefit_{RD,ann} \\\\\n= \\$114B + \\$58.6B \\\\\n= \\$172B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nBenefit_{peace,soc} \\\\\n= Cost_{war,total} \\times Reduce_{treaty} \\\\\n= \\$11.4T \\times 1\\% \\\\\n= \\$114B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,total} \\\\\n= Cost_{war,direct} + Cost_{war,indirect} \\\\\n= \\$7.66T + \\$3.7T \\\\\n= \\$11.4T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,direct} \\\\\n= Loss_{life,conflict} + Damage_{infra,total} \\\\\n+ Disruption_{trade} + Spending_{mil} \\\\\n= \\$2.45T + \\$1.88T + \\$616B + \\$2.72T \\\\\n= \\$7.66T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{life,conflict} \\\\\n= Cost_{combat,human} + Cost_{state,human} \\\\\n+ Cost_{terror,human} \\\\\n= \\$2.34T + \\$27B + \\$83B \\\\\n= \\$2.45T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{combat,human} \\\\\n= Deaths_{combat} \\times VSL \\\\\n= 234{,}000 \\times \\$10M \\\\\n= \\$2.34T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{state,human} \\\\\n= Deaths_{state} \\times VSL \\\\\n= 2{,}700 \\times \\$10M \\\\\n= \\$27B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{terror,human} \\\\\n= Deaths_{terror} \\times VSL \\\\\n= 8{,}300 \\times \\$10M \\\\\n= \\$83B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDamage_{infra,total} \\\\\n= Damage_{comms} + Damage_{edu} + Damage_{energy} \\\\\n+ Damage_{health} + Damage_{transport} + Damage_{water} \\\\\n= \\$298B + \\$234B + \\$422B + \\$166B + \\$487B + \\$268B \\\\\n= \\$1.88T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDisruption_{trade} \\\\\n= Disruption_{currency} + Disruption_{energy} \\\\\n+ Disruption_{shipping} + Disruption_{supply} \\\\\n= \\$57.4B + \\$125B + \\$247B + \\$187B \\\\\n= \\$616B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,indirect} \\\\\n= Damage_{env} + Loss_{growth,mil} + Loss_{capital,conflict} \\\\\n+ Cost_{psych} + Cost_{refugee} + Cost_{vet} \\\\\n= \\$100B + \\$2.72T + \\$300B + \\$232B + \\$150B + \\$200B \\\\\n= \\$3.7T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nBenefit_{RD,ann} \\\\\n= Spending_{trials} \\times Reduce_{pct} \\\\\n= \\$60B \\times 97.7\\% \\\\\n= \\$58.6B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nReduce_{pct} \\\\\n= 1 - \\frac{Cost_{pragmatic,pt}}{Cost_{P3,pt}} \\\\\n= 1 - \\frac{\\$929}{\\$41K} \\\\\n= 97.7\\%\n\\end{gathered}\n$$"
"treaty_peace_recovery_gdp_growth_bonus_year_15": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_peace_recovery_gdp_growth_bonus_year_15\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Annual GDP growth bonus by year 15 from explicit avoided war-cost drag under the treaty take-hold path. | Calculated from 5 inputs | ✓ High confidence | Formula: (PEACE_DIVIDEND_ANNUAL_SOCIETAL_BENEFIT ÷ GLOBAL_GDP_2025) × (TREATY_EFFECTIVE_REALLOCATION_SHARE_YEAR_15 ÷ TREATY_REDUCTION_PCT) × PEACE_DIVIDEND_CONFLICT_ELASTICITY | Unit: rate | Click to view details, calculation & sources\">0.435% (95% CI: 0.345%-0.538%)</a>"
"treaty_peace_recovery_gdp_growth_bonus_year_15_latex": "$$\n\\begin{gathered}\ng_{peace,treaty,15} \\\\\n= \\left(\\frac{Benefit_{peace,soc}}{GDP_{global}}\\right) \\times \\left(\\frac{\\bar{s}_{treaty,15}}{Reduce_{treaty}}\\right) \\times \\varepsilon_{conflict}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nBenefit_{peace,soc} \\\\\n= Cost_{war,total} \\times Reduce_{treaty} \\\\\n= \\$11.4T \\times 1\\% \\\\\n= \\$114B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,total} \\\\\n= Cost_{war,direct} + Cost_{war,indirect} \\\\\n= \\$7.66T + \\$3.7T \\\\\n= \\$11.4T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,direct} \\\\\n= Loss_{life,conflict} + Damage_{infra,total} \\\\\n+ Disruption_{trade} + Spending_{mil} \\\\\n= \\$2.45T + \\$1.88T + \\$616B + \\$2.72T \\\\\n= \\$7.66T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{life,conflict} \\\\\n= Cost_{combat,human} + Cost_{state,human} \\\\\n+ Cost_{terror,human} \\\\\n= \\$2.34T + \\$27B + \\$83B \\\\\n= \\$2.45T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{combat,human} \\\\\n= Deaths_{combat} \\times VSL \\\\\n= 234{,}000 \\times \\$10M \\\\\n= \\$2.34T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{state,human} \\\\\n= Deaths_{state} \\times VSL \\\\\n= 2{,}700 \\times \\$10M \\\\\n= \\$27B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{terror,human} \\\\\n= Deaths_{terror} \\times VSL \\\\\n= 8{,}300 \\times \\$10M \\\\\n= \\$83B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDamage_{infra,total} \\\\\n= Damage_{comms} + Damage_{edu} + Damage_{energy} \\\\\n+ Damage_{health} + Damage_{transport} + Damage_{water} \\\\\n= \\$298B + \\$234B + \\$422B + \\$166B + \\$487B + \\$268B \\\\\n= \\$1.88T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDisruption_{trade} \\\\\n= Disruption_{currency} + Disruption_{energy} \\\\\n+ Disruption_{shipping} + Disruption_{supply} \\\\\n= \\$57.4B + \\$125B + \\$247B + \\$187B \\\\\n= \\$616B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,indirect} \\\\\n= Damage_{env} + Loss_{growth,mil} + Loss_{capital,conflict} \\\\\n+ Cost_{psych} + Cost_{refugee} + Cost_{vet} \\\\\n= \\$100B + \\$2.72T + \\$300B + \\$232B + \\$150B + \\$200B \\\\\n= \\$3.7T\n\\end{gathered}\n$$"
"treaty_peace_recovery_gdp_growth_bonus_year_20": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_peace_recovery_gdp_growth_bonus_year_20\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Annual GDP growth bonus by year 20 from explicit avoided war-cost drag under the treaty take-hold path. | Calculated from 5 inputs | ✓ High confidence | Formula: (PEACE_DIVIDEND_ANNUAL_SOCIETAL_BENEFIT ÷ GLOBAL_GDP_2025) × (TREATY_EFFECTIVE_REALLOCATION_SHARE_YEAR_20 ÷ TREATY_REDUCTION_PCT) × PEACE_DIVIDEND_CONFLICT_ELASTICITY | Unit: rate | Click to view details, calculation & sources\">0.573% (95% CI: 0.455%-0.709%)</a>"
"treaty_peace_recovery_gdp_growth_bonus_year_20_latex": "$$\n\\begin{gathered}\ng_{peace,treaty,20} \\\\\n= \\left(\\frac{Benefit_{peace,soc}}{GDP_{global}}\\right) \\times \\left(\\frac{\\bar{s}_{treaty,20}}{Reduce_{treaty}}\\right) \\times \\varepsilon_{conflict}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nBenefit_{peace,soc} \\\\\n= Cost_{war,total} \\times Reduce_{treaty} \\\\\n= \\$11.4T \\times 1\\% \\\\\n= \\$114B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,total} \\\\\n= Cost_{war,direct} + Cost_{war,indirect} \\\\\n= \\$7.66T + \\$3.7T \\\\\n= \\$11.4T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,direct} \\\\\n= Loss_{life,conflict} + Damage_{infra,total} \\\\\n+ Disruption_{trade} + Spending_{mil} \\\\\n= \\$2.45T + \\$1.88T + \\$616B + \\$2.72T \\\\\n= \\$7.66T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{life,conflict} \\\\\n= Cost_{combat,human} + Cost_{state,human} \\\\\n+ Cost_{terror,human} \\\\\n= \\$2.34T + \\$27B + \\$83B \\\\\n= \\$2.45T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{combat,human} \\\\\n= Deaths_{combat} \\times VSL \\\\\n= 234{,}000 \\times \\$10M \\\\\n= \\$2.34T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{state,human} \\\\\n= Deaths_{state} \\times VSL \\\\\n= 2{,}700 \\times \\$10M \\\\\n= \\$27B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{terror,human} \\\\\n= Deaths_{terror} \\times VSL \\\\\n= 8{,}300 \\times \\$10M \\\\\n= \\$83B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDamage_{infra,total} \\\\\n= Damage_{comms} + Damage_{edu} + Damage_{energy} \\\\\n+ Damage_{health} + Damage_{transport} + Damage_{water} \\\\\n= \\$298B + \\$234B + \\$422B + \\$166B + \\$487B + \\$268B \\\\\n= \\$1.88T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDisruption_{trade} \\\\\n= Disruption_{currency} + Disruption_{energy} \\\\\n+ Disruption_{shipping} + Disruption_{supply} \\\\\n= \\$57.4B + \\$125B + \\$247B + \\$187B \\\\\n= \\$616B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,indirect} \\\\\n= Damage_{env} + Loss_{growth,mil} + Loss_{capital,conflict} \\\\\n+ Cost_{psych} + Cost_{refugee} + Cost_{vet} \\\\\n= \\$100B + \\$2.72T + \\$300B + \\$232B + \\$150B + \\$200B \\\\\n= \\$3.7T\n\\end{gathered}\n$$"
"treaty_personal_upside_blend": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_personal_upside_blend\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Blended personal upside under Treaty Trajectory: lifetime income gain plus valued healthy-life gains. | Calculated from 2 inputs | ✓ High confidence | Formula: TREATY_TRAJECTORY_LIFETIME_INCOME_GAIN_PER_CAPITA + TREATY_HALE_VALUE_PER_CAPITA | Unit: USD/person | Click to view details, calculation & sources\">$6.74M (95% CI: $2.62M-$15.7M)</a>"
"treaty_personal_upside_blend_latex": "$$\n\\begin{gathered}\nUpside_{blend,treaty} \\\\\n= \\Delta Y_{lifetime,treaty} + Value_{HALE,treaty} \\\\\n= \\$3.48M + \\$3.26M \\\\\n= \\$6.74M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\Delta Y_{lifetime,treaty} \\\\\n= Y_{cum,treaty} - Y_{cum,earth} \\\\\n= \\$4.58M - \\$1.1M \\\\\n= \\$3.48M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nY_{cum,treaty} \\\\\n= \\bar{y}_0 \\cdot \\frac{(1+g_{pc,treaty})((1+g_{pc,treaty})^{20}-1)}{g_{pc,treaty}} \\\\\n+ \\bar{y}_{treaty,20} \\cdot \\frac{(1+g_{pc,base})((1+g_{pc,base})^{T_{remaining}-20}-1)}{g_{pc,base}}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{y}_{0} \\\\\n= \\frac{GDP_{global}}{Pop_{global}} \\\\\n= \\frac{\\$115T}{8B} \\\\\n= \\$14.4K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{y}_{treaty,20} \\\\\n= \\frac{GDP_{treaty,20}}{Pop_{2045}} \\\\\n= \\frac{\\$919T}{9.2B} \\\\\n= \\$99.9K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nGDP_{treaty,20} \\\\\n= GDP_{global} \\times (1 + g_{base} + g_{redirect,treaty,20} \\\\\n+ g_{peace,treaty,20} + g_{cyber,treaty,20} \\\\\n+ g_{health,treaty,20})^{20}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{redirect,treaty,20} \\\\\n= \\bar{s}_{treaty,20} \\times \\Delta g_{30\\%} \\times m_{spillover} \\times 1.67 \\\\\n= 5.8\\% \\times 5.5\\% \\times 2 \\times 1.67 \\\\\n= 1.06\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{peace,treaty,20} \\\\\n= \\left(\\frac{Benefit_{peace,soc}}{GDP_{global}}\\right) \\times \\left(\\frac{\\bar{s}_{treaty,20}}{Reduce_{treaty}}\\right) \\times \\varepsilon_{conflict}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nBenefit_{peace,soc} \\\\\n= Cost_{war,total} \\times Reduce_{treaty} \\\\\n= \\$11.4T \\times 1\\% \\\\\n= \\$114B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,total} \\\\\n= Cost_{war,direct} + Cost_{war,indirect} \\\\\n= \\$7.66T + \\$3.7T \\\\\n= \\$11.4T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,direct} \\\\\n= Loss_{life,conflict} + Damage_{infra,total} \\\\\n+ Disruption_{trade} + Spending_{mil} \\\\\n= \\$2.45T + \\$1.88T + \\$616B + \\$2.72T \\\\\n= \\$7.66T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{life,conflict} \\\\\n= Cost_{combat,human} + Cost_{state,human} \\\\\n+ Cost_{terror,human} \\\\\n= \\$2.34T + \\$27B + \\$83B \\\\\n= \\$2.45T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{combat,human} \\\\\n= Deaths_{combat} \\times VSL \\\\\n= 234{,}000 \\times \\$10M \\\\\n= \\$2.34T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{state,human} \\\\\n= Deaths_{state} \\times VSL \\\\\n= 2{,}700 \\times \\$10M \\\\\n= \\$27B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{terror,human} \\\\\n= Deaths_{terror} \\times VSL \\\\\n= 8{,}300 \\times \\$10M \\\\\n= \\$83B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDamage_{infra,total} \\\\\n= Damage_{comms} + Damage_{edu} + Damage_{energy} \\\\\n+ Damage_{health} + Damage_{transport} + Damage_{water} \\\\\n= \\$298B + \\$234B + \\$422B + \\$166B + \\$487B + \\$268B \\\\\n= \\$1.88T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDisruption_{trade} \\\\\n= Disruption_{currency} + Disruption_{energy} \\\\\n+ Disruption_{shipping} + Disruption_{supply} \\\\\n= \\$57.4B + \\$125B + \\$247B + \\$187B \\\\\n= \\$616B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,indirect} \\\\\n= Damage_{env} + Loss_{growth,mil} + Loss_{capital,conflict} \\\\\n+ Cost_{psych} + Cost_{refugee} + Cost_{vet} \\\\\n= \\$100B + \\$2.72T + \\$300B + \\$232B + \\$150B + \\$200B \\\\\n= \\$3.7T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{cyber,treaty,20} \\\\\n= \\left(\\frac{Cost_{cyber}}{GDP_{global}}\\right) \\times \\bar{s}_{treaty,20} \\times \\varepsilon_{conflict}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{health,treaty,20} \\\\\n= ((1 + f_{cure,20,treaty} \\times d_{disease} \\\\\n+ \\left(\\frac{Loss_{lag}}{GDP_{global}}\\right))^{\\frac{1}{20}}) - 1\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nf_{cure,20,treaty} \\\\\n= \\min\\left(1.0, Treatments_{new,ann} \\times (3 \\times min(k_{capacity} \\times 1, k_{capacity,max}) \\\\\n+ 4 \\times min(k_{capacity} \\times 2, k_{capacity,max}) \\\\\n+ 5 \\times min(k_{capacity} \\times 5, k_{capacity,max}) \\\\\n+ 8 \\times min(k_{capacity} \\times 10, k_{capacity,max})) / N_{untreated}\\right)\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity,max} \\\\\n= \\frac{N_{willing}}{Slots_{curr}} \\\\\n= \\frac{1.08B}{1.9M} \\\\\n= 566\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{willing} \\\\\n= N_{patients} \\times Pct_{willing} \\\\\n= 2.4B \\times 44.8\\% \\\\\n= 1.08B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{lag} \\\\\n= Deaths_{lag,total} \\times (LE_{global} - Age_{death,delay}) \\times Value_{QALY} \\\\\n= 102M \\times (79 - 62) \\times \\$150K \\\\\n= \\$259T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDeaths_{lag,total} \\\\\n= Lives_{saved,annual} \\times T_{lag} \\\\\n= 12.4M \\times 8.2 \\\\\n= 102M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLives_{saved,annual} \\\\\n= \\frac{LY_{saved,annual}}{T_{ext}} \\\\\n= \\frac{149M}{12} \\\\\n= 12.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{y}_{base,20} \\\\\n= \\frac{GDP_{base,20}}{Pop_{2045}} \\\\\n= \\frac{\\$188T}{9.2B} \\\\\n= \\$20.5K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nGDP_{base,20} = GDP_{global} \\times (1 + g_{base})^{20}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{remaining} \\\\\n= LE_{global} - Age_{median} \\\\\n= 79 - 30.5 \\\\\n= 48.5\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nY_{cum,earth} \\\\\n= \\bar{y}_0 \\cdot \\frac{(1+g_{pc,base})((1+g_{pc,base})^{T_{remaining}}-1)}{g_{pc,base}}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nValue_{HALE,treaty} \\\\\n= \\Delta HALE_{treaty,15} \\times Value_{QALY} \\\\\n= 21.7 \\times \\$150K \\\\\n= \\$3.26M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\Delta HALE_{treaty,15} \\\\\n= f_{cure,15,treaty} \\times \\Delta_{HALE} \\\\\n+ \\Delta HALE_{treaty,longevity,15}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nf_{cure,15,treaty} \\\\\n= \\min\\left(1.0, Treatments_{new,ann} \\times (3 \\times min(k_{capacity} \\times 1, k_{capacity,max}) \\\\\n+ 4 \\times min(k_{capacity} \\times 2, k_{capacity,max}) \\\\\n+ 5 \\times min(k_{capacity} \\times 5, k_{capacity,max}) \\\\\n+ 3 \\times min(k_{capacity} \\times 10, k_{capacity,max})) / N_{untreated}\\right)\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\Delta HALE_{treaty,longevity,15} \\\\\n= T_{extend} \\times \\rho_{HALE,15} \\times f_{cure,15,treaty} \\\\\n= 20 \\times 30\\% \\times 100\\% \\\\\n= 6\n\\end{gathered}\n$$"
"treaty_projected_hale_year_15": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_projected_hale_year_15\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Projected global HALE at year 15 under Treaty Trajectory. Current HALE plus the treaty-driven improvement from closing the disease gap. | Calculated from 2 inputs | ✓ High confidence | Formula: GLOBAL_HALE_CURRENT + TREATY_HALE_GAIN_YEAR_15 | Unit: years | Click to view details, calculation & sources\">85 years (95% CI: 76.4 years-95.6 years)</a>"
"treaty_projected_hale_year_15_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_projected_hale_year_15\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Projected global HALE at year 15 under Treaty Trajectory. Current HALE plus the treaty-driven improvement from closing the disease gap. | Calculated from 2 inputs | ✓ High confidence | Formula: GLOBAL_HALE_CURRENT + TREATY_HALE_GAIN_YEAR_15 | Unit: years | Click to view details, calculation & sources\">85 (95% CI: 76.4-95.6)</a>"
"treaty_projected_hale_year_15_latex": "$$\n\\begin{gathered}\nHALE_{treaty,15} \\\\\n= HALE_{0} + \\Delta HALE_{treaty,15} \\\\\n= 63.3 + 21.7 \\\\\n= 85\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\Delta HALE_{treaty,15} \\\\\n= f_{cure,15,treaty} \\times \\Delta_{HALE} \\\\\n+ \\Delta HALE_{treaty,longevity,15}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nf_{cure,15,treaty} \\\\\n= \\min\\left(1.0, Treatments_{new,ann} \\times (3 \\times min(k_{capacity} \\times 1, k_{capacity,max}) \\\\\n+ 4 \\times min(k_{capacity} \\times 2, k_{capacity,max}) \\\\\n+ 5 \\times min(k_{capacity} \\times 5, k_{capacity,max}) \\\\\n+ 3 \\times min(k_{capacity} \\times 10, k_{capacity,max})) / N_{untreated}\\right)\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity,max} \\\\\n= \\frac{N_{willing}}{Slots_{curr}} \\\\\n= \\frac{1.08B}{1.9M} \\\\\n= 566\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{willing} \\\\\n= N_{patients} \\times Pct_{willing} \\\\\n= 2.4B \\times 44.8\\% \\\\\n= 1.08B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\Delta HALE_{treaty,longevity,15} \\\\\n= T_{extend} \\times \\rho_{HALE,15} \\times f_{cure,15,treaty} \\\\\n= 20 \\times 30\\% \\times 100\\% \\\\\n= 6\n\\end{gathered}\n$$"
"treaty_qalys_gained_annual_global": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_qalys_gained_annual_global\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Annual QALYs gained from peace dividend (lives saved × QALYs/life) | Calculated from 2 inputs | ✓ High confidence | Formula: LIVES_SAVED × QALYS_PER_LIFE | Unit: QALYs/year | Click to view details, calculation & sources\">85.6 thousand QALYs/year (95% CI: 45.1 thousand QALYs/year-141 thousand QALYs/year)</a>"
"treaty_qalys_gained_annual_global_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_qalys_gained_annual_global\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Annual QALYs gained from peace dividend (lives saved × QALYs/life) | Calculated from 2 inputs | ✓ High confidence | Formula: LIVES_SAVED × QALYS_PER_LIFE | Unit: QALYs/year | Click to view details, calculation & sources\">85.6 thousand (95% CI: 45.1 thousand-141 thousand)</a>"
"treaty_qalys_gained_annual_global_latex": "$$\n\\begin{gathered}\nQALY_{treaty,ann} \\\\\n= QALY_{life} \\times Lives_{treaty,ann} \\\\\n= 35 \\times 2{,}450 \\\\\n= 85{,}600\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLives_{treaty,ann} \\\\\n= Deaths_{conflict} \\times Reduce_{treaty} \\\\\n= 245{,}000 \\times 1\\% \\\\\n= 2{,}450\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDeaths_{conflict} \\\\\n= Deaths_{combat} + Deaths_{state} + Deaths_{terror} \\\\\n= 234{,}000 + 2{,}700 + 8{,}300 \\\\\n= 245{,}000\n\\end{gathered}\n$$"
"treaty_redirected_spending_infinite_roi": "<span class=\"parameter-definition\" title=\"ROI when redirecting existing spending (no new costs = infinite return) | Unit: ratio | Core definition\">0</span>"
"treaty_redirected_spending_infinite_roi_latex": "$$\n\\begin{gathered}\n\\text{ROI} \\\\\n= \\frac{\\text{Annual Benefits}}{\\text{New Spending}} \\\\\n= \\frac{\\$172B}{0} \\\\\n= \\infty\n\\end{gathered}\n$$"
"treaty_redirect_gdp_growth_bonus_year_15": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_redirect_gdp_growth_bonus_year_15\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Annual GDP growth bonus by year 15 from redirecting military spending to medical research under the treaty take-hold path, including R&D spillovers. | Calculated from 3 inputs | ✓ High confidence | Formula: TREATY_EFFECTIVE_REALLOCATION_SHARE_YEAR_15 × ((MILITARY_REDIRECT_GDP_BOOST_AT_30PCT ÷ 0.30) × (RD_SPILLOVER_MULTIPLIER ÷ 2.0)) | Unit: rate | Click to view details, calculation & sources\">0.807% (95% CI: 0.444%-1.26%)</a>"
"treaty_redirect_gdp_growth_bonus_year_15_latex": "$$\n\\begin{gathered}\ng_{redirect,treaty,15} \\\\\n= \\bar{s}_{treaty,15} \\times \\Delta g_{30\\%} \\times m_{spillover} \\times 1.67 \\\\\n= 4.4\\% \\times 5.5\\% \\times 2 \\times 1.67 \\\\\n= 0.807\\%\n\\end{gathered}\n$$"
"treaty_redirect_gdp_growth_bonus_year_20": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_redirect_gdp_growth_bonus_year_20\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Annual GDP growth bonus by year 20 from redirecting military spending to medical research under the treaty take-hold path, including R&D spillovers. | Calculated from 3 inputs | ✓ High confidence | Formula: TREATY_EFFECTIVE_REALLOCATION_SHARE_YEAR_20 × ((MILITARY_REDIRECT_GDP_BOOST_AT_30PCT ÷ 0.30) × (RD_SPILLOVER_MULTIPLIER ÷ 2.0)) | Unit: rate | Click to view details, calculation & sources\">1.06% (95% CI: 0.585%-1.66%)</a>"
"treaty_redirect_gdp_growth_bonus_year_20_latex": "$$\n\\begin{gathered}\ng_{redirect,treaty,20} \\\\\n= \\bar{s}_{treaty,20} \\times \\Delta g_{30\\%} \\times m_{spillover} \\times 1.67 \\\\\n= 5.8\\% \\times 5.5\\% \\times 2 \\times 1.67 \\\\\n= 1.06\\%\n\\end{gathered}\n$$"
"treaty_reduction_pct": "<span class=\"parameter-definition\" title=\"1% reduction in military spending/war costs from treaty | Unit: rate | Core definition\">1%</span>"
"treaty_roi_existing_drugs_only": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_roi_existing_drugs_only\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Treaty ROI based on historical rate of drug development (existing drugs only). Total one-time benefit from avoiding regulatory delay for drugs already in development divided by campaign cost. Excludes future innovation effects. | Calculated from 2 inputs | ✓ High confidence | Formula: HISTORICAL_PROGRESS_TOTAL ÷ CAMPAIGN_COST | Unit: ratio | Click to view details, calculation & sources\">259k (95% CI: 110k-419k)</a>"
"treaty_roi_existing_drugs_only_latex": "$$\n\\begin{gathered}\nROI_{drugs} \\\\\n= \\frac{Loss_{lag}}{Cost_{campaign}} \\\\\n= \\frac{\\$259T}{\\$1B} \\\\\n= 259{,}000\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{lag} \\\\\n= Deaths_{lag,total} \\times (LE_{global} - Age_{death,delay}) \\times Value_{QALY} \\\\\n= 102M \\times (79 - 62) \\times \\$150K \\\\\n= \\$259T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDeaths_{lag,total} \\\\\n= Lives_{saved,annual} \\times T_{lag} \\\\\n= 12.4M \\times 8.2 \\\\\n= 102M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLives_{saved,annual} \\\\\n= \\frac{LY_{saved,annual}}{T_{ext}} \\\\\n= \\frac{149M}{12} \\\\\n= 12.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{campaign} \\\\\n= Budget_{viral,base} + Budget_{lobby,treaty} \\\\\n+ Budget_{reserve} \\\\\n= \\$250M + \\$650M + \\$100M \\\\\n= \\$1B\n\\end{gathered}\n$$"
"treaty_roi_trial_capacity_plus_efficacy_lag": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_roi_trial_capacity_plus_efficacy_lag\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Treaty ROI from elimination of efficacy lag plus earlier treatment discovery from increased trial throughput. Total one-time benefit divided by campaign cost. This is the primary ROI estimate for total health benefits. | Calculated from 2 inputs | ~ Medium confidence | Formula: DFDA_TRIAL_CAPACITY_PLUS_EFFICACY_LAG_ECONOMIC_VALUE ÷ CAMPAIGN_COST | Unit: ratio | Click to view details, calculation & sources\">84.8M (95% CI: 46.6M-144M)</a>"
"treaty_roi_trial_capacity_plus_efficacy_lag_latex": "$$\n\\begin{gathered}\nROI_{max} \\\\\n= \\frac{Value_{max}}{Cost_{campaign}} \\\\\n= \\frac{\\$84800T}{\\$1B} \\\\\n= 84.8M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nValue_{max} \\\\\n= DALYs_{max} \\times Value_{QALY} \\\\\n= 565B \\times \\$150K \\\\\n= \\$84800T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDALYs_{max} \\\\\n= DALYs_{global,ann} \\times Pct_{avoid,DALY} \\times T_{accel,max} \\\\\n= 2.88B \\times 92.6\\% \\times 212 \\\\\n= 565B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nT_{accel,max} = T_{accel} + T_{lag} = 204 + 8.2 = 212\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{accel} \\\\\n= T_{first,SQ} \\times \\left(1 - \\frac{1}{k_{capacity}}\\right) \\\\\n= 222 \\times \\left(1 - \\frac{1}{12.3}\\right) \\\\\n= 204\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{first,SQ} \\\\\n= T_{queue,SQ} \\times 0.5 \\\\\n= 443 \\times 0.5 \\\\\n= 222\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{queue,SQ} \\\\\n= \\frac{N_{untreated}}{Treatments_{new,ann}} \\\\\n= \\frac{6{,}650}{15} \\\\\n= 443\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{campaign} \\\\\n= Budget_{viral,base} + Budget_{lobby,treaty} \\\\\n+ Budget_{reserve} \\\\\n= \\$250M + \\$650M + \\$100M \\\\\n= \\$1B\n\\end{gathered}\n$$"
"treaty_total_annual_costs": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_total_annual_costs\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Total annual system costs (campaign + Decentralized Framework for Drug Assessment operations) | Calculated from 2 inputs | ✓ High confidence | Formula: CAMPAIGN_ANNUAL + DFDA_OPEX | Unit: USD/year | Click to view details, calculation & sources\">$290M (95% CI: $185M-$434M)</a>"
"treaty_total_annual_costs_latex": "$$\n\\begin{gathered}\nCost_{treaty,ann} \\\\\n= OPEX_{dFDA} + Cost_{camp,amort} \\\\\n= \\$40M + \\$250M \\\\\n= \\$290M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{camp,amort} \\\\\n= \\frac{Cost_{campaign}}{T_{campaign}} \\\\\n= \\frac{\\$1B}{4} \\\\\n= \\$250M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{campaign} \\\\\n= Budget_{viral,base} + Budget_{lobby,treaty} \\\\\n+ Budget_{reserve} \\\\\n= \\$250M + \\$650M + \\$100M \\\\\n= \\$1B\n\\end{gathered}\n$$"
"treaty_trajectory_avg_income_year_15": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_trajectory_avg_income_year_15\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Average income (GDP per capita) at year 15 under the Treaty Trajectory. | Calculated from 2 inputs | ✓ High confidence | Formula: TREATY_TRAJECTORY_GDP_YEAR_15 / GLOBAL_POPULATION_2040_PROJECTED | Unit: USD | Click to view details, calculation & sources\">$76.7K (95% CI: $37.8K-$161K)</a>"
"treaty_trajectory_avg_income_year_15_latex": "$$\n\\begin{gathered}\n\\bar{y}_{treaty,15} \\\\\n= \\frac{GDP_{treaty,15}}{Pop_{2040}} \\\\\n= \\frac{\\$683T}{8.9B} \\\\\n= \\$76.7K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nGDP_{treaty,15} \\\\\n= GDP_{global} \\times (1 + g_{base} + g_{redirect,treaty,15} \\\\\n+ g_{peace,treaty,15} + g_{cyber,treaty,15} \\\\\n+ g_{health,treaty,15})^{15}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{redirect,treaty,15} \\\\\n= \\bar{s}_{treaty,15} \\times \\Delta g_{30\\%} \\times m_{spillover} \\times 1.67 \\\\\n= 4.4\\% \\times 5.5\\% \\times 2 \\times 1.67 \\\\\n= 0.807\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{peace,treaty,15} \\\\\n= \\left(\\frac{Benefit_{peace,soc}}{GDP_{global}}\\right) \\times \\left(\\frac{\\bar{s}_{treaty,15}}{Reduce_{treaty}}\\right) \\times \\varepsilon_{conflict}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nBenefit_{peace,soc} \\\\\n= Cost_{war,total} \\times Reduce_{treaty} \\\\\n= \\$11.4T \\times 1\\% \\\\\n= \\$114B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,total} \\\\\n= Cost_{war,direct} + Cost_{war,indirect} \\\\\n= \\$7.66T + \\$3.7T \\\\\n= \\$11.4T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,direct} \\\\\n= Loss_{life,conflict} + Damage_{infra,total} \\\\\n+ Disruption_{trade} + Spending_{mil} \\\\\n= \\$2.45T + \\$1.88T + \\$616B + \\$2.72T \\\\\n= \\$7.66T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{life,conflict} \\\\\n= Cost_{combat,human} + Cost_{state,human} \\\\\n+ Cost_{terror,human} \\\\\n= \\$2.34T + \\$27B + \\$83B \\\\\n= \\$2.45T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{combat,human} \\\\\n= Deaths_{combat} \\times VSL \\\\\n= 234{,}000 \\times \\$10M \\\\\n= \\$2.34T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{state,human} \\\\\n= Deaths_{state} \\times VSL \\\\\n= 2{,}700 \\times \\$10M \\\\\n= \\$27B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{terror,human} \\\\\n= Deaths_{terror} \\times VSL \\\\\n= 8{,}300 \\times \\$10M \\\\\n= \\$83B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDamage_{infra,total} \\\\\n= Damage_{comms} + Damage_{edu} + Damage_{energy} \\\\\n+ Damage_{health} + Damage_{transport} + Damage_{water} \\\\\n= \\$298B + \\$234B + \\$422B + \\$166B + \\$487B + \\$268B \\\\\n= \\$1.88T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDisruption_{trade} \\\\\n= Disruption_{currency} + Disruption_{energy} \\\\\n+ Disruption_{shipping} + Disruption_{supply} \\\\\n= \\$57.4B + \\$125B + \\$247B + \\$187B \\\\\n= \\$616B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,indirect} \\\\\n= Damage_{env} + Loss_{growth,mil} + Loss_{capital,conflict} \\\\\n+ Cost_{psych} + Cost_{refugee} + Cost_{vet} \\\\\n= \\$100B + \\$2.72T + \\$300B + \\$232B + \\$150B + \\$200B \\\\\n= \\$3.7T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{cyber,treaty,15} \\\\\n= \\left(\\frac{Cost_{cyber}}{GDP_{global}}\\right) \\times \\bar{s}_{treaty,15} \\times \\varepsilon_{conflict}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{health,treaty,15} \\\\\n= ((1 + f_{cure,15,treaty} \\times d_{disease} \\\\\n+ \\left(\\frac{Loss_{lag}}{GDP_{global}}\\right))^{\\frac{1}{15}}) - 1\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nf_{cure,15,treaty} \\\\\n= \\min\\left(1.0, Treatments_{new,ann} \\times (3 \\times min(k_{capacity} \\times 1, k_{capacity,max}) \\\\\n+ 4 \\times min(k_{capacity} \\times 2, k_{capacity,max}) \\\\\n+ 5 \\times min(k_{capacity} \\times 5, k_{capacity,max}) \\\\\n+ 3 \\times min(k_{capacity} \\times 10, k_{capacity,max})) / N_{untreated}\\right)\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity,max} \\\\\n= \\frac{N_{willing}}{Slots_{curr}} \\\\\n= \\frac{1.08B}{1.9M} \\\\\n= 566\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{willing} \\\\\n= N_{patients} \\times Pct_{willing} \\\\\n= 2.4B \\times 44.8\\% \\\\\n= 1.08B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{lag} \\\\\n= Deaths_{lag,total} \\times (LE_{global} - Age_{death,delay}) \\times Value_{QALY} \\\\\n= 102M \\times (79 - 62) \\times \\$150K \\\\\n= \\$259T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDeaths_{lag,total} \\\\\n= Lives_{saved,annual} \\times T_{lag} \\\\\n= 12.4M \\times 8.2 \\\\\n= 102M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLives_{saved,annual} \\\\\n= \\frac{LY_{saved,annual}}{T_{ext}} \\\\\n= \\frac{149M}{12} \\\\\n= 12.4M\n\\end{gathered}\n$$"
"treaty_trajectory_avg_income_year_20": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_trajectory_avg_income_year_20\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Average income (GDP per capita) at year 20 under the Treaty Trajectory. | Calculated from 2 inputs | ✓ High confidence | Formula: TREATY_TRAJECTORY_GDP_YEAR_20 / GLOBAL_POPULATION_2045_PROJECTED | Unit: USD | Click to view details, calculation & sources\">$99.9K (95% CI: $47.1K-$222K)</a>"
"treaty_trajectory_avg_income_year_20_latex": "$$\n\\begin{gathered}\n\\bar{y}_{treaty,20} \\\\\n= \\frac{GDP_{treaty,20}}{Pop_{2045}} \\\\\n= \\frac{\\$919T}{9.2B} \\\\\n= \\$99.9K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nGDP_{treaty,20} \\\\\n= GDP_{global} \\times (1 + g_{base} + g_{redirect,treaty,20} \\\\\n+ g_{peace,treaty,20} + g_{cyber,treaty,20} \\\\\n+ g_{health,treaty,20})^{20}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{redirect,treaty,20} \\\\\n= \\bar{s}_{treaty,20} \\times \\Delta g_{30\\%} \\times m_{spillover} \\times 1.67 \\\\\n= 5.8\\% \\times 5.5\\% \\times 2 \\times 1.67 \\\\\n= 1.06\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{peace,treaty,20} \\\\\n= \\left(\\frac{Benefit_{peace,soc}}{GDP_{global}}\\right) \\times \\left(\\frac{\\bar{s}_{treaty,20}}{Reduce_{treaty}}\\right) \\times \\varepsilon_{conflict}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nBenefit_{peace,soc} \\\\\n= Cost_{war,total} \\times Reduce_{treaty} \\\\\n= \\$11.4T \\times 1\\% \\\\\n= \\$114B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,total} \\\\\n= Cost_{war,direct} + Cost_{war,indirect} \\\\\n= \\$7.66T + \\$3.7T \\\\\n= \\$11.4T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,direct} \\\\\n= Loss_{life,conflict} + Damage_{infra,total} \\\\\n+ Disruption_{trade} + Spending_{mil} \\\\\n= \\$2.45T + \\$1.88T + \\$616B + \\$2.72T \\\\\n= \\$7.66T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{life,conflict} \\\\\n= Cost_{combat,human} + Cost_{state,human} \\\\\n+ Cost_{terror,human} \\\\\n= \\$2.34T + \\$27B + \\$83B \\\\\n= \\$2.45T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{combat,human} \\\\\n= Deaths_{combat} \\times VSL \\\\\n= 234{,}000 \\times \\$10M \\\\\n= \\$2.34T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{state,human} \\\\\n= Deaths_{state} \\times VSL \\\\\n= 2{,}700 \\times \\$10M \\\\\n= \\$27B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{terror,human} \\\\\n= Deaths_{terror} \\times VSL \\\\\n= 8{,}300 \\times \\$10M \\\\\n= \\$83B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDamage_{infra,total} \\\\\n= Damage_{comms} + Damage_{edu} + Damage_{energy} \\\\\n+ Damage_{health} + Damage_{transport} + Damage_{water} \\\\\n= \\$298B + \\$234B + \\$422B + \\$166B + \\$487B + \\$268B \\\\\n= \\$1.88T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDisruption_{trade} \\\\\n= Disruption_{currency} + Disruption_{energy} \\\\\n+ Disruption_{shipping} + Disruption_{supply} \\\\\n= \\$57.4B + \\$125B + \\$247B + \\$187B \\\\\n= \\$616B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,indirect} \\\\\n= Damage_{env} + Loss_{growth,mil} + Loss_{capital,conflict} \\\\\n+ Cost_{psych} + Cost_{refugee} + Cost_{vet} \\\\\n= \\$100B + \\$2.72T + \\$300B + \\$232B + \\$150B + \\$200B \\\\\n= \\$3.7T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{cyber,treaty,20} \\\\\n= \\left(\\frac{Cost_{cyber}}{GDP_{global}}\\right) \\times \\bar{s}_{treaty,20} \\times \\varepsilon_{conflict}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{health,treaty,20} \\\\\n= ((1 + f_{cure,20,treaty} \\times d_{disease} \\\\\n+ \\left(\\frac{Loss_{lag}}{GDP_{global}}\\right))^{\\frac{1}{20}}) - 1\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nf_{cure,20,treaty} \\\\\n= \\min\\left(1.0, Treatments_{new,ann} \\times (3 \\times min(k_{capacity} \\times 1, k_{capacity,max}) \\\\\n+ 4 \\times min(k_{capacity} \\times 2, k_{capacity,max}) \\\\\n+ 5 \\times min(k_{capacity} \\times 5, k_{capacity,max}) \\\\\n+ 8 \\times min(k_{capacity} \\times 10, k_{capacity,max})) / N_{untreated}\\right)\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity,max} \\\\\n= \\frac{N_{willing}}{Slots_{curr}} \\\\\n= \\frac{1.08B}{1.9M} \\\\\n= 566\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{willing} \\\\\n= N_{patients} \\times Pct_{willing} \\\\\n= 2.4B \\times 44.8\\% \\\\\n= 1.08B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{lag} \\\\\n= Deaths_{lag,total} \\times (LE_{global} - Age_{death,delay}) \\times Value_{QALY} \\\\\n= 102M \\times (79 - 62) \\times \\$150K \\\\\n= \\$259T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDeaths_{lag,total} \\\\\n= Lives_{saved,annual} \\times T_{lag} \\\\\n= 12.4M \\times 8.2 \\\\\n= 102M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLives_{saved,annual} \\\\\n= \\frac{LY_{saved,annual}}{T_{ext}} \\\\\n= \\frac{149M}{12} \\\\\n= 12.4M\n\\end{gathered}\n$$"
"treaty_trajectory_cagr_year_20": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_trajectory_cagr_year_20\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Compound annual growth rate implied by Treaty Trajectory GDP trajectory over 20 years. | Calculated from 2 inputs | ✓ High confidence | Formula: (TREATY_TRAJECTORY_GDP_YEAR_20 ÷ GLOBAL_GDP_2025)^(1/20) - 1 | Unit: rate | Click to view details, calculation & sources\">10.9% (95% CI: 6.86%-15.5%)</a>"
"treaty_trajectory_cagr_year_20_latex": "$$\n\\begin{gathered}\ng_{treaty,CAGR} \\\\\n= \\left(\\frac{GDP_{treaty,20}}{GDP_{global}}\\right)^{\\frac{1}{20}} - 1\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nGDP_{treaty,20} \\\\\n= GDP_{global} \\times (1 + g_{base} + g_{redirect,treaty,20} \\\\\n+ g_{peace,treaty,20} + g_{cyber,treaty,20} \\\\\n+ g_{health,treaty,20})^{20}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{redirect,treaty,20} \\\\\n= \\bar{s}_{treaty,20} \\times \\Delta g_{30\\%} \\times m_{spillover} \\times 1.67 \\\\\n= 5.8\\% \\times 5.5\\% \\times 2 \\times 1.67 \\\\\n= 1.06\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{peace,treaty,20} \\\\\n= \\left(\\frac{Benefit_{peace,soc}}{GDP_{global}}\\right) \\times \\left(\\frac{\\bar{s}_{treaty,20}}{Reduce_{treaty}}\\right) \\times \\varepsilon_{conflict}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nBenefit_{peace,soc} \\\\\n= Cost_{war,total} \\times Reduce_{treaty} \\\\\n= \\$11.4T \\times 1\\% \\\\\n= \\$114B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,total} \\\\\n= Cost_{war,direct} + Cost_{war,indirect} \\\\\n= \\$7.66T + \\$3.7T \\\\\n= \\$11.4T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,direct} \\\\\n= Loss_{life,conflict} + Damage_{infra,total} \\\\\n+ Disruption_{trade} + Spending_{mil} \\\\\n= \\$2.45T + \\$1.88T + \\$616B + \\$2.72T \\\\\n= \\$7.66T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{life,conflict} \\\\\n= Cost_{combat,human} + Cost_{state,human} \\\\\n+ Cost_{terror,human} \\\\\n= \\$2.34T + \\$27B + \\$83B \\\\\n= \\$2.45T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{combat,human} \\\\\n= Deaths_{combat} \\times VSL \\\\\n= 234{,}000 \\times \\$10M \\\\\n= \\$2.34T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{state,human} \\\\\n= Deaths_{state} \\times VSL \\\\\n= 2{,}700 \\times \\$10M \\\\\n= \\$27B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{terror,human} \\\\\n= Deaths_{terror} \\times VSL \\\\\n= 8{,}300 \\times \\$10M \\\\\n= \\$83B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDamage_{infra,total} \\\\\n= Damage_{comms} + Damage_{edu} + Damage_{energy} \\\\\n+ Damage_{health} + Damage_{transport} + Damage_{water} \\\\\n= \\$298B + \\$234B + \\$422B + \\$166B + \\$487B + \\$268B \\\\\n= \\$1.88T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDisruption_{trade} \\\\\n= Disruption_{currency} + Disruption_{energy} \\\\\n+ Disruption_{shipping} + Disruption_{supply} \\\\\n= \\$57.4B + \\$125B + \\$247B + \\$187B \\\\\n= \\$616B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,indirect} \\\\\n= Damage_{env} + Loss_{growth,mil} + Loss_{capital,conflict} \\\\\n+ Cost_{psych} + Cost_{refugee} + Cost_{vet} \\\\\n= \\$100B + \\$2.72T + \\$300B + \\$232B + \\$150B + \\$200B \\\\\n= \\$3.7T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{cyber,treaty,20} \\\\\n= \\left(\\frac{Cost_{cyber}}{GDP_{global}}\\right) \\times \\bar{s}_{treaty,20} \\times \\varepsilon_{conflict}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{health,treaty,20} \\\\\n= ((1 + f_{cure,20,treaty} \\times d_{disease} \\\\\n+ \\left(\\frac{Loss_{lag}}{GDP_{global}}\\right))^{\\frac{1}{20}}) - 1\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nf_{cure,20,treaty} \\\\\n= \\min\\left(1.0, Treatments_{new,ann} \\times (3 \\times min(k_{capacity} \\times 1, k_{capacity,max}) \\\\\n+ 4 \\times min(k_{capacity} \\times 2, k_{capacity,max}) \\\\\n+ 5 \\times min(k_{capacity} \\times 5, k_{capacity,max}) \\\\\n+ 8 \\times min(k_{capacity} \\times 10, k_{capacity,max})) / N_{untreated}\\right)\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity,max} \\\\\n= \\frac{N_{willing}}{Slots_{curr}} \\\\\n= \\frac{1.08B}{1.9M} \\\\\n= 566\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{willing} \\\\\n= N_{patients} \\times Pct_{willing} \\\\\n= 2.4B \\times 44.8\\% \\\\\n= 1.08B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{lag} \\\\\n= Deaths_{lag,total} \\times (LE_{global} - Age_{death,delay}) \\times Value_{QALY} \\\\\n= 102M \\times (79 - 62) \\times \\$150K \\\\\n= \\$259T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDeaths_{lag,total} \\\\\n= Lives_{saved,annual} \\times T_{lag} \\\\\n= 12.4M \\times 8.2 \\\\\n= 102M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLives_{saved,annual} \\\\\n= \\frac{LY_{saved,annual}}{T_{ext}} \\\\\n= \\frac{149M}{12} \\\\\n= 12.4M\n\\end{gathered}\n$$"
"treaty_trajectory_cumulative_lifetime_income": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_trajectory_cumulative_lifetime_income\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Cumulative per-capita income over an average remaining lifespan under Treaty Trajectory. Uses implied per-capita CAGR for years 1-20 (derived from known year-0 and year-20 per-capita incomes), then current-trajectory per-capita growth from the year-20 level. Conservative: assumes no further treaty acceleration beyond year 20. | Calculated from 4 inputs | ✓ High confidence | Formula: Phase 1: y0*(1+g_pc,treaty)*((1+g_pc,treaty)^20-1)/g_pc,treaty + Phase 2: y20*(1+g_pc,base)*((1+g_pc,base)^(T-20)-1)/g_pc,base | Unit: USD | Click to view details, calculation & sources\">$4.58M (95% CI: $2.04M-$11M)</a>"
"treaty_trajectory_cumulative_lifetime_income_latex": "$$\n\\begin{gathered}\nY_{cum,treaty} \\\\\n= \\bar{y}_0 \\cdot \\frac{(1+g_{pc,treaty})((1+g_{pc,treaty})^{20}-1)}{g_{pc,treaty}} \\\\\n+ \\bar{y}_{treaty,20} \\cdot \\frac{(1+g_{pc,base})((1+g_{pc,base})^{T_{remaining}-20}-1)}{g_{pc,base}}\n\\end{gathered}\n$$"
"treaty_trajectory_gdp_vs_current_trajectory_multiplier_year_15": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_trajectory_gdp_vs_current_trajectory_multiplier_year_15\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Treaty Trajectory GDP at year 15 as a multiple of current trajectory GDP at year 15. | Calculated from 2 inputs | ✓ High confidence | Formula: TREATY_TRAJECTORY_GDP_YEAR_15 / CURRENT_TRAJECTORY_GDP_YEAR_15 | Unit: x | Click to view details, calculation & sources\">4.1x (95% CI: 2.02x-8.62x)</a>"
"treaty_trajectory_gdp_vs_current_trajectory_multiplier_year_15_latex": "$$\n\\begin{gathered}\nk_{treaty:base,15} \\\\\n= \\frac{GDP_{treaty,15}}{GDP_{base,15}} \\\\\n= \\frac{\\$683T}{\\$167T} \\\\\n= 4.1\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nGDP_{treaty,15} \\\\\n= GDP_{global} \\times (1 + g_{base} + g_{redirect,treaty,15} \\\\\n+ g_{peace,treaty,15} + g_{cyber,treaty,15} \\\\\n+ g_{health,treaty,15})^{15}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{redirect,treaty,15} \\\\\n= \\bar{s}_{treaty,15} \\times \\Delta g_{30\\%} \\times m_{spillover} \\times 1.67 \\\\\n= 4.4\\% \\times 5.5\\% \\times 2 \\times 1.67 \\\\\n= 0.807\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{peace,treaty,15} \\\\\n= \\left(\\frac{Benefit_{peace,soc}}{GDP_{global}}\\right) \\times \\left(\\frac{\\bar{s}_{treaty,15}}{Reduce_{treaty}}\\right) \\times \\varepsilon_{conflict}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nBenefit_{peace,soc} \\\\\n= Cost_{war,total} \\times Reduce_{treaty} \\\\\n= \\$11.4T \\times 1\\% \\\\\n= \\$114B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,total} \\\\\n= Cost_{war,direct} + Cost_{war,indirect} \\\\\n= \\$7.66T + \\$3.7T \\\\\n= \\$11.4T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,direct} \\\\\n= Loss_{life,conflict} + Damage_{infra,total} \\\\\n+ Disruption_{trade} + Spending_{mil} \\\\\n= \\$2.45T + \\$1.88T + \\$616B + \\$2.72T \\\\\n= \\$7.66T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{life,conflict} \\\\\n= Cost_{combat,human} + Cost_{state,human} \\\\\n+ Cost_{terror,human} \\\\\n= \\$2.34T + \\$27B + \\$83B \\\\\n= \\$2.45T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{combat,human} \\\\\n= Deaths_{combat} \\times VSL \\\\\n= 234{,}000 \\times \\$10M \\\\\n= \\$2.34T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{state,human} \\\\\n= Deaths_{state} \\times VSL \\\\\n= 2{,}700 \\times \\$10M \\\\\n= \\$27B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{terror,human} \\\\\n= Deaths_{terror} \\times VSL \\\\\n= 8{,}300 \\times \\$10M \\\\\n= \\$83B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDamage_{infra,total} \\\\\n= Damage_{comms} + Damage_{edu} + Damage_{energy} \\\\\n+ Damage_{health} + Damage_{transport} + Damage_{water} \\\\\n= \\$298B + \\$234B + \\$422B + \\$166B + \\$487B + \\$268B \\\\\n= \\$1.88T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDisruption_{trade} \\\\\n= Disruption_{currency} + Disruption_{energy} \\\\\n+ Disruption_{shipping} + Disruption_{supply} \\\\\n= \\$57.4B + \\$125B + \\$247B + \\$187B \\\\\n= \\$616B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,indirect} \\\\\n= Damage_{env} + Loss_{growth,mil} + Loss_{capital,conflict} \\\\\n+ Cost_{psych} + Cost_{refugee} + Cost_{vet} \\\\\n= \\$100B + \\$2.72T + \\$300B + \\$232B + \\$150B + \\$200B \\\\\n= \\$3.7T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{cyber,treaty,15} \\\\\n= \\left(\\frac{Cost_{cyber}}{GDP_{global}}\\right) \\times \\bar{s}_{treaty,15} \\times \\varepsilon_{conflict}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{health,treaty,15} \\\\\n= ((1 + f_{cure,15,treaty} \\times d_{disease} \\\\\n+ \\left(\\frac{Loss_{lag}}{GDP_{global}}\\right))^{\\frac{1}{15}}) - 1\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nf_{cure,15,treaty} \\\\\n= \\min\\left(1.0, Treatments_{new,ann} \\times (3 \\times min(k_{capacity} \\times 1, k_{capacity,max}) \\\\\n+ 4 \\times min(k_{capacity} \\times 2, k_{capacity,max}) \\\\\n+ 5 \\times min(k_{capacity} \\times 5, k_{capacity,max}) \\\\\n+ 3 \\times min(k_{capacity} \\times 10, k_{capacity,max})) / N_{untreated}\\right)\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity,max} \\\\\n= \\frac{N_{willing}}{Slots_{curr}} \\\\\n= \\frac{1.08B}{1.9M} \\\\\n= 566\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{willing} \\\\\n= N_{patients} \\times Pct_{willing} \\\\\n= 2.4B \\times 44.8\\% \\\\\n= 1.08B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{lag} \\\\\n= Deaths_{lag,total} \\times (LE_{global} - Age_{death,delay}) \\times Value_{QALY} \\\\\n= 102M \\times (79 - 62) \\times \\$150K \\\\\n= \\$259T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDeaths_{lag,total} \\\\\n= Lives_{saved,annual} \\times T_{lag} \\\\\n= 12.4M \\times 8.2 \\\\\n= 102M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLives_{saved,annual} \\\\\n= \\frac{LY_{saved,annual}}{T_{ext}} \\\\\n= \\frac{149M}{12} \\\\\n= 12.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nGDP_{base,15} = GDP_{global} \\times (1 + g_{base})^{15}\n$$"
"treaty_trajectory_gdp_vs_current_trajectory_multiplier_year_20": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_trajectory_gdp_vs_current_trajectory_multiplier_year_20\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Treaty Trajectory GDP at year 20 as a multiple of current trajectory GDP at year 20. | Calculated from 2 inputs | ✓ High confidence | Formula: TREATY_TRAJECTORY_GDP_YEAR_20 ÷ CURRENT_TRAJECTORY_GDP_YEAR_20 | Unit: x | Click to view details, calculation & sources\">4.88x (95% CI: 2.3x-10.8x)</a>"
"treaty_trajectory_gdp_vs_current_trajectory_multiplier_year_20_latex": "$$\n\\begin{gathered}\nk_{treaty:base,20} \\\\\n= \\frac{GDP_{treaty,20}}{GDP_{base,20}} \\\\\n= \\frac{\\$919T}{\\$188T} \\\\\n= 4.88\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nGDP_{treaty,20} \\\\\n= GDP_{global} \\times (1 + g_{base} + g_{redirect,treaty,20} \\\\\n+ g_{peace,treaty,20} + g_{cyber,treaty,20} \\\\\n+ g_{health,treaty,20})^{20}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{redirect,treaty,20} \\\\\n= \\bar{s}_{treaty,20} \\times \\Delta g_{30\\%} \\times m_{spillover} \\times 1.67 \\\\\n= 5.8\\% \\times 5.5\\% \\times 2 \\times 1.67 \\\\\n= 1.06\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{peace,treaty,20} \\\\\n= \\left(\\frac{Benefit_{peace,soc}}{GDP_{global}}\\right) \\times \\left(\\frac{\\bar{s}_{treaty,20}}{Reduce_{treaty}}\\right) \\times \\varepsilon_{conflict}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nBenefit_{peace,soc} \\\\\n= Cost_{war,total} \\times Reduce_{treaty} \\\\\n= \\$11.4T \\times 1\\% \\\\\n= \\$114B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,total} \\\\\n= Cost_{war,direct} + Cost_{war,indirect} \\\\\n= \\$7.66T + \\$3.7T \\\\\n= \\$11.4T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,direct} \\\\\n= Loss_{life,conflict} + Damage_{infra,total} \\\\\n+ Disruption_{trade} + Spending_{mil} \\\\\n= \\$2.45T + \\$1.88T + \\$616B + \\$2.72T \\\\\n= \\$7.66T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{life,conflict} \\\\\n= Cost_{combat,human} + Cost_{state,human} \\\\\n+ Cost_{terror,human} \\\\\n= \\$2.34T + \\$27B + \\$83B \\\\\n= \\$2.45T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{combat,human} \\\\\n= Deaths_{combat} \\times VSL \\\\\n= 234{,}000 \\times \\$10M \\\\\n= \\$2.34T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{state,human} \\\\\n= Deaths_{state} \\times VSL \\\\\n= 2{,}700 \\times \\$10M \\\\\n= \\$27B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{terror,human} \\\\\n= Deaths_{terror} \\times VSL \\\\\n= 8{,}300 \\times \\$10M \\\\\n= \\$83B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDamage_{infra,total} \\\\\n= Damage_{comms} + Damage_{edu} + Damage_{energy} \\\\\n+ Damage_{health} + Damage_{transport} + Damage_{water} \\\\\n= \\$298B + \\$234B + \\$422B + \\$166B + \\$487B + \\$268B \\\\\n= \\$1.88T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDisruption_{trade} \\\\\n= Disruption_{currency} + Disruption_{energy} \\\\\n+ Disruption_{shipping} + Disruption_{supply} \\\\\n= \\$57.4B + \\$125B + \\$247B + \\$187B \\\\\n= \\$616B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,indirect} \\\\\n= Damage_{env} + Loss_{growth,mil} + Loss_{capital,conflict} \\\\\n+ Cost_{psych} + Cost_{refugee} + Cost_{vet} \\\\\n= \\$100B + \\$2.72T + \\$300B + \\$232B + \\$150B + \\$200B \\\\\n= \\$3.7T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{cyber,treaty,20} \\\\\n= \\left(\\frac{Cost_{cyber}}{GDP_{global}}\\right) \\times \\bar{s}_{treaty,20} \\times \\varepsilon_{conflict}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{health,treaty,20} \\\\\n= ((1 + f_{cure,20,treaty} \\times d_{disease} \\\\\n+ \\left(\\frac{Loss_{lag}}{GDP_{global}}\\right))^{\\frac{1}{20}}) - 1\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nf_{cure,20,treaty} \\\\\n= \\min\\left(1.0, Treatments_{new,ann} \\times (3 \\times min(k_{capacity} \\times 1, k_{capacity,max}) \\\\\n+ 4 \\times min(k_{capacity} \\times 2, k_{capacity,max}) \\\\\n+ 5 \\times min(k_{capacity} \\times 5, k_{capacity,max}) \\\\\n+ 8 \\times min(k_{capacity} \\times 10, k_{capacity,max})) / N_{untreated}\\right)\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity,max} \\\\\n= \\frac{N_{willing}}{Slots_{curr}} \\\\\n= \\frac{1.08B}{1.9M} \\\\\n= 566\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{willing} \\\\\n= N_{patients} \\times Pct_{willing} \\\\\n= 2.4B \\times 44.8\\% \\\\\n= 1.08B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{lag} \\\\\n= Deaths_{lag,total} \\times (LE_{global} - Age_{death,delay}) \\times Value_{QALY} \\\\\n= 102M \\times (79 - 62) \\times \\$150K \\\\\n= \\$259T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDeaths_{lag,total} \\\\\n= Lives_{saved,annual} \\times T_{lag} \\\\\n= 12.4M \\times 8.2 \\\\\n= 102M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLives_{saved,annual} \\\\\n= \\frac{LY_{saved,annual}}{T_{ext}} \\\\\n= \\frac{149M}{12} \\\\\n= 12.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nGDP_{base,20} = GDP_{global} \\times (1 + g_{base})^{20}\n$$"
"treaty_trajectory_gdp_year_15": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_trajectory_gdp_year_15\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Projected global GDP at year 15 under the optimistic treaty take-hold path. Compounds baseline growth plus explicit military redirect spillovers, peace dividend recovery, cybercrime drag recovery, and health recovery from disease cures and faster deployment. | Calculated from 6 inputs | ✓ High confidence | Formula: GLOBAL_GDP_2025 × (1 + GDP_BASELINE_GROWTH_RATE + TREATY_REDIRECT_GDP_GROWTH_BONUS_YEAR_15 + TREATY_PEACE_RECOVERY_GDP_GROWTH_BONUS_YEAR_15 + TREATY_CYBERCRIME_RECOVERY_GDP_GROWTH_BONUS_YEAR_15 + TREATY_HEALTH_RECOVERY_GDP_GROWTH_BONUS_YEAR_15)^15 | Unit: USD | Click to view details, calculation & sources\">$683T (95% CI: $336T-$1.43 quadrillion)</a>"
"treaty_trajectory_gdp_year_15_latex": "$$\n\\begin{gathered}\nGDP_{treaty,15} \\\\\n= GDP_{global} \\times (1 + g_{base} + g_{redirect,treaty,15} \\\\\n+ g_{peace,treaty,15} + g_{cyber,treaty,15} \\\\\n+ g_{health,treaty,15})^{15}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{redirect,treaty,15} \\\\\n= \\bar{s}_{treaty,15} \\times \\Delta g_{30\\%} \\times m_{spillover} \\times 1.67 \\\\\n= 4.4\\% \\times 5.5\\% \\times 2 \\times 1.67 \\\\\n= 0.807\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{peace,treaty,15} \\\\\n= \\left(\\frac{Benefit_{peace,soc}}{GDP_{global}}\\right) \\times \\left(\\frac{\\bar{s}_{treaty,15}}{Reduce_{treaty}}\\right) \\times \\varepsilon_{conflict}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nBenefit_{peace,soc} \\\\\n= Cost_{war,total} \\times Reduce_{treaty} \\\\\n= \\$11.4T \\times 1\\% \\\\\n= \\$114B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,total} \\\\\n= Cost_{war,direct} + Cost_{war,indirect} \\\\\n= \\$7.66T + \\$3.7T \\\\\n= \\$11.4T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,direct} \\\\\n= Loss_{life,conflict} + Damage_{infra,total} \\\\\n+ Disruption_{trade} + Spending_{mil} \\\\\n= \\$2.45T + \\$1.88T + \\$616B + \\$2.72T \\\\\n= \\$7.66T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{life,conflict} \\\\\n= Cost_{combat,human} + Cost_{state,human} \\\\\n+ Cost_{terror,human} \\\\\n= \\$2.34T + \\$27B + \\$83B \\\\\n= \\$2.45T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{combat,human} \\\\\n= Deaths_{combat} \\times VSL \\\\\n= 234{,}000 \\times \\$10M \\\\\n= \\$2.34T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{state,human} \\\\\n= Deaths_{state} \\times VSL \\\\\n= 2{,}700 \\times \\$10M \\\\\n= \\$27B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{terror,human} \\\\\n= Deaths_{terror} \\times VSL \\\\\n= 8{,}300 \\times \\$10M \\\\\n= \\$83B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDamage_{infra,total} \\\\\n= Damage_{comms} + Damage_{edu} + Damage_{energy} \\\\\n+ Damage_{health} + Damage_{transport} + Damage_{water} \\\\\n= \\$298B + \\$234B + \\$422B + \\$166B + \\$487B + \\$268B \\\\\n= \\$1.88T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDisruption_{trade} \\\\\n= Disruption_{currency} + Disruption_{energy} \\\\\n+ Disruption_{shipping} + Disruption_{supply} \\\\\n= \\$57.4B + \\$125B + \\$247B + \\$187B \\\\\n= \\$616B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,indirect} \\\\\n= Damage_{env} + Loss_{growth,mil} + Loss_{capital,conflict} \\\\\n+ Cost_{psych} + Cost_{refugee} + Cost_{vet} \\\\\n= \\$100B + \\$2.72T + \\$300B + \\$232B + \\$150B + \\$200B \\\\\n= \\$3.7T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{cyber,treaty,15} \\\\\n= \\left(\\frac{Cost_{cyber}}{GDP_{global}}\\right) \\times \\bar{s}_{treaty,15} \\times \\varepsilon_{conflict}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{health,treaty,15} \\\\\n= ((1 + f_{cure,15,treaty} \\times d_{disease} \\\\\n+ \\left(\\frac{Loss_{lag}}{GDP_{global}}\\right))^{\\frac{1}{15}}) - 1\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nf_{cure,15,treaty} \\\\\n= \\min\\left(1.0, Treatments_{new,ann} \\times (3 \\times min(k_{capacity} \\times 1, k_{capacity,max}) \\\\\n+ 4 \\times min(k_{capacity} \\times 2, k_{capacity,max}) \\\\\n+ 5 \\times min(k_{capacity} \\times 5, k_{capacity,max}) \\\\\n+ 3 \\times min(k_{capacity} \\times 10, k_{capacity,max})) / N_{untreated}\\right)\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity,max} \\\\\n= \\frac{N_{willing}}{Slots_{curr}} \\\\\n= \\frac{1.08B}{1.9M} \\\\\n= 566\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{willing} \\\\\n= N_{patients} \\times Pct_{willing} \\\\\n= 2.4B \\times 44.8\\% \\\\\n= 1.08B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{lag} \\\\\n= Deaths_{lag,total} \\times (LE_{global} - Age_{death,delay}) \\times Value_{QALY} \\\\\n= 102M \\times (79 - 62) \\times \\$150K \\\\\n= \\$259T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDeaths_{lag,total} \\\\\n= Lives_{saved,annual} \\times T_{lag} \\\\\n= 12.4M \\times 8.2 \\\\\n= 102M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLives_{saved,annual} \\\\\n= \\frac{LY_{saved,annual}}{T_{ext}} \\\\\n= \\frac{149M}{12} \\\\\n= 12.4M\n\\end{gathered}\n$$"
"treaty_trajectory_gdp_year_20": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_trajectory_gdp_year_20\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Projected global GDP at year 20 under the optimistic treaty take-hold path. Compounds baseline growth plus explicit military redirect spillovers, peace dividend recovery, cybercrime drag recovery, and health recovery from disease cures and faster deployment. | Calculated from 6 inputs | ✓ High confidence | Formula: GLOBAL_GDP_2025 × (1 + GDP_BASELINE_GROWTH_RATE + TREATY_REDIRECT_GDP_GROWTH_BONUS_YEAR_20 + TREATY_PEACE_RECOVERY_GDP_GROWTH_BONUS_YEAR_20 + TREATY_CYBERCRIME_RECOVERY_GDP_GROWTH_BONUS_YEAR_20 + TREATY_HEALTH_RECOVERY_GDP_GROWTH_BONUS_YEAR_20)^20 | Unit: USD | Click to view details, calculation & sources\">$919T (95% CI: $433T-$2.04 quadrillion)</a>"
"treaty_trajectory_gdp_year_20_latex": "$$\n\\begin{gathered}\nGDP_{treaty,20} \\\\\n= GDP_{global} \\times (1 + g_{base} + g_{redirect,treaty,20} \\\\\n+ g_{peace,treaty,20} + g_{cyber,treaty,20} \\\\\n+ g_{health,treaty,20})^{20}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{redirect,treaty,20} \\\\\n= \\bar{s}_{treaty,20} \\times \\Delta g_{30\\%} \\times m_{spillover} \\times 1.67 \\\\\n= 5.8\\% \\times 5.5\\% \\times 2 \\times 1.67 \\\\\n= 1.06\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{peace,treaty,20} \\\\\n= \\left(\\frac{Benefit_{peace,soc}}{GDP_{global}}\\right) \\times \\left(\\frac{\\bar{s}_{treaty,20}}{Reduce_{treaty}}\\right) \\times \\varepsilon_{conflict}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nBenefit_{peace,soc} \\\\\n= Cost_{war,total} \\times Reduce_{treaty} \\\\\n= \\$11.4T \\times 1\\% \\\\\n= \\$114B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,total} \\\\\n= Cost_{war,direct} + Cost_{war,indirect} \\\\\n= \\$7.66T + \\$3.7T \\\\\n= \\$11.4T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,direct} \\\\\n= Loss_{life,conflict} + Damage_{infra,total} \\\\\n+ Disruption_{trade} + Spending_{mil} \\\\\n= \\$2.45T + \\$1.88T + \\$616B + \\$2.72T \\\\\n= \\$7.66T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{life,conflict} \\\\\n= Cost_{combat,human} + Cost_{state,human} \\\\\n+ Cost_{terror,human} \\\\\n= \\$2.34T + \\$27B + \\$83B \\\\\n= \\$2.45T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{combat,human} \\\\\n= Deaths_{combat} \\times VSL \\\\\n= 234{,}000 \\times \\$10M \\\\\n= \\$2.34T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{state,human} \\\\\n= Deaths_{state} \\times VSL \\\\\n= 2{,}700 \\times \\$10M \\\\\n= \\$27B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{terror,human} \\\\\n= Deaths_{terror} \\times VSL \\\\\n= 8{,}300 \\times \\$10M \\\\\n= \\$83B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDamage_{infra,total} \\\\\n= Damage_{comms} + Damage_{edu} + Damage_{energy} \\\\\n+ Damage_{health} + Damage_{transport} + Damage_{water} \\\\\n= \\$298B + \\$234B + \\$422B + \\$166B + \\$487B + \\$268B \\\\\n= \\$1.88T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDisruption_{trade} \\\\\n= Disruption_{currency} + Disruption_{energy} \\\\\n+ Disruption_{shipping} + Disruption_{supply} \\\\\n= \\$57.4B + \\$125B + \\$247B + \\$187B \\\\\n= \\$616B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,indirect} \\\\\n= Damage_{env} + Loss_{growth,mil} + Loss_{capital,conflict} \\\\\n+ Cost_{psych} + Cost_{refugee} + Cost_{vet} \\\\\n= \\$100B + \\$2.72T + \\$300B + \\$232B + \\$150B + \\$200B \\\\\n= \\$3.7T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{cyber,treaty,20} \\\\\n= \\left(\\frac{Cost_{cyber}}{GDP_{global}}\\right) \\times \\bar{s}_{treaty,20} \\times \\varepsilon_{conflict}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{health,treaty,20} \\\\\n= ((1 + f_{cure,20,treaty} \\times d_{disease} \\\\\n+ \\left(\\frac{Loss_{lag}}{GDP_{global}}\\right))^{\\frac{1}{20}}) - 1\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nf_{cure,20,treaty} \\\\\n= \\min\\left(1.0, Treatments_{new,ann} \\times (3 \\times min(k_{capacity} \\times 1, k_{capacity,max}) \\\\\n+ 4 \\times min(k_{capacity} \\times 2, k_{capacity,max}) \\\\\n+ 5 \\times min(k_{capacity} \\times 5, k_{capacity,max}) \\\\\n+ 8 \\times min(k_{capacity} \\times 10, k_{capacity,max})) / N_{untreated}\\right)\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity,max} \\\\\n= \\frac{N_{willing}}{Slots_{curr}} \\\\\n= \\frac{1.08B}{1.9M} \\\\\n= 566\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{willing} \\\\\n= N_{patients} \\times Pct_{willing} \\\\\n= 2.4B \\times 44.8\\% \\\\\n= 1.08B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{lag} \\\\\n= Deaths_{lag,total} \\times (LE_{global} - Age_{death,delay}) \\times Value_{QALY} \\\\\n= 102M \\times (79 - 62) \\times \\$150K \\\\\n= \\$259T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDeaths_{lag,total} \\\\\n= Lives_{saved,annual} \\times T_{lag} \\\\\n= 12.4M \\times 8.2 \\\\\n= 102M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLives_{saved,annual} \\\\\n= \\frac{LY_{saved,annual}}{T_{ext}} \\\\\n= \\frac{149M}{12} \\\\\n= 12.4M\n\\end{gathered}\n$$"
"treaty_trajectory_lifetime_income_gain_per_capita": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_trajectory_lifetime_income_gain_per_capita\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Lifetime per-capita income gain from Treaty Trajectory vs current trajectory. Cumulative treaty income minus cumulative earth income over average remaining lifespan. Uses global averages; individual gain scales with starting income. | Calculated from 2 inputs | ✓ High confidence | Formula: TREATY_TRAJECTORY_CUMULATIVE_LIFETIME_INCOME - CURRENT_TRAJECTORY_CUMULATIVE_LIFETIME_INCOME | Unit: USD | Click to view details, calculation & sources\">$3.48M (95% CI: $1.05M-$9.82M)</a>"
"treaty_trajectory_lifetime_income_gain_per_capita_latex": "$$\n\\begin{gathered}\n\\Delta Y_{lifetime,treaty} \\\\\n= Y_{cum,treaty} - Y_{cum,earth} \\\\\n= \\$4.58M - \\$1.1M \\\\\n= \\$3.48M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nY_{cum,treaty} \\\\\n= \\bar{y}_0 \\cdot \\frac{(1+g_{pc,treaty})((1+g_{pc,treaty})^{20}-1)}{g_{pc,treaty}} \\\\\n+ \\bar{y}_{treaty,20} \\cdot \\frac{(1+g_{pc,base})((1+g_{pc,base})^{T_{remaining}-20}-1)}{g_{pc,base}}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{y}_{0} \\\\\n= \\frac{GDP_{global}}{Pop_{global}} \\\\\n= \\frac{\\$115T}{8B} \\\\\n= \\$14.4K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{y}_{treaty,20} \\\\\n= \\frac{GDP_{treaty,20}}{Pop_{2045}} \\\\\n= \\frac{\\$919T}{9.2B} \\\\\n= \\$99.9K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nGDP_{treaty,20} \\\\\n= GDP_{global} \\times (1 + g_{base} + g_{redirect,treaty,20} \\\\\n+ g_{peace,treaty,20} + g_{cyber,treaty,20} \\\\\n+ g_{health,treaty,20})^{20}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{redirect,treaty,20} \\\\\n= \\bar{s}_{treaty,20} \\times \\Delta g_{30\\%} \\times m_{spillover} \\times 1.67 \\\\\n= 5.8\\% \\times 5.5\\% \\times 2 \\times 1.67 \\\\\n= 1.06\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{peace,treaty,20} \\\\\n= \\left(\\frac{Benefit_{peace,soc}}{GDP_{global}}\\right) \\times \\left(\\frac{\\bar{s}_{treaty,20}}{Reduce_{treaty}}\\right) \\times \\varepsilon_{conflict}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nBenefit_{peace,soc} \\\\\n= Cost_{war,total} \\times Reduce_{treaty} \\\\\n= \\$11.4T \\times 1\\% \\\\\n= \\$114B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,total} \\\\\n= Cost_{war,direct} + Cost_{war,indirect} \\\\\n= \\$7.66T + \\$3.7T \\\\\n= \\$11.4T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,direct} \\\\\n= Loss_{life,conflict} + Damage_{infra,total} \\\\\n+ Disruption_{trade} + Spending_{mil} \\\\\n= \\$2.45T + \\$1.88T + \\$616B + \\$2.72T \\\\\n= \\$7.66T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{life,conflict} \\\\\n= Cost_{combat,human} + Cost_{state,human} \\\\\n+ Cost_{terror,human} \\\\\n= \\$2.34T + \\$27B + \\$83B \\\\\n= \\$2.45T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{combat,human} \\\\\n= Deaths_{combat} \\times VSL \\\\\n= 234{,}000 \\times \\$10M \\\\\n= \\$2.34T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{state,human} \\\\\n= Deaths_{state} \\times VSL \\\\\n= 2{,}700 \\times \\$10M \\\\\n= \\$27B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{terror,human} \\\\\n= Deaths_{terror} \\times VSL \\\\\n= 8{,}300 \\times \\$10M \\\\\n= \\$83B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDamage_{infra,total} \\\\\n= Damage_{comms} + Damage_{edu} + Damage_{energy} \\\\\n+ Damage_{health} + Damage_{transport} + Damage_{water} \\\\\n= \\$298B + \\$234B + \\$422B + \\$166B + \\$487B + \\$268B \\\\\n= \\$1.88T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDisruption_{trade} \\\\\n= Disruption_{currency} + Disruption_{energy} \\\\\n+ Disruption_{shipping} + Disruption_{supply} \\\\\n= \\$57.4B + \\$125B + \\$247B + \\$187B \\\\\n= \\$616B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,indirect} \\\\\n= Damage_{env} + Loss_{growth,mil} + Loss_{capital,conflict} \\\\\n+ Cost_{psych} + Cost_{refugee} + Cost_{vet} \\\\\n= \\$100B + \\$2.72T + \\$300B + \\$232B + \\$150B + \\$200B \\\\\n= \\$3.7T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{cyber,treaty,20} \\\\\n= \\left(\\frac{Cost_{cyber}}{GDP_{global}}\\right) \\times \\bar{s}_{treaty,20} \\times \\varepsilon_{conflict}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{health,treaty,20} \\\\\n= ((1 + f_{cure,20,treaty} \\times d_{disease} \\\\\n+ \\left(\\frac{Loss_{lag}}{GDP_{global}}\\right))^{\\frac{1}{20}}) - 1\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nf_{cure,20,treaty} \\\\\n= \\min\\left(1.0, Treatments_{new,ann} \\times (3 \\times min(k_{capacity} \\times 1, k_{capacity,max}) \\\\\n+ 4 \\times min(k_{capacity} \\times 2, k_{capacity,max}) \\\\\n+ 5 \\times min(k_{capacity} \\times 5, k_{capacity,max}) \\\\\n+ 8 \\times min(k_{capacity} \\times 10, k_{capacity,max})) / N_{untreated}\\right)\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity,max} \\\\\n= \\frac{N_{willing}}{Slots_{curr}} \\\\\n= \\frac{1.08B}{1.9M} \\\\\n= 566\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{willing} \\\\\n= N_{patients} \\times Pct_{willing} \\\\\n= 2.4B \\times 44.8\\% \\\\\n= 1.08B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{lag} \\\\\n= Deaths_{lag,total} \\times (LE_{global} - Age_{death,delay}) \\times Value_{QALY} \\\\\n= 102M \\times (79 - 62) \\times \\$150K \\\\\n= \\$259T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDeaths_{lag,total} \\\\\n= Lives_{saved,annual} \\times T_{lag} \\\\\n= 12.4M \\times 8.2 \\\\\n= 102M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLives_{saved,annual} \\\\\n= \\frac{LY_{saved,annual}}{T_{ext}} \\\\\n= \\frac{149M}{12} \\\\\n= 12.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{y}_{base,20} \\\\\n= \\frac{GDP_{base,20}}{Pop_{2045}} \\\\\n= \\frac{\\$188T}{9.2B} \\\\\n= \\$20.5K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nGDP_{base,20} = GDP_{global} \\times (1 + g_{base})^{20}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{remaining} \\\\\n= LE_{global} - Age_{median} \\\\\n= 79 - 30.5 \\\\\n= 48.5\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nY_{cum,earth} \\\\\n= \\bar{y}_0 \\cdot \\frac{(1+g_{pc,base})((1+g_{pc,base})^{T_{remaining}}-1)}{g_{pc,base}}\n\\end{gathered}\n$$"
"treaty_trajectory_lifetime_income_multiplier": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_trajectory_lifetime_income_multiplier\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Ratio of cumulative lifetime income under Treaty Trajectory vs current trajectory. Income-agnostic: applies as a multiplier to any individual's lifetime earnings. | Calculated from 2 inputs | ✓ High confidence | Formula: TREATY_TRAJECTORY_CUMULATIVE_LIFETIME_INCOME / CURRENT_TRAJECTORY_CUMULATIVE_LIFETIME_INCOME | Unit: x | Click to view details, calculation & sources\">4.17x (95% CI: 2.06x-9.09x)</a>"
"treaty_trajectory_lifetime_income_multiplier_latex": "$$\n\\begin{gathered}\nk_{lifetime,treaty:earth} \\\\\n= \\frac{Y_{cum,treaty}}{Y_{cum,earth}} \\\\\n= \\frac{\\$4.58M}{\\$1.1M} \\\\\n= 4.17\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nY_{cum,treaty} \\\\\n= \\bar{y}_0 \\cdot \\frac{(1+g_{pc,treaty})((1+g_{pc,treaty})^{20}-1)}{g_{pc,treaty}} \\\\\n+ \\bar{y}_{treaty,20} \\cdot \\frac{(1+g_{pc,base})((1+g_{pc,base})^{T_{remaining}-20}-1)}{g_{pc,base}}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{y}_{0} \\\\\n= \\frac{GDP_{global}}{Pop_{global}} \\\\\n= \\frac{\\$115T}{8B} \\\\\n= \\$14.4K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{y}_{treaty,20} \\\\\n= \\frac{GDP_{treaty,20}}{Pop_{2045}} \\\\\n= \\frac{\\$919T}{9.2B} \\\\\n= \\$99.9K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nGDP_{treaty,20} \\\\\n= GDP_{global} \\times (1 + g_{base} + g_{redirect,treaty,20} \\\\\n+ g_{peace,treaty,20} + g_{cyber,treaty,20} \\\\\n+ g_{health,treaty,20})^{20}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{redirect,treaty,20} \\\\\n= \\bar{s}_{treaty,20} \\times \\Delta g_{30\\%} \\times m_{spillover} \\times 1.67 \\\\\n= 5.8\\% \\times 5.5\\% \\times 2 \\times 1.67 \\\\\n= 1.06\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{peace,treaty,20} \\\\\n= \\left(\\frac{Benefit_{peace,soc}}{GDP_{global}}\\right) \\times \\left(\\frac{\\bar{s}_{treaty,20}}{Reduce_{treaty}}\\right) \\times \\varepsilon_{conflict}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nBenefit_{peace,soc} \\\\\n= Cost_{war,total} \\times Reduce_{treaty} \\\\\n= \\$11.4T \\times 1\\% \\\\\n= \\$114B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,total} \\\\\n= Cost_{war,direct} + Cost_{war,indirect} \\\\\n= \\$7.66T + \\$3.7T \\\\\n= \\$11.4T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,direct} \\\\\n= Loss_{life,conflict} + Damage_{infra,total} \\\\\n+ Disruption_{trade} + Spending_{mil} \\\\\n= \\$2.45T + \\$1.88T + \\$616B + \\$2.72T \\\\\n= \\$7.66T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{life,conflict} \\\\\n= Cost_{combat,human} + Cost_{state,human} \\\\\n+ Cost_{terror,human} \\\\\n= \\$2.34T + \\$27B + \\$83B \\\\\n= \\$2.45T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{combat,human} \\\\\n= Deaths_{combat} \\times VSL \\\\\n= 234{,}000 \\times \\$10M \\\\\n= \\$2.34T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{state,human} \\\\\n= Deaths_{state} \\times VSL \\\\\n= 2{,}700 \\times \\$10M \\\\\n= \\$27B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{terror,human} \\\\\n= Deaths_{terror} \\times VSL \\\\\n= 8{,}300 \\times \\$10M \\\\\n= \\$83B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDamage_{infra,total} \\\\\n= Damage_{comms} + Damage_{edu} + Damage_{energy} \\\\\n+ Damage_{health} + Damage_{transport} + Damage_{water} \\\\\n= \\$298B + \\$234B + \\$422B + \\$166B + \\$487B + \\$268B \\\\\n= \\$1.88T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDisruption_{trade} \\\\\n= Disruption_{currency} + Disruption_{energy} \\\\\n+ Disruption_{shipping} + Disruption_{supply} \\\\\n= \\$57.4B + \\$125B + \\$247B + \\$187B \\\\\n= \\$616B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,indirect} \\\\\n= Damage_{env} + Loss_{growth,mil} + Loss_{capital,conflict} \\\\\n+ Cost_{psych} + Cost_{refugee} + Cost_{vet} \\\\\n= \\$100B + \\$2.72T + \\$300B + \\$232B + \\$150B + \\$200B \\\\\n= \\$3.7T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{cyber,treaty,20} \\\\\n= \\left(\\frac{Cost_{cyber}}{GDP_{global}}\\right) \\times \\bar{s}_{treaty,20} \\times \\varepsilon_{conflict}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{health,treaty,20} \\\\\n= ((1 + f_{cure,20,treaty} \\times d_{disease} \\\\\n+ \\left(\\frac{Loss_{lag}}{GDP_{global}}\\right))^{\\frac{1}{20}}) - 1\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nf_{cure,20,treaty} \\\\\n= \\min\\left(1.0, Treatments_{new,ann} \\times (3 \\times min(k_{capacity} \\times 1, k_{capacity,max}) \\\\\n+ 4 \\times min(k_{capacity} \\times 2, k_{capacity,max}) \\\\\n+ 5 \\times min(k_{capacity} \\times 5, k_{capacity,max}) \\\\\n+ 8 \\times min(k_{capacity} \\times 10, k_{capacity,max})) / N_{untreated}\\right)\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity,max} \\\\\n= \\frac{N_{willing}}{Slots_{curr}} \\\\\n= \\frac{1.08B}{1.9M} \\\\\n= 566\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{willing} \\\\\n= N_{patients} \\times Pct_{willing} \\\\\n= 2.4B \\times 44.8\\% \\\\\n= 1.08B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{lag} \\\\\n= Deaths_{lag,total} \\times (LE_{global} - Age_{death,delay}) \\times Value_{QALY} \\\\\n= 102M \\times (79 - 62) \\times \\$150K \\\\\n= \\$259T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDeaths_{lag,total} \\\\\n= Lives_{saved,annual} \\times T_{lag} \\\\\n= 12.4M \\times 8.2 \\\\\n= 102M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLives_{saved,annual} \\\\\n= \\frac{LY_{saved,annual}}{T_{ext}} \\\\\n= \\frac{149M}{12} \\\\\n= 12.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{y}_{base,20} \\\\\n= \\frac{GDP_{base,20}}{Pop_{2045}} \\\\\n= \\frac{\\$188T}{9.2B} \\\\\n= \\$20.5K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nGDP_{base,20} = GDP_{global} \\times (1 + g_{base})^{20}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{remaining} \\\\\n= LE_{global} - Age_{median} \\\\\n= 79 - 30.5 \\\\\n= 48.5\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nY_{cum,earth} \\\\\n= \\bar{y}_0 \\cdot \\frac{(1+g_{pc,base})((1+g_{pc,base})^{T_{remaining}}-1)}{g_{pc,base}}\n\\end{gathered}\n$$"
"treaty_vs_bed_nets_multiplier": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_vs_bed_nets_multiplier\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"How many times more cost-effective than bed nets (using bed net cost per DALY midpoint estimate) | Calculated from 2 inputs | ✓ High confidence | Formula: BED_NETS_COST_PER_DALY ÷ TREATY_COST_PER_DALY | Unit: x | Click to view details, calculation & sources\">50.3kx (95% CI: 23.8kx-111.7kx)</a>"
"treaty_vs_bed_nets_multiplier_latex": "$$\n\\begin{gathered}\nk_{treaty:nets} \\\\\n= \\frac{Cost_{nets}}{Cost_{treaty,DALY}} \\\\\n= \\frac{\\$89}{\\$0.00177} \\\\\n= 50{,}300\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{treaty,DALY} \\\\\n= \\frac{Cost_{campaign}}{DALYs_{max}} \\\\\n= \\frac{\\$1B}{565B} \\\\\n= \\$0.00177\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{campaign} \\\\\n= Budget_{viral,base} + Budget_{lobby,treaty} \\\\\n+ Budget_{reserve} \\\\\n= \\$250M + \\$650M + \\$100M \\\\\n= \\$1B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDALYs_{max} \\\\\n= DALYs_{global,ann} \\times Pct_{avoid,DALY} \\times T_{accel,max} \\\\\n= 2.88B \\times 92.6\\% \\times 212 \\\\\n= 565B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nT_{accel,max} = T_{accel} + T_{lag} = 204 + 8.2 = 212\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{accel} \\\\\n= T_{first,SQ} \\times \\left(1 - \\frac{1}{k_{capacity}}\\right) \\\\\n= 222 \\times \\left(1 - \\frac{1}{12.3}\\right) \\\\\n= 204\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{first,SQ} \\\\\n= T_{queue,SQ} \\times 0.5 \\\\\n= 443 \\times 0.5 \\\\\n= 222\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{queue,SQ} \\\\\n= \\frac{N_{untreated}}{Treatments_{new,ann}} \\\\\n= \\frac{6{,}650}{15} \\\\\n= 443\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$"
"treaty_vs_direct_funding_leverage": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-treaty_vs_direct_funding_leverage\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"How many times more cost-effective the treaty campaign is vs direct funding. Treaty campaign unlocks government funding at scale, avoiding need for philanthropists/NIH to directly commit equivalent amounts. Both approaches achieve same DALY timeline shift benefit. Treaty spreads cost across governments while building sustainable public funding infrastructure. | Calculated from 2 inputs | ✓ High confidence | Formula: DFDA_DIRECT_FUNDING_COST_PER_DALY ÷ TREATY_COST_PER_DALY | Unit: x | Click to view details, calculation & sources\">476x (95% CI: 329x-462x)</a>"
"treaty_vs_direct_funding_leverage_latex": "$$\n\\begin{gathered}\nLeverage_{treaty} \\\\\n= \\frac{Cost_{direct,DALY}}{Cost_{treaty,DALY}} \\\\\n= \\frac{\\$0.842}{\\$0.00177} \\\\\n= 476\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{direct,DALY} \\\\\n= \\frac{NPV_{direct}}{DALYs_{max}} \\\\\n= \\frac{\\$476B}{565B} \\\\\n= \\$0.842\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nNPV_{direct} \\\\\n= \\frac{T_{queue,dFDA}}{Funding_{dFDA,ann} \\times r_{discount}} \\\\\n= \\frac{36}{\\$21.8B \\times 3\\%} \\\\\n= \\$476B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{queue,dFDA} \\\\\n= \\frac{T_{queue,SQ}}{k_{capacity}} \\\\\n= \\frac{443}{12.3} \\\\\n= 36\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{queue,SQ} \\\\\n= \\frac{N_{untreated}}{Treatments_{new,ann}} \\\\\n= \\frac{6{,}650}{15} \\\\\n= 443\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDALYs_{max} \\\\\n= DALYs_{global,ann} \\times Pct_{avoid,DALY} \\times T_{accel,max} \\\\\n= 2.88B \\times 92.6\\% \\times 212 \\\\\n= 565B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nT_{accel,max} = T_{accel} + T_{lag} = 204 + 8.2 = 212\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{accel} \\\\\n= T_{first,SQ} \\times \\left(1 - \\frac{1}{k_{capacity}}\\right) \\\\\n= 222 \\times \\left(1 - \\frac{1}{12.3}\\right) \\\\\n= 204\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{first,SQ} \\\\\n= T_{queue,SQ} \\times 0.5 \\\\\n= 443 \\times 0.5 \\\\\n= 222\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{treaty,DALY} \\\\\n= \\frac{Cost_{campaign}}{DALYs_{max}} \\\\\n= \\frac{\\$1B}{565B} \\\\\n= \\$0.00177\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{campaign} \\\\\n= Budget_{viral,base} + Budget_{lobby,treaty} \\\\\n+ Budget_{reserve} \\\\\n= \\$250M + \\$650M + \\$100M \\\\\n= \\$1B\n\\end{gathered}\n$$"
"trial_capacity_cumulative_years_20yr": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-trial_capacity_cumulative_years_20yr\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Cumulative trial-capacity-equivalent years over 20-year period | Calculated from 1 input | ✓ High confidence | Formula: DFDA_TRIAL_CAPACITY_MULTIPLIER × 20 YEARS | Unit: years | Click to view details, calculation & sources\">247 years (95% CI: 84 years-1.23 thousand years)</a>"
"trial_capacity_cumulative_years_20yr_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-trial_capacity_cumulative_years_20yr\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Cumulative trial-capacity-equivalent years over 20-year period | Calculated from 1 input | ✓ High confidence | Formula: DFDA_TRIAL_CAPACITY_MULTIPLIER × 20 YEARS | Unit: years | Click to view details, calculation & sources\">247 (95% CI: 84-1.23 thousand)</a>"
"trial_capacity_cumulative_years_20yr_latex": "$$\n\\begin{gathered}\nCapacity_{20yr} \\\\\n= k_{capacity} \\times 20 \\\\\n= 12.3 \\times 20 \\\\\n= 247\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$"
"trial_relevant_diseases_count": "<span class=\"parameter-definition\" title=\"Consolidated count of trial-relevant diseases worth targeting (after grouping ICD-10 codes) | Unit: diseases | Core definition\">1 thousand diseases (95% CI: 800 diseases-1.2 thousand diseases)</span>"
"trial_relevant_diseases_count_nounit": "<span class=\"parameter-definition\" title=\"Consolidated count of trial-relevant diseases worth targeting (after grouping ICD-10 codes) | Unit: diseases | Core definition\">1 thousand (95% CI: 800-1.2 thousand)</span>"
"type_ii_error_cost_ratio": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-type_ii_error_cost_ratio\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Ratio of Type II error cost to Type I error benefit (harm from delay vs. harm prevented) | Calculated from 2 inputs | ~ Medium confidence | Formula: TYPE_II_COST ÷ TYPE_I_BENEFIT | Unit: ratio | Click to view details, calculation & sources\">3.07k (95% CI: 2.88k-3.12k)</a>"
"type_ii_error_cost_ratio_latex": "$$\n\\begin{gathered}\nRatio_{TypeII} \\\\\n= \\frac{DALYs_{lag}}{DALY_{TypeI}} \\\\\n= \\frac{7.94B}{2.59M} \\\\\n= 3{,}070\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nDALYs_{lag} = YLL_{lag} + YLD_{lag} = 7.07B + 873M = 7.94B\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nYLL_{lag} \\\\\n= Deaths_{lag} \\times (LE_{global} - Age_{death,delay}) \\\\\n= 416M \\times (79 - 62) \\\\\n= 7.07B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDeaths_{lag} \\\\\n= T_{lag} \\times Deaths_{disease,daily} \\times 338 \\\\\n= 8.2 \\times 150{,}000 \\times 338 \\\\\n= 416M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nYLD_{lag} \\\\\n= Deaths_{lag} \\times T_{suffering} \\times DW_{chronic} \\\\\n= 416M \\times 6 \\times 0.35 \\\\\n= 873M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDALY_{TypeI} \\\\\n= DALY_{thal} \\times 62 \\\\\n= 41{,}800 \\times 62 \\\\\n= 2.59M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDALY_{thal} \\\\\n= YLD_{thal} + YLL_{thal} \\\\\n= 13{,}000 + 28{,}800 \\\\\n= 41{,}800\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nYLD_{thal} \\\\\n= DW_{thal} \\times N_{thal,survive} \\times LE_{thal} \\\\\n= 0.4 \\times 540 \\times 60 \\\\\n= 13{,}000\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{thal,survive} \\\\\n= N_{thal,US,prevent} \\times (1 - Rate_{thal,mort}) \\\\\n= 900 \\times (1 - 40\\%) \\\\\n= 540\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{thal,US,prevent} \\\\\n= N_{thal,global} \\times Pct_{US,1960} \\\\\n= 15{,}000 \\times 6\\% \\\\\n= 900\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nYLL_{thal} \\\\\n= Deaths_{thal} \\times 80 \\\\\n= 360 \\times 80 \\\\\n= 28{,}800\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDeaths_{thal} \\\\\n= Rate_{thal,mort} \\times N_{thal,US,prevent} \\\\\n= 40\\% \\times 900 \\\\\n= 360\n\\end{gathered}\n$$"
"type_i_error_benefit_dalys": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-type_i_error_benefit_dalys\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Maximum DALYs saved by FDA preventing unsafe drugs over 62-year period 1962-2024 (extreme overestimate: one Thalidomide-scale event per year) | Calculated from 1 input | ? Low confidence | Formula: THALIDOMIDE_DALYS_PER_EVENT × 62 years | Unit: DALYs | Click to view details, calculation & sources\">2.59 million DALYs (95% CI: 1.54 million DALYs-4.16 million DALYs)</a>"
"type_i_error_benefit_dalys_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-type_i_error_benefit_dalys\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Maximum DALYs saved by FDA preventing unsafe drugs over 62-year period 1962-2024 (extreme overestimate: one Thalidomide-scale event per year) | Calculated from 1 input | ? Low confidence | Formula: THALIDOMIDE_DALYS_PER_EVENT × 62 years | Unit: DALYs | Click to view details, calculation & sources\">2.59 million (95% CI: 1.54 million-4.16 million)</a>"
"type_i_error_benefit_dalys_latex": "$$\n\\begin{gathered}\nDALY_{TypeI} \\\\\n= DALY_{thal} \\times 62 \\\\\n= 41{,}800 \\times 62 \\\\\n= 2.59M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDALY_{thal} \\\\\n= YLD_{thal} + YLL_{thal} \\\\\n= 13{,}000 + 28{,}800 \\\\\n= 41{,}800\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nYLD_{thal} \\\\\n= DW_{thal} \\times N_{thal,survive} \\times LE_{thal} \\\\\n= 0.4 \\times 540 \\times 60 \\\\\n= 13{,}000\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{thal,survive} \\\\\n= N_{thal,US,prevent} \\times (1 - Rate_{thal,mort}) \\\\\n= 900 \\times (1 - 40\\%) \\\\\n= 540\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{thal,US,prevent} \\\\\n= N_{thal,global} \\times Pct_{US,1960} \\\\\n= 15{,}000 \\times 6\\% \\\\\n= 900\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nYLL_{thal} \\\\\n= Deaths_{thal} \\times 80 \\\\\n= 360 \\times 80 \\\\\n= 28{,}800\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDeaths_{thal} \\\\\n= Rate_{thal,mort} \\times N_{thal,US,prevent} \\\\\n= 40\\% \\times 900 \\\\\n= 360\n\\end{gathered}\n$$"
"unexplored_ratio": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-unexplored_ratio\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Fraction of possible drug-disease space that remains unexplored (>99%) | Calculated from 2 inputs | ✓ High confidence | Formula: 1 - EXPLORATION_RATIO | Unit: percentage | Click to view details, calculation & sources\">99.7% (95% CI: 99%-100%)</a>"
"unexplored_ratio_latex": "$$\n\\begin{gathered}\nRatio_{unexplored} \\\\\n= 1 - \\frac{N_{tested}}{N_{combos}} \\\\\n= 1 - \\frac{32{,}500}{9.5M} \\\\\n= 99.7\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{combos} \\\\\n= N_{safe} \\times N_{diseases,trial} \\\\\n= 9{,}500 \\times 1{,}000 \\\\\n= 9.5M\n\\end{gathered}\n$$"
"us_alzheimers_annual_cost": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_alzheimers_annual_cost\" class=\"parameter-link\" data-source-ref=\"disease-cost-alzheimers-1300b\" data-source-type=\"external\" data-peer-reviewed=\"true\" data-confidence=\"high\" title=\"Annual US cost of Alzheimer's disease (direct and indirect) | ✓ High confidence | \U0001F4CA Peer-reviewed | 95% CI: [$302B, $408B] | Dist: Lognormal | Unit: USD | Click to view details, calculation & sources\">$355B (95% CI: $302B-$408B)</a>"
"us_alzheimers_annual_cost_cite": "@disease-cost-alzheimers-1300b"
"us_cancer_annual_cost": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_cancer_annual_cost\" class=\"parameter-link\" data-source-ref=\"disease-cost-cancer-1800b\" data-source-type=\"external\" data-peer-reviewed=\"true\" data-confidence=\"high\" title=\"Annual US cost of cancer (direct and indirect) | ✓ High confidence | \U0001F4CA Peer-reviewed | 95% CI: [$177B, $239B] | Dist: Lognormal | Unit: USD | Click to view details, calculation & sources\">$208B (95% CI: $177B-$239B)</a>"
"us_cancer_annual_cost_cite": "@disease-cost-cancer-1800b"
"us_chronic_disease_spending_annual": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_chronic_disease_spending_annual\" class=\"parameter-link\" data-source-ref=\"us-chronic-disease-spending\" data-source-type=\"external\" data-confidence=\"high\" title=\"US annual chronic disease spending | ✓ High confidence | 95% CI: [$3.3T, $5T] | Dist: Lognormal | Unit: USD/year | Click to view details, calculation & sources\">$4.1T (95% CI: $3.3T-$5T)</a>"
"us_chronic_disease_spending_annual_cite": "@us-chronic-disease-spending"
"us_congress_full_advocacy_cost": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_congress_full_advocacy_cost\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Upper-bound advocacy cost to match career incentives for all 535 members of Congress | Calculated from 2 inputs | ~ Medium confidence | Formula: CONGRESS_MEMBERS x POST_OFFICE_VALUE | Unit: USD | Click to view details, calculation & sources\">$5.35B</a>"
"us_congress_full_advocacy_cost_latex": "$$\n\\begin{gathered}\nCost_{US,congress} \\\\\n= N_{congress} \\times V_{post-office} \\\\\n= 535 \\times \\$10M \\\\\n= \\$5.35B\n\\end{gathered}\n$$"
"us_congress_member_count": "<span class=\"parameter-definition\" title=\"Total members of US Congress (100 senators + 435 representatives) | Unit: members | Core definition\">535 members</span>"
"us_congress_member_count_nounit": "<span class=\"parameter-definition\" title=\"Total members of US Congress (100 senators + 435 representatives) | Unit: members | Core definition\">535</span>"
"us_diabetes_annual_cost": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_diabetes_annual_cost\" class=\"parameter-link\" data-source-ref=\"disease-cost-diabetes-1500b\" data-source-type=\"external\" data-peer-reviewed=\"true\" data-confidence=\"high\" title=\"Annual US cost of diabetes (direct and indirect) | ✓ High confidence | \U0001F4CA Peer-reviewed | 95% CI: [$278B, $376B] | Dist: Lognormal | Unit: USD | Click to view details, calculation & sources\">$327B (95% CI: $278B-$376B)</a>"
"us_diabetes_annual_cost_cite": "@disease-cost-diabetes-1500b"
"us_dysfunction_premium_vs_switzerland": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_dysfunction_premium_vs_switzerland\" class=\"parameter-link\" data-source-ref=\"oecd-govt-spending\" data-source-type=\"definition\" data-confidence=\"high\" title=\"US 'dysfunction premium' vs Switzerland: US spends 3% more of GDP yet achieves 6.5 fewer years of life expectancy. This premium represents pure waste from governance inefficiency. Calculated as: 38% (US) - 35% (CH). | ✓ High confidence | Dist: Fixed | Formula: US_GOVT_SPENDING_PCT_GDP - SWITZERLAND_GOVT_SPENDING_PCT_GDP | Unit: percent | Click to view details, calculation & sources\">300%</a>"
"us_federal_spending_2024": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_federal_spending_2024\" class=\"parameter-link\" data-source-ref=\"cbo-long-term-budget-2024\" data-source-type=\"external\" data-confidence=\"high\" title=\"US federal government spending in FY2024. CBO reports outlays of $6.8T (23.9% of GDP). Includes mandatory spending, discretionary spending, and net interest ($888B). | ✓ High confidence | Dist: Fixed | Unit: USD | Click to view details, calculation & sources\">$6.8T</a>"
"us_federal_spending_2024_cite": "@cbo-long-term-budget-2024"
"us_federal_spending_per_capita": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_federal_spending_per_capita\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"US federal spending per capita. $6.8T total federal spending divided by 335M population. | Calculated from 2 inputs | ✓ High confidence | Formula: US_FEDERAL_SPENDING_2024 / US_POPULATION_2024 | Unit: USD/person | Click to view details, calculation & sources\">$20.3K (95% CI: $20K-$20.6K)</a>"
"us_federal_spending_per_capita_latex": "$$\n\\begin{gathered}\nSpend_{fed,pc} \\\\\n= \\frac{Spending_{US,fed}}{Pop_{US}} \\\\\n= \\frac{\\$6.8T}{335M} \\\\\n= \\$20.3K\n\\end{gathered}\n$$"
"us_fed_discretionary_efficiency": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_fed_discretionary_efficiency\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"US federal discretionary spending efficiency. What fraction of discretionary spending avoids direct waste (Cat 1 only: military overspend, corporate welfare, drug war, fossil/ag subsidies). ~41%. Some Cat 1 items (farm subsidies, tax expenditures) are technically mandatory/off-budget but are fungible policy choices. | Calculated from 2 inputs | ~ Medium confidence | Formula: 1 - (CAT1 / DISCRETIONARY) | Unit: percent | Click to view details, calculation & sources\">40.5% (95% CI: 23.8%-53.5%)</a>"
"us_fed_discretionary_efficiency_latex": "$$\n\\begin{gathered}\nE_{US,disc} \\\\\n= 1 - \\frac{W_{cat1}}{Spending_{US,disc}} \\\\\n= 1 - \\frac{\\$1.01T}{\\$1.7T} \\\\\n= 40.5\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nW_{cat1} \\\\\n= W_{military} + W_{corporate} + W_{drugs} + W_{fossil} \\\\\n+ W_{agriculture} \\\\\n= \\$615B + \\$181B + \\$90B + \\$50B + \\$75B \\\\\n= \\$1.01T\n\\end{gathered}\n$$"
"us_fed_discretionary_spending_2024": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_fed_discretionary_spending_2024\" class=\"parameter-link\" data-source-ref=\"cbo-long-term-budget-2024\" data-source-type=\"external\" data-confidence=\"high\" title=\"US federal discretionary spending in FY2024. Approximately $886B defense + ~$814B non-defense discretionary = ~$1.7T. Used as denominator for discretionary efficiency rating (Cat 1 waste items are discretionary/fungible). | ✓ High confidence | Dist: Fixed | Unit: USD | Click to view details, calculation & sources\">$1.7T</a>"
"us_fed_discretionary_spending_2024_cite": "@cbo-long-term-budget-2024"
"us_fed_discretionary_waste_pct": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_fed_discretionary_waste_pct\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Category 1 direct spending waste as percentage of federal discretionary spending. ~$1.01T Cat 1 waste / $1.7T discretionary = ~59%. Uses discretionary spending as denominator because Cat 1 items (military overspend, corporate welfare, drug war, fossil/ag subsidies) are fungible policy choices within discretionary budget. | Calculated from 2 inputs | ~ Medium confidence | Formula: US_GOV_WASTE_CATEGORY_1_DIRECT_SPENDING / US_FED_DISCRETIONARY_SPENDING_2024 | Unit: percent | Click to view details, calculation & sources\">59.5% (95% CI: 46.5%-76.2%)</a>"
"us_fed_discretionary_waste_pct_latex": "$$\n\\begin{gathered}\nW_{US,\\%disc} \\\\\n= \\frac{W_{cat1}}{Spending_{US,disc}} \\\\\n= \\frac{\\$1.01T}{\\$1.7T} \\\\\n= 59.5\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nW_{cat1} \\\\\n= W_{military} + W_{corporate} + W_{drugs} + W_{fossil} \\\\\n+ W_{agriculture} \\\\\n= \\$615B + \\$181B + \\$90B + \\$50B + \\$75B \\\\\n= \\$1.01T\n\\end{gathered}\n$$"
"us_gdp_2024": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_gdp_2024\" class=\"parameter-link\" data-source-ref=\"worldbank-gdp\" data-source-type=\"external\" data-confidence=\"high\" title=\"US GDP in 2024 dollars for calculating policy costs as percentage of GDP. | ✓ High confidence | Dist: Fixed | Unit: USD | Click to view details, calculation & sources\">$28.8T</a>"
"us_gdp_2024_cite": "@worldbank-gdp"
"us_governance_efficiency_gdp": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_governance_efficiency_gdp\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Total US governance efficiency: all 4 waste categories as share of GDP. 1 - ($4.9T / $28.78T) = ~83%. This broader metric captures direct spending waste, compliance burden, policy-induced GDP loss, and system inefficiency relative to total economic output. | Calculated from 2 inputs | ~ Medium confidence | Formula: 1 - (US_GOV_WASTE_TOTAL / US_GDP) | Unit: percent | Click to view details, calculation & sources\">83% (95% CI: 77.4%-87.4%)</a>"
"us_governance_efficiency_gdp_latex": "$$\n\\begin{gathered}\nE_{US,GDP} \\\\\n= 1 - \\frac{W_{total,US}}{GDP_{US}} \\\\\n= 1 - \\frac{\\$4.9T}{\\$28.8T} \\\\\n= 83\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nW_{total,US} \\\\\n= W_{raw,US} \\times \\delta_{overlap} \\\\\n= \\$4.9T \\times 1 \\\\\n= \\$4.9T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nW_{raw,US} \\\\\n= W_{health} + W_{housing} + W_{military} + W_{regulatory} \\\\\n+ W_{tax} + W_{corporate} + W_{tariffs} + W_{drugs} \\\\\n+ W_{fossil} + W_{agriculture} \\\\\n= \\$1.2T + \\$1.4T + \\$615B + \\$580B + \\$546B + \\$181B + \\$160B \\\\\n+ \\$90B + \\$50B + \\$75B \\\\\n= \\$4.9T\n\\end{gathered}\n$$"
"us_govt_spending_pct_gdp": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_govt_spending_pct_gdp\" class=\"parameter-link\" data-source-ref=\"oecd-govt-spending\" data-source-type=\"external\" data-confidence=\"high\" title=\"US total government spending as percentage of GDP (federal + state + local). OECD average is ~40%, but US gets worse outcomes for similar spending. | ✓ High confidence | Dist: Fixed | Unit: percent | Click to view details, calculation & sources\">3800%</a>"
"us_govt_spending_pct_gdp_cite": "@oecd-govt-spending"
"us_gov_waste_agricultural_subsidies": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_gov_waste_agricultural_subsidies\" class=\"parameter-link\" data-source-ref=\"ewg-farm-subsidies\" data-source-type=\"external\" data-confidence=\"high\" title=\"Deadweight loss from US agricultural subsidies. Direct subsidies ~$30B/yr but create larger distortions: overproduction, environmental damage, benefits concentrated in large farms (top 10% receive 78% of subsidies). Total welfare loss ~$75B. Textbook example of capture; very high economist consensus. [CATEGORY 1: Direct Spending] | ✓ High confidence | 95% CI: [$50B, $120B] | Dist: Lognormal (SE: $25B) | Unit: USD | Click to view details, calculation & sources\">$75B (95% CI: $50B-$120B)</a>"
"us_gov_waste_agricultural_subsidies_cite": "@ewg-farm-subsidies"
"us_gov_waste_category_1_direct_spending": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_gov_waste_category_1_direct_spending\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Category 1: Direct Federal Spending Waste. Actual federal budget allocations that could be redirected. Includes military overspend ($615B), corporate welfare ($181B), drug war ($90B), fossil fuel subsidies ($50B), and agricultural subsidies ($75B). Total: ~$1.01T annually. Solution: Budget reallocation. | Calculated from 5 inputs | ~ Medium confidence | Formula: Military + Corporate + Drug War + Fossil + Agriculture | Unit: USD | Click to view details, calculation & sources\">$1.01T (95% CI: $790B-$1.3T)</a>"
"us_gov_waste_category_1_direct_spending_latex": "$$\n\\begin{gathered}\nW_{cat1} \\\\\n= W_{military} + W_{corporate} + W_{drugs} + W_{fossil} \\\\\n+ W_{agriculture} \\\\\n= \\$615B + \\$181B + \\$90B + \\$50B + \\$75B \\\\\n= \\$1.01T\n\\end{gathered}\n$$"
"us_gov_waste_category_2_compliance": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_gov_waste_category_2_compliance\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Category 2: Compliance Burden on Private Sector. Private sector resources consumed by government-imposed compliance requirements. Includes tax compliance ($546B) and regulatory red tape ($580B). Total: ~$1.13T annually. Solution: Simplification (tax code reform, regulatory streamlining). | Calculated from 2 inputs | ~ Medium confidence | Formula: Tax Compliance + Regulatory Red Tape | Unit: USD | Click to view details, calculation & sources\">$1.13T (95% CI: $775B-$1.58T)</a>"
"us_gov_waste_category_2_compliance_latex": "$$\n\\begin{gathered}\nW_{cat2} \\\\\n= W_{tax} + W_{regulatory} \\\\\n= \\$546B + \\$580B \\\\\n= \\$1.13T\n\\end{gathered}\n$$"
"us_gov_waste_category_3_gdp_loss": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_gov_waste_category_3_gdp_loss\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Category 3: Policy-Induced GDP Loss. Economic output foregone due to policy constraints on markets. Includes housing/zoning restrictions ($1.4T) and tariffs ($160B). Total: ~$1.56T annually. Solution: Policy reform (zoning liberalization, trade policy). | Calculated from 2 inputs | ~ Medium confidence | Formula: Housing/Zoning + Tariffs | Unit: USD | Click to view details, calculation & sources\">$1.56T (95% CI: $1.05T-$2.18T)</a>"
"us_gov_waste_category_3_gdp_loss_latex": "$$\n\\begin{gathered}\nW_{cat3} \\\\\n= W_{housing} + W_{tariffs} \\\\\n= \\$1.4T + \\$160B \\\\\n= \\$1.56T\n\\end{gathered}\n$$"
"us_gov_waste_category_4_system": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_gov_waste_category_4_system\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Category 4: Total System Inefficiency. Fundamental system design failures requiring structural redesign. Currently only healthcare system inefficiency ($1.2T). Solution: System redesign using competitive market models (Singapore's catastrophic coverage + HSAs, Switzerland's regulated competition). | Calculated from 1 input | ✓ High confidence | Formula: Healthcare Inefficiency | Unit: USD | Click to view details, calculation & sources\">$1.2T (95% CI: $1T-$1.45T)</a>"
"us_gov_waste_category_4_system_latex": "$$\nW_{cat4} = W_{health} = \\$1.2T = \\$1.2T\n$$"
"us_gov_waste_corporate_welfare": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_gov_waste_corporate_welfare\" class=\"parameter-link\" data-source-ref=\"political-dysfunction-tax-paper-2025\" data-source-type=\"external\" data-confidence=\"high\" title=\"Direct US federal corporate welfare: subsidies to agriculture ($16.4B), green energy tax credits, semiconductor aid, aviation support. Agricultural subsidies are highly regressive (top 10% receive 63%). Cato Institute forensic tally. [CATEGORY 1: Direct Spending] | ✓ High confidence | 95% CI: [$150B, $220B] | Dist: Normal (SE: $20B) | Unit: USD | Click to view details, calculation & sources\">$181B (95% CI: $150B-$220B)</a>"
"us_gov_waste_corporate_welfare_cite": "@political-dysfunction-tax-paper-2025"
"us_gov_waste_drug_war": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_gov_waste_drug_war\" class=\"parameter-link\" data-source-ref=\"drugpolicyalliance2021\" data-source-type=\"external\" data-confidence=\"medium\" title=\"Annual cost of drug war: ~$41B federal drug control budget, ~$10B state/local enforcement, ~$40B incarceration and lost productivity. After 50+ years and $1T+ spent, drug use is higher than ever. [CATEGORY 1: Direct Spending] | ~ Medium confidence | 95% CI: [$60B, $150B] | Dist: Lognormal (SE: $30B) | Unit: USD | Click to view details, calculation & sources\">$90B (95% CI: $60B-$150B)</a>"
"us_gov_waste_drug_war_cite": "@drugpolicyalliance2021"
"us_gov_waste_fossil_fuel_subsidies": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_gov_waste_fossil_fuel_subsidies\" class=\"parameter-link\" data-source-ref=\"imf-fossilfuel2023\" data-source-type=\"external\" data-confidence=\"medium\" title=\"US explicit fossil fuel subsidies (direct payments, tax breaks). IMF estimates US total subsidies at $649B but ~92% is implicit (externalities). This figure includes only explicit subsidies (~$50B) for defensibility. [CATEGORY 1: Direct Spending] | ~ Medium confidence | 95% CI: [$30B, $80B] | Dist: Lognormal (SE: $15B) | Unit: USD | Click to view details, calculation & sources\">$50B (95% CI: $30B-$80B)</a>"
"us_gov_waste_fossil_fuel_subsidies_cite": "@imf-fossilfuel2023"
"us_gov_waste_healthcare_inefficiency": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_gov_waste_healthcare_inefficiency\" class=\"parameter-link\" data-source-ref=\"papanicolas2018\" data-source-type=\"external\" data-confidence=\"high\" title=\"US healthcare spending inefficiency. US spends ~$4.5T/yr (18% GDP) vs 9-11% in comparable OECD countries with similar/better outcomes. Papanicolas et al. (2018 JAMA) and multiple studies document $1-1.5T in excess spending from administrative complexity, high prices, and poor care coordination. Very high economist consensus. [CATEGORY 4: System Inefficiency] | ✓ High confidence | 95% CI: [$1T, $1.5T] | Dist: Normal (SE: $150B) | Unit: USD | Click to view details, calculation & sources\">$1.2T (95% CI: $1T-$1.5T)</a>"
"us_gov_waste_healthcare_inefficiency_cite": "@papanicolas2018"
"us_gov_waste_housing_zoning": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_gov_waste_housing_zoning\" class=\"parameter-link\" data-source-ref=\"hsieh-moretti2019\" data-source-type=\"external\" data-confidence=\"medium\" title=\"GDP loss from housing/zoning restrictions. Original Hsieh-Moretti (2019 AEJ:Macro) estimate of 36% GDP growth reduction was substantially revised by Greaney (2023). Current $1.4T represents a moderate estimate; revised lower bound implies ~$500B. [CATEGORY 3: GDP Loss] | ~ Medium confidence | 95% CI: [$500B, $2T] | Dist: Lognormal (SE: $300B) | Unit: USD | Click to view details, calculation & sources\">$1.4T (95% CI: $500B-$2T)</a>"
"us_gov_waste_housing_zoning_cite": "@hsieh-moretti2019"
"us_gov_waste_military_overspend": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_gov_waste_military_overspend\" class=\"parameter-link\" data-source-ref=\"political-dysfunction-tax-paper-2025\" data-source-type=\"external\" data-confidence=\"medium\" title=\"US military spending above 'Strict Deterrence' baseline. Current budget ~$900B supports global power projection (750+ bases). Strict Deterrence (nuclear triad $95B, Coast Guard $14B, National Guard $33B, Missile Defense $28B, Cyber $15B, defensive Navy/Air Force $100B) = ~$285B. Delta: $900B - $285B = $615B 'Hegemony Tax'. [CATEGORY 1: Direct Spending] | ~ Medium confidence | 95% CI: [$500B, $750B] | Dist: Normal (SE: $75B) | Unit: USD | Click to view details, calculation & sources\">$615B (95% CI: $500B-$750B)</a>"
"us_gov_waste_military_overspend_cite": "@political-dysfunction-tax-paper-2025"
"us_gov_waste_overlap_discount": "<span class=\"parameter-definition\" title=\"Overlap discount factor between US government waste categories. Set to 1.0 (no discount). Categories are treated as additive, recognizing that any overlap is offset by excluded categories (state/local inefficiency, implicit subsidies, behavioral effects). | Unit: ratio | Core definition\">1</span>"
"us_gov_waste_pct_gdp": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_gov_waste_pct_gdp\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"US government waste as percentage of GDP. ~$4.90T waste / $28.78T GDP = ~17%. This represents the 'dysfunction tax' that American citizens effectively pay through inefficient governance. | Calculated from 2 inputs | ~ Medium confidence | Formula: US_GOV_WASTE_TOTAL / US_GDP | Unit: percent | Click to view details, calculation & sources\">17% (95% CI: 12.6%-22.6%)</a>"
"us_gov_waste_pct_gdp_latex": "$$\n\\begin{gathered}\nW_{US,\\%GDP} \\\\\n= \\frac{W_{total,US}}{GDP_{US}} \\\\\n= \\frac{\\$4.9T}{\\$28.8T} \\\\\n= 17\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nW_{total,US} \\\\\n= W_{raw,US} \\times \\delta_{overlap} \\\\\n= \\$4.9T \\times 1 \\\\\n= \\$4.9T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nW_{raw,US} \\\\\n= W_{health} + W_{housing} + W_{military} + W_{regulatory} \\\\\n+ W_{tax} + W_{corporate} + W_{tariffs} + W_{drugs} \\\\\n+ W_{fossil} + W_{agriculture} \\\\\n= \\$1.2T + \\$1.4T + \\$615B + \\$580B + \\$546B + \\$181B + \\$160B \\\\\n+ \\$90B + \\$50B + \\$75B \\\\\n= \\$4.9T\n\\end{gathered}\n$$"
"us_gov_waste_qaly_equivalents": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_gov_waste_qaly_equivalents\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"US government waste expressed as QALY equivalents. This is an economic equivalent, NOT epidemiological health outcomes. Dividing by QALY threshold yields a measure of foregone welfare. | Calculated from 2 inputs | ~ Medium confidence | Formula: US_GOV_WASTE_TOTAL / QALY_THRESHOLD | Unit: QALYs | Click to view details, calculation & sources\">49 million QALYs (95% CI: 36.2 million QALYs-65 million QALYs)</a>"
"us_gov_waste_qaly_equivalents_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_gov_waste_qaly_equivalents\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"US government waste expressed as QALY equivalents. This is an economic equivalent, NOT epidemiological health outcomes. Dividing by QALY threshold yields a measure of foregone welfare. | Calculated from 2 inputs | ~ Medium confidence | Formula: US_GOV_WASTE_TOTAL / QALY_THRESHOLD | Unit: QALYs | Click to view details, calculation & sources\">49 million (95% CI: 36.2 million-65 million)</a>"
"us_gov_waste_qaly_equivalents_latex": "$$\n\\begin{gathered}\nW_{US,QALY} \\\\\n= \\frac{W_{total,US}}{QALY_{threshold}} \\\\\n= \\frac{\\$4.9T}{\\$100K} \\\\\n= 49M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nW_{total,US} \\\\\n= W_{raw,US} \\times \\delta_{overlap} \\\\\n= \\$4.9T \\times 1 \\\\\n= \\$4.9T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nW_{raw,US} \\\\\n= W_{health} + W_{housing} + W_{military} + W_{regulatory} \\\\\n+ W_{tax} + W_{corporate} + W_{tariffs} + W_{drugs} \\\\\n+ W_{fossil} + W_{agriculture} \\\\\n= \\$1.2T + \\$1.4T + \\$615B + \\$580B + \\$546B + \\$181B + \\$160B \\\\\n+ \\$90B + \\$50B + \\$75B \\\\\n= \\$4.9T\n\\end{gathered}\n$$"
"us_gov_waste_raw_total": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_gov_waste_raw_total\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Raw sum of US government waste components before overlap discount: healthcare ($1.2T) + housing ($1.4T) + military ($615B) + regulatory ($580B) + tax ($546B) + corporate ($181B) + tariffs ($160B) + drug war ($90B) + fossil fuel ($50B) + agriculture ($75B) = ~$4.9T raw. | Calculated from 10 inputs | ~ Medium confidence | Formula: SUM(all 10 components) | Unit: USD | Click to view details, calculation & sources\">$4.9T (95% CI: $3.62T-$6.5T)</a>"
"us_gov_waste_raw_total_latex": "$$\n\\begin{gathered}\nW_{raw,US} \\\\\n= W_{health} + W_{housing} + W_{military} + W_{regulatory} \\\\\n+ W_{tax} + W_{corporate} + W_{tariffs} + W_{drugs} \\\\\n+ W_{fossil} + W_{agriculture} \\\\\n= \\$1.2T + \\$1.4T + \\$615B + \\$580B + \\$546B + \\$181B + \\$160B \\\\\n+ \\$90B + \\$50B + \\$75B \\\\\n= \\$4.9T\n\\end{gathered}\n$$"
"us_gov_waste_recoverable": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_gov_waste_recoverable\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Recoverable capital if US improved to OECD median efficiency. Current US efficiency ~38-48%; OECD median ~75-85%. Closing to ~80% would recover approximately half the gap. | Calculated from 1 input | ? Low confidence | Formula: US_GOV_WASTE_TOTAL x 0.50 | Unit: USD | Click to view details, calculation & sources\">$2.45T (95% CI: $1.81T-$3.25T)</a>"
"us_gov_waste_recoverable_latex": "$$\n\\begin{gathered}\nW_{US,recoverable} \\\\\n= W_{total,US} \\times 0.5 \\\\\n= \\$4.9T \\times 0.5 \\\\\n= \\$2.45T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nW_{total,US} \\\\\n= W_{raw,US} \\times \\delta_{overlap} \\\\\n= \\$4.9T \\times 1 \\\\\n= \\$4.9T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nW_{raw,US} \\\\\n= W_{health} + W_{housing} + W_{military} + W_{regulatory} \\\\\n+ W_{tax} + W_{corporate} + W_{tariffs} + W_{drugs} \\\\\n+ W_{fossil} + W_{agriculture} \\\\\n= \\$1.2T + \\$1.4T + \\$615B + \\$580B + \\$546B + \\$181B + \\$160B \\\\\n+ \\$90B + \\$50B + \\$75B \\\\\n= \\$4.9T\n\\end{gathered}\n$$"
"us_gov_waste_regulatory_red_tape": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_gov_waste_regulatory_red_tape\" class=\"parameter-link\" data-source-ref=\"political-dysfunction-tax-paper-2025\" data-source-type=\"external\" data-confidence=\"medium\" title=\"Deadweight loss from US regulatory red tape (procedural friction without safety benefits). Competitive Enterprise Institute estimates total regulatory burden at $2.15T; European studies find red tape costs 0.1-4% of GDP. Conservative estimate: ~2% of US GDP = $580B. [CATEGORY 2: Compliance Burden] | ~ Medium confidence | 95% CI: [$290B, $1T] | Dist: Lognormal (SE: $200B) | Unit: USD | Click to view details, calculation & sources\">$580B (95% CI: $290B-$1T)</a>"
"us_gov_waste_regulatory_red_tape_cite": "@political-dysfunction-tax-paper-2025"
"us_gov_waste_tariffs": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_gov_waste_tariffs\" class=\"parameter-link\" data-source-ref=\"yalebudgetlab2025\" data-source-type=\"external\" data-confidence=\"medium\" title=\"Annual GDP reduction from US tariffs and retaliation. Yale Budget Lab estimates 0.6% smaller GDP in long run, equivalent to $160B annually. Trade barriers reduce efficiency and raise consumer prices. [CATEGORY 3: GDP Loss] | ~ Medium confidence | 95% CI: [$90B, $250B] | Dist: Normal (SE: $50B) | Unit: USD | Click to view details, calculation & sources\">$160B (95% CI: $90B-$250B)</a>"
"us_gov_waste_tariffs_cite": "@yalebudgetlab2025"
"us_gov_waste_tax_compliance": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_gov_waste_tax_compliance\" class=\"parameter-link\" data-source-ref=\"taxfoundation2024-compliance\" data-source-type=\"external\" data-confidence=\"high\" title=\"Annual cost of US tax code compliance: 7.9 billion hours of lost productivity ($413B) plus $133B in out-of-pocket costs. Equals nearly 2% of GDP. Could be largely eliminated with simplified tax code or return-free filing. [CATEGORY 2: Compliance Burden] | ✓ High confidence | 95% CI: [$450B, $650B] | Dist: Normal (SE: $50B) | Unit: USD | Click to view details, calculation & sources\">$546B (95% CI: $450B-$650B)</a>"
"us_gov_waste_tax_compliance_cite": "@taxfoundation2024-compliance"
"us_gov_waste_total": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_gov_waste_total\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Total annual US government waste (additive sum of components). Consolidates healthcare ($1.2T), housing ($1.4T), military ($615B), regulatory ($580B), tax ($546B), corporate ($181B), tariffs ($160B), drug war ($90B), fossil fuel ($50B), agriculture ($75B). Categories treated as additive; any overlap offset by excluded categories (state/local inefficiency, implicit subsidies, behavioral effects). ~$4.9T annually. | Calculated from 2 inputs | ~ Medium confidence | Formula: SUM(all components) | Unit: USD | Click to view details, calculation & sources\">$4.9T (95% CI: $3.62T-$6.5T)</a>"
"us_gov_waste_total_latex": "$$\n\\begin{gathered}\nW_{total,US} \\\\\n= W_{raw,US} \\times \\delta_{overlap} \\\\\n= \\$4.9T \\times 1 \\\\\n= \\$4.9T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nW_{raw,US} \\\\\n= W_{health} + W_{housing} + W_{military} + W_{regulatory} \\\\\n+ W_{tax} + W_{corporate} + W_{tariffs} + W_{drugs} \\\\\n+ W_{fossil} + W_{agriculture} \\\\\n= \\$1.2T + \\$1.4T + \\$615B + \\$580B + \\$546B + \\$181B + \\$160B \\\\\n+ \\$90B + \\$50B + \\$75B \\\\\n= \\$4.9T\n\\end{gathered}\n$$"
"us_gov_waste_vsl_equivalents": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_gov_waste_vsl_equivalents\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"US government waste expressed as VSL equivalents. This is an economic equivalent, NOT literal deaths. Dividing the efficiency gap by VSL yields a measure of foregone welfare. | Calculated from 2 inputs | ~ Medium confidence | Formula: US_GOV_WASTE_TOTAL / DOT_VSL | Unit: people | Click to view details, calculation & sources\">357 thousand people (95% CI: 264 thousand people-475 thousand people)</a>"
"us_gov_waste_vsl_equivalents_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_gov_waste_vsl_equivalents\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"US government waste expressed as VSL equivalents. This is an economic equivalent, NOT literal deaths. Dividing the efficiency gap by VSL yields a measure of foregone welfare. | Calculated from 2 inputs | ~ Medium confidence | Formula: US_GOV_WASTE_TOTAL / DOT_VSL | Unit: people | Click to view details, calculation & sources\">357 thousand (95% CI: 264 thousand-475 thousand)</a>"
"us_gov_waste_vsl_equivalents_latex": "$$\n\\begin{gathered}\nW_{US,VSL} \\\\\n= \\frac{W_{total,US}}{VSL_{DOT}} \\\\\n= \\frac{\\$4.9T}{\\$13.7M} \\\\\n= 357{,}000\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nW_{total,US} \\\\\n= W_{raw,US} \\times \\delta_{overlap} \\\\\n= \\$4.9T \\times 1 \\\\\n= \\$4.9T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nW_{raw,US} \\\\\n= W_{health} + W_{housing} + W_{military} + W_{regulatory} \\\\\n+ W_{tax} + W_{corporate} + W_{tariffs} + W_{drugs} \\\\\n+ W_{fossil} + W_{agriculture} \\\\\n= \\$1.2T + \\$1.4T + \\$615B + \\$580B + \\$546B + \\$181B + \\$160B \\\\\n+ \\$90B + \\$50B + \\$75B \\\\\n= \\$4.9T\n\\end{gathered}\n$$"
"us_gov_waste_vs_treaty_multiplier": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_gov_waste_vs_treaty_multiplier\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"How many times the US government efficiency gap could fund the 1% Treaty. The efficiency gap represents capital that could fund transformative health research many times over. | Calculated from 2 inputs | ~ Medium confidence | Formula: US_GOV_WASTE_TOTAL / TREATY_ANNUAL_FUNDING | Unit: ratio | Click to view details, calculation & sources\">180 (95% CI: 133-239)</a>"
"us_gov_waste_vs_treaty_multiplier_latex": "$$\n\\begin{gathered}\nk_{waste:treaty} \\\\\n= \\frac{W_{total,US}}{Funding_{treaty}} \\\\\n= \\frac{\\$4.9T}{\\$27.2B} \\\\\n= 180\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nW_{total,US} \\\\\n= W_{raw,US} \\times \\delta_{overlap} \\\\\n= \\$4.9T \\times 1 \\\\\n= \\$4.9T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nW_{raw,US} \\\\\n= W_{health} + W_{housing} + W_{military} + W_{regulatory} \\\\\n+ W_{tax} + W_{corporate} + W_{tariffs} + W_{drugs} \\\\\n+ W_{fossil} + W_{agriculture} \\\\\n= \\$1.2T + \\$1.4T + \\$615B + \\$580B + \\$546B + \\$181B + \\$160B \\\\\n+ \\$90B + \\$50B + \\$75B \\\\\n= \\$4.9T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nFunding_{treaty} \\\\\n= Spending_{mil} \\times Reduce_{treaty} \\\\\n= \\$2.72T \\times 1\\% \\\\\n= \\$27.2B\n\\end{gathered}\n$$"
"us_heart_disease_annual_cost": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_heart_disease_annual_cost\" class=\"parameter-link\" data-source-ref=\"disease-cost-heart-disease-2100b\" data-source-type=\"external\" data-peer-reviewed=\"true\" data-confidence=\"high\" title=\"Annual US cost of heart disease and stroke (direct and indirect) | ✓ High confidence | \U0001F4CA Peer-reviewed | 95% CI: [$309B, $417B] | Dist: Lognormal | Unit: USD | Click to view details, calculation & sources\">$363B (95% CI: $309B-$417B)</a>"
"us_heart_disease_annual_cost_cite": "@disease-cost-heart-disease-2100b"
"us_life_expectancy_1880": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_life_expectancy_1880\" class=\"parameter-link\" data-source-ref=\"life-expectancy-increase-pre-1962\" data-source-type=\"external\" data-peer-reviewed=\"true\" data-confidence=\"high\" title=\"US life expectancy in 1880 (closest available data point to 1883). | ✓ High confidence | \U0001F4CA Peer-reviewed | 95% CI: [38.9 years, 39.9 years] | Dist: Normal | Unit: years | Click to view details, calculation & sources\">39.4 years (95% CI: 38.9 years-39.9 years)</a>"
"us_life_expectancy_1880_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_life_expectancy_1880\" class=\"parameter-link\" data-source-ref=\"life-expectancy-increase-pre-1962\" data-source-type=\"external\" data-peer-reviewed=\"true\" data-confidence=\"high\" title=\"US life expectancy in 1880 (closest available data point to 1883). | ✓ High confidence | \U0001F4CA Peer-reviewed | 95% CI: [38.9 years, 39.9 years] | Dist: Normal | Unit: years | Click to view details, calculation & sources\">39.4 (95% CI: 38.9-39.9)</a>"
"us_life_expectancy_1880_cite": "@life-expectancy-increase-pre-1962"
"us_life_expectancy_1962": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_life_expectancy_1962\" class=\"parameter-link\" data-source-ref=\"life-expectancy-increase-pre-1962\" data-source-type=\"external\" data-peer-reviewed=\"true\" data-confidence=\"high\" title=\"US life expectancy in 1962 (year of Kefauver-Harris Amendments). | ✓ High confidence | \U0001F4CA Peer-reviewed | 95% CI: [69.8 years, 70.3 years] | Dist: Normal | Unit: years | Click to view details, calculation & sources\">70.1 years (95% CI: 69.8 years-70.3 years)</a>"
"us_life_expectancy_1962_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_life_expectancy_1962\" class=\"parameter-link\" data-source-ref=\"life-expectancy-increase-pre-1962\" data-source-type=\"external\" data-peer-reviewed=\"true\" data-confidence=\"high\" title=\"US life expectancy in 1962 (year of Kefauver-Harris Amendments). | ✓ High confidence | \U0001F4CA Peer-reviewed | 95% CI: [69.8 years, 70.3 years] | Dist: Normal | Unit: years | Click to view details, calculation & sources\">70.1 (95% CI: 69.8-70.3)</a>"
"us_life_expectancy_1962_cite": "@life-expectancy-increase-pre-1962"
"us_life_expectancy_2019": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_life_expectancy_2019\" class=\"parameter-link\" data-source-ref=\"post-1962-life-expectancy-slowdown\" data-source-type=\"external\" data-peer-reviewed=\"true\" data-confidence=\"high\" title=\"US life expectancy in 2019 (latest available data). | ✓ High confidence | \U0001F4CA Peer-reviewed | 95% CI: [78.6 years, 79.1 years] | Dist: Normal | Unit: years | Click to view details, calculation & sources\">78.9 years (95% CI: 78.6 years-79.1 years)</a>"
"us_life_expectancy_2019_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_life_expectancy_2019\" class=\"parameter-link\" data-source-ref=\"post-1962-life-expectancy-slowdown\" data-source-type=\"external\" data-peer-reviewed=\"true\" data-confidence=\"high\" title=\"US life expectancy in 2019 (latest available data). | ✓ High confidence | \U0001F4CA Peer-reviewed | 95% CI: [78.6 years, 79.1 years] | Dist: Normal | Unit: years | Click to view details, calculation & sources\">78.9 (95% CI: 78.6-79.1)</a>"
"us_life_expectancy_2019_cite": "@post-1962-life-expectancy-slowdown"
"us_life_expectancy_2023": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_life_expectancy_2023\" class=\"parameter-link\" data-source-ref=\"cdc-life-expectancy\" data-source-type=\"external\" data-confidence=\"high\" title=\"US life expectancy at birth (2023). Lowest among high-income OECD countries despite highest healthcare spending. | ✓ High confidence | Dist: Fixed | Unit: years | Click to view details, calculation & sources\">77.5 years</a>"
"us_life_expectancy_2023_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_life_expectancy_2023\" class=\"parameter-link\" data-source-ref=\"cdc-life-expectancy\" data-source-type=\"external\" data-confidence=\"high\" title=\"US life expectancy at birth (2023). Lowest among high-income OECD countries despite highest healthcare spending. | ✓ High confidence | Dist: Fixed | Unit: years | Click to view details, calculation & sources\">77.5</a>"
"us_life_expectancy_2023_cite": "@cdc-life-expectancy"
"us_major_diseases_total_annual_cost": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_major_diseases_total_annual_cost\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Total annual US cost of major diseases (diabetes, Alzheimer's, heart disease, cancer) | Calculated from 4 inputs | ✓ High confidence | Formula: DIABETES + ALZHEIMERS + HEART + CANCER | Unit: USD | Click to view details, calculation & sources\">$1.25T (95% CI: $1.1T-$1.42T)</a>"
"us_major_diseases_total_annual_cost_latex": "$$\n\\begin{gathered}\nCost_{disease,US} \\\\\n= Cost_{ALZ,US} + Cost_{cancer,US} + Cost_{diabetes,US} \\\\\n+ Cost_{heart,US} \\\\\n= \\$355B + \\$208B + \\$327B + \\$363B \\\\\n= \\$1.25T\n\\end{gathered}\n$$"
"us_median_household_income_2023": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_median_household_income_2023\" class=\"parameter-link\" data-source-ref=\"census-income-2023\" data-source-type=\"external\" data-confidence=\"high\" title=\"US median household income (2023). High in absolute terms but adjusted for healthcare costs and inequality, purchasing power is lower than peers. | ✓ High confidence | Dist: Fixed | Unit: USD | Click to view details, calculation & sources\">$80.6K</a>"
"us_median_household_income_2023_cite": "@census-income-2023"
"us_mental_health_cost_annual": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_mental_health_cost_annual\" class=\"parameter-link\" data-source-ref=\"mental-health-burden\" data-source-type=\"external\" data-confidence=\"high\" title=\"US mental health costs (treatment + productivity loss) | ✓ High confidence | 95% CI: [$260B, $450B] | Dist: Lognormal | Unit: USD/year | Click to view details, calculation & sources\">$350B (95% CI: $260B-$450B)</a>"
"us_mental_health_cost_annual_cite": "@mental-health-burden"
"us_military_spending_1939_annual_2024usd": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_military_spending_1939_annual_2024usd\" class=\"parameter-link\" data-source-ref=\"us-military-spending-historical-constant-dollars\" data-source-type=\"external\" data-confidence=\"high\" title=\"US military spending in 1939 (pre-WW2 baseline) in constant 2024 dollars | ✓ High confidence | Dist: Fixed | Unit: USD | Click to view details, calculation & sources\">$29B</a>"
"us_military_spending_1939_annual_2024usd_cite": "@us-military-spending-historical-constant-dollars"
"us_military_spending_1945_peak_annual_2024usd": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_military_spending_1945_peak_annual_2024usd\" class=\"parameter-link\" data-source-ref=\"us-military-spending-historical-constant-dollars\" data-source-type=\"external\" data-confidence=\"high\" title=\"US military spending at WW2 peak (1945) in constant 2024 dollars | ✓ High confidence | Dist: Fixed | Unit: USD | Click to view details, calculation & sources\">$1.42T</a>"
"us_military_spending_1945_peak_annual_2024usd_cite": "@us-military-spending-historical-constant-dollars"
"us_military_spending_1947_annual_2024usd": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_military_spending_1947_annual_2024usd\" class=\"parameter-link\" data-source-ref=\"us-military-spending-historical-constant-dollars\" data-source-type=\"external\" data-confidence=\"high\" title=\"US military spending in 1947 (post-WW2 trough, 2 years after peak) in constant 2024 dollars | ✓ High confidence | Dist: Fixed | Unit: USD | Click to view details, calculation & sources\">$176B</a>"
"us_military_spending_1947_annual_2024usd_cite": "@us-military-spending-historical-constant-dollars"
"us_military_spending_2024_annual": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_military_spending_2024_annual\" class=\"parameter-link\" data-source-ref=\"us-military-spending-historical-constant-dollars\" data-source-type=\"external\" data-confidence=\"high\" title=\"US military spending in 2024 in constant dollars | ✓ High confidence | Dist: Fixed | Unit: USD | Click to view details, calculation & sources\">$886B</a>"
"us_military_spending_2024_annual_cite": "@us-military-spending-historical-constant-dollars"
"us_military_spending_current_vs_prewar_multiplier": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_military_spending_current_vs_prewar_multiplier\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Ratio of current US military spending to pre-WW2 baseline in constant dollars ($886B / $29B) | Calculated from 2 inputs | ✓ High confidence | Formula: US_MILITARY_SPENDING_2024 / US_MILITARY_SPENDING_1939 | Unit: x | Click to view details, calculation & sources\">30.6x</a>"
"us_military_spending_current_vs_prewar_multiplier_latex": "$$\n\\begin{gathered}\nRatio_{US,2024:1939} \\\\\n= \\frac{Spending_{US,2024}}{Spending_{US,1939}} \\\\\n= \\frac{\\$886B}{\\$29B} \\\\\n= 30.6\n\\end{gathered}\n$$"
"us_military_spending_pct_gdp": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_military_spending_pct_gdp\" class=\"parameter-link\" data-source-ref=\"us-military-budget-3-5-pct-gdp\" data-source-type=\"external\" data-confidence=\"high\" title=\"US military spending as percentage of GDP (2024) | ✓ High confidence | Unit: rate | Click to view details, calculation & sources\">3.5%</a>"
"us_military_spending_pct_gdp_cite": "@us-military-budget-3-5-pct-gdp"
"us_political_effort_multiplier": "<span class=\"parameter-definition\" title=\"Fraction of campaign + lobbying spending needed to achieve policy reform. Accounts for efficiency gains from coordination, message clarity, and public interest alignment. Range 0.4-1.2 reflects uncertainty about political dynamics. | Unit: multiplier | Core definition\">0.7x (95% CI: 0.4x-1.2x)</span>"
"us_political_reform_investment_total": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_political_reform_investment_total\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Total upper-bound investment for US political reform: (campaign spending + 2 years lobbying) × effort multiplier + Congress career advocacy. Represents cost to achieve democratic parity with incumbent interests. | Calculated from 4 inputs | ? Low confidence | Formula: (CAMPAIGN + LOBBYING×2) × EFFORT_MULTIPLIER + CONGRESS_CAREER | Unit: USD | Click to view details, calculation & sources\">$25.5B (95% CI: $17.3B-$36.3B)</a>"
"us_political_reform_investment_total_latex": "$$\n\\begin{gathered}\nCost_{US,total} \\\\\n= (Cost_{campaign} \\\\\n+ Cost_{lobby} \\times 2) \\times \\mu_{effort} + Cost_{career}\n\\end{gathered}\n$$"
"us_population_2024": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_population_2024\" class=\"parameter-link\" data-source-ref=\"us-voter-population\" data-source-type=\"external\" data-confidence=\"high\" title=\"US population in 2024 | ✓ High confidence | 95% CI: [330 million people, 340 million people] | Dist: Lognormal | Unit: people | Click to view details, calculation & sources\">335 million people (95% CI: 330 million people-340 million people)</a>"
"us_population_2024_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_population_2024\" class=\"parameter-link\" data-source-ref=\"us-voter-population\" data-source-type=\"external\" data-confidence=\"high\" title=\"US population in 2024 | ✓ High confidence | 95% CI: [330 million people, 340 million people] | Dist: Lognormal | Unit: people | Click to view details, calculation & sources\">335 million (95% CI: 330 million-340 million)</a>"
"us_population_2024_cite": "@us-voter-population"
"us_senate_treaty_advocacy_cost": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_senate_treaty_advocacy_cost\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Upper-bound advocacy cost to match career incentives for 67 senators (treaty ratification threshold) | Calculated from 2 inputs | ~ Medium confidence | Formula: SENATORS_FOR_TREATY x POST_OFFICE_VALUE | Unit: USD | Click to view details, calculation & sources\">$670M</a>"
"us_senate_treaty_advocacy_cost_latex": "$$\n\\begin{gathered}\nCost_{US,senate} \\\\\n= N_{senators,treaty} \\times V_{post-office} \\\\\n= 67 \\times \\$10M \\\\\n= \\$670M\n\\end{gathered}\n$$"
"us_senators_for_treaty": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_senators_for_treaty\" class=\"parameter-link\" data-source-ref=\"us-senate-treaties\" data-source-type=\"external\" data-confidence=\"high\" title=\"Senators needed for treaty ratification (2/3 majority per Article II, Section 2) | ✓ High confidence | Dist: Fixed | Unit: senators | Click to view details, calculation & sources\">67 senators</a>"
"us_senators_for_treaty_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_senators_for_treaty\" class=\"parameter-link\" data-source-ref=\"us-senate-treaties\" data-source-type=\"external\" data-confidence=\"high\" title=\"Senators needed for treaty ratification (2/3 majority per Article II, Section 2) | ✓ High confidence | Dist: Fixed | Unit: senators | Click to view details, calculation & sources\">67</a>"
"us_senators_for_treaty_cite": "@us-senate-treaties"
"us_total_federal_campaign_spending_2024": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_total_federal_campaign_spending_2024\" class=\"parameter-link\" data-source-ref=\"fec-2024-summary\" data-source-type=\"external\" data-confidence=\"high\" title=\"Total US federal election spending in 2024 cycle including presidential, congressional, party committees, and PACs. Source: FEC Statistical Summary 2024. | ✓ High confidence | 95% CI: [$18B, $22B] | Unit: USD | Click to view details, calculation & sources\">$20B (95% CI: $18B-$22B)</a>"
"us_total_federal_campaign_spending_2024_cite": "@fec-2024-summary"
"us_total_lobbying_annual": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_total_lobbying_annual\" class=\"parameter-link\" data-source-ref=\"opensecrets-lobbying-2024\" data-source-type=\"external\" data-confidence=\"high\" title=\"Total US federal lobbying expenditure in 2024 (record year). Source: OpenSecrets. | ✓ High confidence | 95% CI: [$3.74B, $5.06B] | Unit: USD | Click to view details, calculation & sources\">$4.4B (95% CI: $3.74B-$5.06B)</a>"
"us_total_lobbying_annual_cite": "@opensecrets-lobbying-2024"
"us_vote_decisive_probability": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_vote_decisive_probability\" class=\"parameter-link\" data-source-ref=\"odds-of-decisive-vote\" data-source-type=\"external\" data-confidence=\"high\" title=\"Probability of a single vote being decisive in a US presidential election. Gelman, Silver, and Edlin (2012) estimate roughly 1 in 60 million on average, varying by state from 1 in 10 million (swing states) to 1 in 1 billion (safe states). | ✓ High confidence | Dist: Fixed | Unit: probability | Click to view details, calculation & sources\">1.67e-08 probability</a>"
"us_vote_decisive_probability_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_vote_decisive_probability\" class=\"parameter-link\" data-source-ref=\"odds-of-decisive-vote\" data-source-type=\"external\" data-confidence=\"high\" title=\"Probability of a single vote being decisive in a US presidential election. Gelman, Silver, and Edlin (2012) estimate roughly 1 in 60 million on average, varying by state from 1 in 10 million (swing states) to 1 in 1 billion (safe states). | ✓ High confidence | Dist: Fixed | Unit: probability | Click to view details, calculation & sources\">1.67e-08</a>"
"us_vote_decisive_probability_cite": "@odds-of-decisive-vote"
"us_vote_expected_value": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_vote_expected_value\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Expected monetary value of a single vote in a US presidential election. Calculated as the probability of being decisive (1 in 60M) times federal spending per capita (~$20,300). Represents the expected influence over government resource allocation from casting one vote. | Calculated from 2 inputs | ✓ High confidence | Formula: US_VOTE_DECISIVE_PROBABILITY x US_FEDERAL_SPENDING_PER_CAPITA | Unit: USD | Click to view details, calculation & sources\">$0.000338 (95% CI: $0.000334-$0.000343)</a>"
"us_vote_expected_value_latex": "$$\n\\begin{gathered}\nEV_{vote} \\\\\n= P_{decisive} \\times Spend_{fed,pc} \\\\\n= 0 \\times \\$20.3K \\\\\n= \\$0.000338\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSpend_{fed,pc} \\\\\n= \\frac{Spending_{US,fed}}{Pop_{US}} \\\\\n= \\frac{\\$6.8T}{335M} \\\\\n= \\$20.3K\n\\end{gathered}\n$$"
"us_vs_singapore_spending_gap": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_vs_singapore_spending_gap\" class=\"parameter-link\" data-source-ref=\"oecd-govt-spending\" data-source-type=\"definition\" data-confidence=\"high\" title=\"Government spending gap: US spends 23 percentage points MORE of GDP than Singapore yet achieves 6.6 fewer years of life expectancy. | ✓ High confidence | Dist: Fixed | Formula: US_SPENDING - SINGAPORE_SPENDING = 38% - 15% | Unit: percent | Click to view details, calculation & sources\">2300%</a>"
"us_vs_switzerland_life_expectancy_gap": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_vs_switzerland_life_expectancy_gap\" class=\"parameter-link\" data-source-ref=\"who-life-expectancy\" data-source-type=\"definition\" data-confidence=\"high\" title=\"Life expectancy gap: Switzerland vs US. Switzerland achieves 6.5 extra years of life while spending 3% LESS of GDP on government. | ✓ High confidence | Dist: Fixed | Formula: SWITZERLAND_LE - US_LE = 84.0 - 77.5 | Unit: years | Click to view details, calculation & sources\">6.5 years</a>"
"us_vs_switzerland_life_expectancy_gap_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_vs_switzerland_life_expectancy_gap\" class=\"parameter-link\" data-source-ref=\"who-life-expectancy\" data-source-type=\"definition\" data-confidence=\"high\" title=\"Life expectancy gap: Switzerland vs US. Switzerland achieves 6.5 extra years of life while spending 3% LESS of GDP on government. | ✓ High confidence | Dist: Fixed | Formula: SWITZERLAND_LE - US_LE = 84.0 - 77.5 | Unit: years | Click to view details, calculation & sources\">6.5</a>"
"us_vs_switzerland_spending_gap": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-us_vs_switzerland_spending_gap\" class=\"parameter-link\" data-source-ref=\"oecd-govt-spending\" data-source-type=\"definition\" data-confidence=\"high\" title=\"Government spending gap: US spends 3 percentage points MORE of GDP than Switzerland yet achieves worse outcomes. | ✓ High confidence | Dist: Fixed | Formula: US_SPENDING - SWITZERLAND_SPENDING = 38% - 35% | Unit: percent | Click to view details, calculation & sources\">300%</a>"
"valley_of_death_attrition_pct": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-valley_of_death_attrition_pct\" class=\"parameter-link\" data-source-ref=\"valley-of-death-attrition\" data-source-type=\"external\" data-confidence=\"medium\" title=\"Percentage of promising Phase 1-passed compounds abandoned primarily due to Phase 2/3 cost barriers (not scientific failure). Conservative estimate: many rare disease, natural compound, and low-margin drugs never tested. | ~ Medium confidence | 95% CI: [25%, 55%] | Dist: Uniform | Unit: percentage | Click to view details, calculation & sources\">40% (95% CI: 25%-55%)</a>"
"valley_of_death_attrition_pct_cite": "@valley-of-death-attrition"
"value_of_statistical_life": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-value_of_statistical_life\" class=\"parameter-link\" data-source-ref=\"dot-vsl-13-6m\" data-source-type=\"external\" data-confidence=\"high\" title=\"Value of Statistical Life (conservative estimate) | ✓ High confidence | 95% CI: [$5M, $15M] | Dist: Gamma (SE: $3M) | Unit: USD | Click to view details, calculation & sources\">$10M (95% CI: $5M-$15M)</a>"
"value_of_statistical_life_cite": "@dot-vsl-13-6m"
"venture_gross_return": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-venture_gross_return\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"external\" data-confidence=\"high\" title=\"Venture capital / private equity gross return (before 2-and-20 fees). Cambridge Associates US VC index 25-year pooled gross IRR. The Prize Fund charges zero fees, so gross return is the correct baseline. Lockup premium is already embedded: VC/PE IS illiquid. | ✓ High confidence | 95% CI: [13%, 22%] | Dist: Normal | Unit: percent | Click to view details, calculation & sources\">17% (95% CI: 13%-22%)</a>"
"victory_bond_annual_payout": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-victory_bond_annual_payout\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Annual VICTORY Incentive Alignment Bond payout (treaty funding × bond percentage) | Calculated from 2 inputs | ✓ High confidence | Formula: TREATY_FUNDING × BOND_PCT | Unit: USD/year | Click to view details, calculation & sources\">$2.72B</a>"
"victory_bond_annual_payout_latex": "$$\n\\begin{gathered}\nPayout_{bond,ann} \\\\\n= Funding_{treaty} \\times Pct_{bond} \\\\\n= \\$27.2B \\times 10\\% \\\\\n= \\$2.72B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nFunding_{treaty} \\\\\n= Spending_{mil} \\times Reduce_{treaty} \\\\\n= \\$2.72T \\times 1\\% \\\\\n= \\$27.2B\n\\end{gathered}\n$$"
"victory_bond_annual_return_pct": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-victory_bond_annual_return_pct\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Annual return percentage for VICTORY Incentive Alignment Bondholders | Calculated from 2 inputs | ✓ High confidence | Formula: PAYOUT ÷ CAMPAIGN_COST | Unit: rate | Click to view details, calculation & sources\">272%</a>"
"victory_bond_annual_return_pct_latex": "$$\n\\begin{gathered}\nr_{bond} \\\\\n= \\frac{Payout_{bond,ann}}{Cost_{campaign}} \\\\\n= \\frac{\\$2.72B}{\\$1B} \\\\\n= 272\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nPayout_{bond,ann} \\\\\n= Funding_{treaty} \\times Pct_{bond} \\\\\n= \\$27.2B \\times 10\\% \\\\\n= \\$2.72B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nFunding_{treaty} \\\\\n= Spending_{mil} \\times Reduce_{treaty} \\\\\n= \\$2.72T \\times 1\\% \\\\\n= \\$27.2B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{campaign} \\\\\n= Budget_{viral,base} + Budget_{lobby,treaty} \\\\\n+ Budget_{reserve} \\\\\n= \\$250M + \\$650M + \\$100M \\\\\n= \\$1B\n\\end{gathered}\n$$"
"victory_bond_funding_pct": "<span class=\"parameter-definition\" title=\"Percentage of captured dividend funding VICTORY Incentive Alignment Bonds (10%) | Unit: rate | Core definition\">10%</span>"
"vitamin_a_cost_per_daly": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-vitamin_a_cost_per_daly\" class=\"parameter-link\" data-source-ref=\"vitamin-a-cost-per-daly\" data-source-type=\"external\" data-confidence=\"medium\" title=\"Cost per DALY for vitamin A supplementation programs (India: $23-50; Africa: $40-255; wide variation by region and baseline VAD prevalence). Using India midpoint as conservative estimate. | ~ Medium confidence | Unit: USD/DALY | Click to view details, calculation & sources\">$37</a>"
"vitamin_a_cost_per_daly_cite": "@vitamin-a-cost-per-daly"
"voter_lives_saved": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-voter_lives_saved\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Lives saved attributable to each voter if the treaty passes (total lives saved ÷ 3.5% voting bloc target) | Calculated from 2 inputs | ✓ High confidence | Formula: DFDA_TRIAL_CAPACITY_PLUS_EFFICACY_LAG_LIVES_SAVED ÷ TREATY_CAMPAIGN_VOTING_BLOC_TARGET | Unit: lives | Click to view details, calculation & sources\">38.4 lives</a>"
"voter_lives_saved_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-voter_lives_saved\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Lives saved attributable to each voter if the treaty passes (total lives saved ÷ 3.5% voting bloc target) | Calculated from 2 inputs | ✓ High confidence | Formula: DFDA_TRIAL_CAPACITY_PLUS_EFFICACY_LAG_LIVES_SAVED ÷ TREATY_CAMPAIGN_VOTING_BLOC_TARGET | Unit: lives | Click to view details, calculation & sources\">38.4</a>"
"voter_lives_saved_latex": "$$\n\\begin{gathered}\nLives_{voter} \\\\\n= \\frac{Lives_{max}}{N_{voters,target}} \\\\\n= \\frac{10.7B}{280M} \\\\\n= 38.4\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLives_{max} \\\\\n= Deaths_{disease,daily} \\times T_{accel,max} \\times 338 \\\\\n= 150{,}000 \\times 212 \\times 338 \\\\\n= 10.7B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nT_{accel,max} = T_{accel} + T_{lag} = 204 + 8.2 = 212\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{accel} \\\\\n= T_{first,SQ} \\times \\left(1 - \\frac{1}{k_{capacity}}\\right) \\\\\n= 222 \\times \\left(1 - \\frac{1}{12.3}\\right) \\\\\n= 204\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{first,SQ} \\\\\n= T_{queue,SQ} \\times 0.5 \\\\\n= 443 \\times 0.5 \\\\\n= 222\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{queue,SQ} \\\\\n= \\frac{N_{untreated}}{Treatments_{new,ann}} \\\\\n= \\frac{6{,}650}{15} \\\\\n= 443\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{voters,target} \\\\\n= Pop_{global} \\times Threshold_{activism} \\\\\n= 8B \\times 3.5\\% \\\\\n= 280M\n\\end{gathered}\n$$"
"voter_suffering_hours_prevented": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-voter_suffering_hours_prevented\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Hours of suffering prevented attributable to each voter if the treaty passes (total suffering hours ÷ 3.5% voting bloc target) | Calculated from 2 inputs | ✓ High confidence | Formula: DFDA_TRIAL_CAPACITY_PLUS_EFFICACY_LAG_SUFFERING_HOURS ÷ TREATY_CAMPAIGN_VOTING_BLOC_TARGET | Unit: hours | Click to view details, calculation & sources\">6.9 million hours</a>"
"voter_suffering_hours_prevented_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-voter_suffering_hours_prevented\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Hours of suffering prevented attributable to each voter if the treaty passes (total suffering hours ÷ 3.5% voting bloc target) | Calculated from 2 inputs | ✓ High confidence | Formula: DFDA_TRIAL_CAPACITY_PLUS_EFFICACY_LAG_SUFFERING_HOURS ÷ TREATY_CAMPAIGN_VOTING_BLOC_TARGET | Unit: hours | Click to view details, calculation & sources\">6.9 million</a>"
"voter_suffering_hours_prevented_latex": "$$\n\\begin{gathered}\nHours_{suffer,voter} \\\\\n= \\frac{Hours_{suffer,max}}{N_{voters,target}} \\\\\n= \\frac{1930T}{280M} \\\\\n= 6.9M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nHours_{suffer,max} \\\\\n= DALYs_{max} \\times Pct_{YLD} \\times 8760 \\\\\n= 565B \\times 0.39 \\times 8760 \\\\\n= 1930T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDALYs_{max} \\\\\n= DALYs_{global,ann} \\times Pct_{avoid,DALY} \\times T_{accel,max} \\\\\n= 2.88B \\times 92.6\\% \\times 212 \\\\\n= 565B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nT_{accel,max} = T_{accel} + T_{lag} = 204 + 8.2 = 212\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{accel} \\\\\n= T_{first,SQ} \\times \\left(1 - \\frac{1}{k_{capacity}}\\right) \\\\\n= 222 \\times \\left(1 - \\frac{1}{12.3}\\right) \\\\\n= 204\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{first,SQ} \\\\\n= T_{queue,SQ} \\times 0.5 \\\\\n= 443 \\times 0.5 \\\\\n= 222\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{queue,SQ} \\\\\n= \\frac{N_{untreated}}{Treatments_{new,ann}} \\\\\n= \\frac{6{,}650}{15} \\\\\n= 443\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{voters,target} \\\\\n= Pop_{global} \\times Threshold_{activism} \\\\\n= 8B \\times 3.5\\% \\\\\n= 280M\n\\end{gathered}\n$$"
"vote_2_claims_payout": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-vote_2_claims_payout\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Payout for a depositor who recruits 2 verified participants (earning 2 VOTE claims). CI range reflects participation uncertainty. | Calculated from 1 input | ✓ High confidence | Formula: 2 × VOTE_TOKEN_VALUE | Unit: USD | Click to view details, calculation & sources\">$16.9K (95% CI: $701-$140K)</a>"
"vote_2_claims_payout_latex": "$$\nV_{2claims} = V_{vote} \\times 2 = \\$8.44K \\times 2 = \\$16.9K\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nV_{vote} \\\\\n= \\frac{Pool}{N_{coord}} \\\\\n= \\frac{\\$33.7T}{4B} \\\\\n= \\$8.44K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nPool \\\\\n= Assets_{invest} \\times R_{pool} \\times M_{pool} \\\\\n= \\$305T \\times 1\\% \\times 11.1 \\\\\n= \\$33.7T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nM_{pool} = (1 + r_{pool}) ^{Y_{50\\%} - Y_0}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nr_{pool} \\\\\n= r_{VC,gross} + \\Delta r_{scale} + \\alpha_{crowd} \\\\\n+ \\alpha_{home} \\\\\n= 17\\% + -2.5\\% + 2.08\\% + 0.8\\% \\\\\n= 17.4\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\alpha_{crowd} \\\\\n= S_{alloc} \\times (Acc_{crowd} - Acc_{expert}) \\\\\n= 8\\% \\times (91\\% - 65\\%) \\\\\n= 2.08\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nY_{50\\%} \\\\\n= Y_0 \\\\\n+ \\frac{\\ln\\left(0.50 / \\text{DESTRUCTIVE\\_PCT\\_GDP}\\right)}{\\ln\\left(1 + \\text{DESTRUCTIVE\\_GROWTH} - \\text{GDP\\_GROWTH}\\right)}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nr_{destruct:GDP} \\\\\n= \\frac{Cost_{destruct}}{GDP_{global}} \\\\\n= \\frac{\\$13.2T}{\\$115T} \\\\\n= 11.5\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{destruct} \\\\\n= Spending_{mil} + Cost_{cyber} \\\\\n= \\$2.72T + \\$10.5T \\\\\n= \\$13.2T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{coord} \\\\\n= Pop_{global} \\times R_{coord} \\\\\n= 8B \\times 50\\% \\\\\n= 4B\n\\end{gathered}\n$$"
"vote_token_value": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-vote_token_value\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Value of a single VOTE claim based on the modeled PRIZE pool size (investable assets × participation rate × horizon multiple). CI range reflects participation uncertainty (0.1%-10%). | Calculated from 2 inputs | ✓ High confidence | Formula: PRIZE_POOL_SIZE / GLOBAL_COORDINATION_TARGET_SUPPORTERS | Unit: USD | Click to view details, calculation & sources\">$8.44K (95% CI: $351-$69.9K)</a>"
"vote_token_value_latex": "$$\n\\begin{gathered}\nV_{vote} \\\\\n= \\frac{Pool}{N_{coord}} \\\\\n= \\frac{\\$33.7T}{4B} \\\\\n= \\$8.44K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nPool \\\\\n= Assets_{invest} \\times R_{pool} \\times M_{pool} \\\\\n= \\$305T \\times 1\\% \\times 11.1 \\\\\n= \\$33.7T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nM_{pool} = (1 + r_{pool}) ^{Y_{50\\%} - Y_0}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nr_{pool} \\\\\n= r_{VC,gross} + \\Delta r_{scale} + \\alpha_{crowd} \\\\\n+ \\alpha_{home} \\\\\n= 17\\% + -2.5\\% + 2.08\\% + 0.8\\% \\\\\n= 17.4\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\alpha_{crowd} \\\\\n= S_{alloc} \\times (Acc_{crowd} - Acc_{expert}) \\\\\n= 8\\% \\times (91\\% - 65\\%) \\\\\n= 2.08\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nY_{50\\%} \\\\\n= Y_0 \\\\\n+ \\frac{\\ln\\left(0.50 / \\text{DESTRUCTIVE\\_PCT\\_GDP}\\right)}{\\ln\\left(1 + \\text{DESTRUCTIVE\\_GROWTH} - \\text{GDP\\_GROWTH}\\right)}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nr_{destruct:GDP} \\\\\n= \\frac{Cost_{destruct}}{GDP_{global}} \\\\\n= \\frac{\\$13.2T}{\\$115T} \\\\\n= 11.5\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{destruct} \\\\\n= Spending_{mil} + Cost_{cyber} \\\\\n= \\$2.72T + \\$10.5T \\\\\n= \\$13.2T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{coord} \\\\\n= Pop_{global} \\times R_{coord} \\\\\n= 8B \\times 50\\% \\\\\n= 4B\n\\end{gathered}\n$$"
"war_avg_years_life_lost_per_death": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-war_avg_years_life_lost_per_death\" class=\"parameter-link\" data-source-ref=\"necrometrics-20th-century\" data-source-type=\"definition\" data-confidence=\"low\" title=\"Average years of life lost per war/conflict death. Based on avg age at death ~28 (soldiers ~23, civilians older) vs mid-century life expectancy ~55. | ? Low confidence | 95% CI: [20 years, 35 years] | Dist: Uniform | Unit: years | Click to view details, calculation & sources\">27 years (95% CI: 20 years-35 years)</a>"
"war_avg_years_life_lost_per_death_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-war_avg_years_life_lost_per_death\" class=\"parameter-link\" data-source-ref=\"necrometrics-20th-century\" data-source-type=\"definition\" data-confidence=\"low\" title=\"Average years of life lost per war/conflict death. Based on avg age at death ~28 (soldiers ~23, civilians older) vs mid-century life expectancy ~55. | ? Low confidence | 95% CI: [20 years, 35 years] | Dist: Uniform | Unit: years | Click to view details, calculation & sources\">27 (95% CI: 20-35)</a>"
"war_children_killed_since_1900": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-war_children_killed_since_1900\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Estimated children under 18 killed in wars, conflicts, genocides, and policy-induced famines since 1900 | Calculated from 2 inputs | ✓ High confidence | Formula: WAR_DEATHS_SINCE_1900 × WAR_CHILD_DEATH_PCT | Unit: deaths | Click to view details, calculation & sources\">102 million deaths</a>"
"war_children_killed_since_1900_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-war_children_killed_since_1900\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Estimated children under 18 killed in wars, conflicts, genocides, and policy-induced famines since 1900 | Calculated from 2 inputs | ✓ High confidence | Formula: WAR_DEATHS_SINCE_1900 × WAR_CHILD_DEATH_PCT | Unit: deaths | Click to view details, calculation & sources\">102 million</a>"
"war_children_killed_since_1900_latex": "$$\n\\begin{gathered}\nDeaths_{war,child} \\\\\n= Deaths_{war,1900} \\times Pct_{war,child} \\\\\n= 310M \\times 33\\% \\\\\n= 102M\n\\end{gathered}\n$$"
"war_child_death_pct": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-war_child_death_pct\" class=\"parameter-link\" data-source-ref=\"de-waal-famine-child-mortality-2018\" data-source-type=\"definition\" data-confidence=\"low\" title=\"Estimated share of war deaths since 1900 that were children under 18. Constructed from category-weighted estimates: combat ~3%, civilian ~35%, genocide ~33%, famine ~60%. Conservative aggregate ~33%. Sources: de Waal 2017 (famine child mortality), APA 2001 (civilian child share). | ? Low confidence | 95% CI: [25%, 40%] | Dist: Uniform | Unit: rate | Click to view details, calculation & sources\">33% (95% CI: 25%-40%)</a>"
"war_costs_cumulative_20yr_current_trajectory": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-war_costs_cumulative_20yr_current_trajectory\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Cumulative global war costs over 20 years if current spending levels continue. The price tag of the status quo trajectory. | Calculated from 1 input | ✓ High confidence | Formula: GLOBAL_ANNUAL_DIRECT_INDIRECT_WAR_COST × 20 | Unit: USD | Click to view details, calculation & sources\">$227T (95% CI: $180T-$281T)</a>"
"war_costs_cumulative_20yr_current_trajectory_latex": "$$\n\\begin{gathered}\nCost_{war,20yr} \\\\\n= Cost_{war,total} \\times 20 \\\\\n= \\$11.4T \\times 20 \\\\\n= \\$227T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,total} \\\\\n= Cost_{war,direct} + Cost_{war,indirect} \\\\\n= \\$7.66T + \\$3.7T \\\\\n= \\$11.4T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,direct} \\\\\n= Loss_{life,conflict} + Damage_{infra,total} \\\\\n+ Disruption_{trade} + Spending_{mil} \\\\\n= \\$2.45T + \\$1.88T + \\$616B + \\$2.72T \\\\\n= \\$7.66T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{life,conflict} \\\\\n= Cost_{combat,human} + Cost_{state,human} \\\\\n+ Cost_{terror,human} \\\\\n= \\$2.34T + \\$27B + \\$83B \\\\\n= \\$2.45T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{combat,human} \\\\\n= Deaths_{combat} \\times VSL \\\\\n= 234{,}000 \\times \\$10M \\\\\n= \\$2.34T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{state,human} \\\\\n= Deaths_{state} \\times VSL \\\\\n= 2{,}700 \\times \\$10M \\\\\n= \\$27B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{terror,human} \\\\\n= Deaths_{terror} \\times VSL \\\\\n= 8{,}300 \\times \\$10M \\\\\n= \\$83B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDamage_{infra,total} \\\\\n= Damage_{comms} + Damage_{edu} + Damage_{energy} \\\\\n+ Damage_{health} + Damage_{transport} + Damage_{water} \\\\\n= \\$298B + \\$234B + \\$422B + \\$166B + \\$487B + \\$268B \\\\\n= \\$1.88T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDisruption_{trade} \\\\\n= Disruption_{currency} + Disruption_{energy} \\\\\n+ Disruption_{shipping} + Disruption_{supply} \\\\\n= \\$57.4B + \\$125B + \\$247B + \\$187B \\\\\n= \\$616B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,indirect} \\\\\n= Damage_{env} + Loss_{growth,mil} + Loss_{capital,conflict} \\\\\n+ Cost_{psych} + Cost_{refugee} + Cost_{vet} \\\\\n= \\$100B + \\$2.72T + \\$300B + \\$232B + \\$150B + \\$200B \\\\\n= \\$3.7T\n\\end{gathered}\n$$"
"war_costs_saved_peace_trajectory_20yr": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-war_costs_saved_peace_trajectory_20yr\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Cumulative war costs saved over 20 years as treaty expands via IAB ratchet. Assumes war costs decline proportionally to spending cuts (e=1.0). Conservative: Pape research suggests e>1.0 due to terrorism feedback loops. | Calculated from 1 input | ✓ High confidence | Formula: GLOBAL_ANNUAL_DIRECT_INDIRECT_WAR_COST × (0.01×3 + 0.02×4 + 0.05×5 + 0.10×8) | Unit: USD | Click to view details, calculation & sources\">$13.2T (95% CI: $10.5T-$16.3T)</a>"
"war_costs_saved_peace_trajectory_20yr_latex": "$$\n\\begin{gathered}\nSavings_{war,20yr} \\\\\n= Cost_{war,total} \\times 1.16 \\\\\n= \\$11.4T \\times 1.16 \\\\\n= \\$13.2T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,total} \\\\\n= Cost_{war,direct} + Cost_{war,indirect} \\\\\n= \\$7.66T + \\$3.7T \\\\\n= \\$11.4T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,direct} \\\\\n= Loss_{life,conflict} + Damage_{infra,total} \\\\\n+ Disruption_{trade} + Spending_{mil} \\\\\n= \\$2.45T + \\$1.88T + \\$616B + \\$2.72T \\\\\n= \\$7.66T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{life,conflict} \\\\\n= Cost_{combat,human} + Cost_{state,human} \\\\\n+ Cost_{terror,human} \\\\\n= \\$2.34T + \\$27B + \\$83B \\\\\n= \\$2.45T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{combat,human} \\\\\n= Deaths_{combat} \\times VSL \\\\\n= 234{,}000 \\times \\$10M \\\\\n= \\$2.34T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{state,human} \\\\\n= Deaths_{state} \\times VSL \\\\\n= 2{,}700 \\times \\$10M \\\\\n= \\$27B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{terror,human} \\\\\n= Deaths_{terror} \\times VSL \\\\\n= 8{,}300 \\times \\$10M \\\\\n= \\$83B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDamage_{infra,total} \\\\\n= Damage_{comms} + Damage_{edu} + Damage_{energy} \\\\\n+ Damage_{health} + Damage_{transport} + Damage_{water} \\\\\n= \\$298B + \\$234B + \\$422B + \\$166B + \\$487B + \\$268B \\\\\n= \\$1.88T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDisruption_{trade} \\\\\n= Disruption_{currency} + Disruption_{energy} \\\\\n+ Disruption_{shipping} + Disruption_{supply} \\\\\n= \\$57.4B + \\$125B + \\$247B + \\$187B \\\\\n= \\$616B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,indirect} \\\\\n= Damage_{env} + Loss_{growth,mil} + Loss_{capital,conflict} \\\\\n+ Cost_{psych} + Cost_{refugee} + Cost_{vet} \\\\\n= \\$100B + \\$2.72T + \\$300B + \\$232B + \\$150B + \\$200B \\\\\n= \\$3.7T\n\\end{gathered}\n$$"
"war_counterfactual_annual_growth_boost": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-war_counterfactual_annual_growth_boost\" class=\"parameter-link\" data-source-ref=\"costa-rica-peace-dividend\" data-source-type=\"definition\" data-confidence=\"low\" title=\"Stacked annual growth boost from 8 non-overlapping war channels. Ch1: productive reallocation 0.8-1.5pp (budget + innovation merged). Ch2: preserved capital 0.2-0.4pp. Ch3: population 0.2-0.4pp. Ch4: no trade drag 0.1-0.3pp. Ch5: no environmental damage 0.1-0.2pp. Ch6: no Cold War isolation 0.1-0.3pp. Ch7: better institutions 0.1-0.3pp. Ch8: open scientific collaboration 0.05-0.15pp. Low 1.65pp, mid 2.6pp, high 3.55pp. | ? Low confidence | 95% CI: [1.65%, 3.55%] | Dist: Uniform | Unit: percentage points | Click to view details, calculation & sources\">2.6% (95% CI: 1.65%-3.55%)</a>"
"war_counterfactual_gdp_per_capita": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-war_counterfactual_gdp_per_capita\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Counterfactual global GDP per capita if all wars abolished since 1900. Actual is $14,375. Mid-range counterfactual: $333,636 (23.2x richer). 8 non-overlapping channels at +2.6pp. | Calculated from 3 inputs | ? Low confidence | Formula: GLOBAL_GDP_PER_CAPITA_1900 × (1 + ACTUAL_CAGR + WAR_COUNTERFACTUAL_ANNUAL_GROWTH_BOOST)^124 | Unit: USD/person | Click to view details, calculation & sources\">$334K (95% CI: $329K-$338K)</a>"
"war_counterfactual_gdp_per_capita_latex": "$$\n\\begin{gathered}\nGDP_{pc,peace} \\\\\n= GDP_{pc,1900} \\times \\left(1 \\\\\n+ \\left(\\frac{\\bar{y}_{0}}{GDP_{pc,1900}}\\right)^{1/124} - 1 \\\\\n+ g_{war,penalty}\\right)^{124} \\\\[0.5em]\n= \\$3.15K \\times \\left(1 + \\left(\\frac{\\$14.4K}{\\$3.15K}\\right)^{1/124} - 1 + 2.6\\%\\right)^{124} \\\\[0.5em]\n= \\$334K\n\\end{gathered}\n$$"
"war_counterfactual_income_multiple": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-war_counterfactual_income_multiple\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"How many times richer the average person would be if wars had been abolished in 1900. Counterfactual GDP per capita / actual GDP per capita. | Calculated from 2 inputs | ? Low confidence | Formula: WAR_COUNTERFACTUAL_GDP_PER_CAPITA / GLOBAL_AVG_INCOME_2025 | Unit: x | Click to view details, calculation & sources\">23.2x (95% CI: 23x-23.4x)</a>"
"war_counterfactual_income_multiple_latex": "$$\n\\begin{gathered}\nM_{war,income} \\\\\n= \\frac{GDP_{pc,peace}}{\\bar{y}_{0}} \\\\\n= \\frac{\\$334K}{\\$14.4K} \\\\\n= 23.2\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nGDP_{pc,peace} \\\\\n= GDP_{pc,1900} \\times \\left(1 \\\\\n+ \\left(\\frac{\\bar{y}_{0}}{GDP_{pc,1900}}\\right)^{1/124} - 1 \\\\\n+ g_{war,penalty}\\right)^{124} \\\\[0.5em]\n= \\$3.15K \\times \\left(1 + \\left(\\frac{\\$14.4K}{\\$3.15K}\\right)^{1/124} - 1 + 2.6\\%\\right)^{124} \\\\[0.5em]\n= \\$334K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{y}_{0} \\\\\n= \\frac{GDP_{global}}{Pop_{global}} \\\\\n= \\frac{\\$115T}{8B} \\\\\n= \\$14.4K\n\\end{gathered}\n$$"
"war_counterfactual_lost_gdp_global": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-war_counterfactual_lost_gdp_global\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Total annual global GDP lost to compound war effects since 1900. Lost GDP per capita × 8 billion people. | Calculated from 2 inputs | ? Low confidence | Formula: WAR_COUNTERFACTUAL_LOST_GDP_PER_CAPITA × GLOBAL_POPULATION_2024 | Unit: USD/year | Click to view details, calculation & sources\">$2.55 quadrillion (95% CI: $2.53 quadrillion-$2.57 quadrillion)</a>"
"war_counterfactual_lost_gdp_global_latex": "$$\n\\begin{gathered}\nGDP_{lost,total} \\\\\n= GDP_{pc,lost} \\times Pop_{global} \\\\\n= \\$319K \\times 8B \\\\\n= \\$2550T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nGDP_{pc,lost} \\\\\n= GDP_{pc,peace} - \\bar{y}_{0} \\\\\n= \\$334K - \\$14.4K \\\\\n= \\$319K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nGDP_{pc,peace} \\\\\n= GDP_{pc,1900} \\times \\left(1 \\\\\n+ \\left(\\frac{\\bar{y}_{0}}{GDP_{pc,1900}}\\right)^{1/124} - 1 \\\\\n+ g_{war,penalty}\\right)^{124} \\\\[0.5em]\n= \\$3.15K \\times \\left(1 + \\left(\\frac{\\$14.4K}{\\$3.15K}\\right)^{1/124} - 1 + 2.6\\%\\right)^{124} \\\\[0.5em]\n= \\$334K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{y}_{0} \\\\\n= \\frac{GDP_{global}}{Pop_{global}} \\\\\n= \\frac{\\$115T}{8B} \\\\\n= \\$14.4K\n\\end{gathered}\n$$"
"war_counterfactual_lost_gdp_per_capita": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-war_counterfactual_lost_gdp_per_capita\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Annual GDP per capita lost due to compound war effects since 1900 | Calculated from 2 inputs | ✓ High confidence | Formula: WAR_COUNTERFACTUAL_GDP_PER_CAPITA - GLOBAL_AVG_INCOME_2025 | Unit: USD/person/year | Click to view details, calculation & sources\">$319K (95% CI: $315K-$323K)</a>"
"war_counterfactual_lost_gdp_per_capita_latex": "$$\n\\begin{gathered}\nGDP_{pc,lost} \\\\\n= GDP_{pc,peace} - \\bar{y}_{0} \\\\\n= \\$334K - \\$14.4K \\\\\n= \\$319K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nGDP_{pc,peace} \\\\\n= GDP_{pc,1900} \\times \\left(1 \\\\\n+ \\left(\\frac{\\bar{y}_{0}}{GDP_{pc,1900}}\\right)^{1/124} - 1 \\\\\n+ g_{war,penalty}\\right)^{124} \\\\[0.5em]\n= \\$3.15K \\times \\left(1 + \\left(\\frac{\\$14.4K}{\\$3.15K}\\right)^{1/124} - 1 + 2.6\\%\\right)^{124} \\\\[0.5em]\n= \\$334K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{y}_{0} \\\\\n= \\frac{GDP_{global}}{Pop_{global}} \\\\\n= \\frac{\\$115T}{8B} \\\\\n= \\$14.4K\n\\end{gathered}\n$$"
"war_deaths_since_1900": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-war_deaths_since_1900\" class=\"parameter-link\" data-source-ref=\"leitenberg-deaths-wars-2006\" data-source-type=\"definition\" data-confidence=\"low\" title=\"Total deaths from wars, conflicts, genocides, and policy-induced famines since 1900. Built from non-overlapping categories: Rummel democide 264M (incl 21st century) + battle deaths 39M + collateral civilian deaths 30M - overlap adjustment 25M = 308M, rounded to 310M. Range: White low 200M to Rummel-high-plus-military 340M. | ? Low confidence | 95% CI: [200 million deaths, 340 million deaths] | Dist: Uniform | Unit: deaths | Click to view details, calculation & sources\">310 million deaths (95% CI: 200 million deaths-340 million deaths)</a>"
"war_deaths_since_1900_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-war_deaths_since_1900\" class=\"parameter-link\" data-source-ref=\"leitenberg-deaths-wars-2006\" data-source-type=\"definition\" data-confidence=\"low\" title=\"Total deaths from wars, conflicts, genocides, and policy-induced famines since 1900. Built from non-overlapping categories: Rummel democide 264M (incl 21st century) + battle deaths 39M + collateral civilian deaths 30M - overlap adjustment 25M = 308M, rounded to 310M. Range: White low 200M to Rummel-high-plus-military 340M. | ? Low confidence | 95% CI: [200 million deaths, 340 million deaths] | Dist: Uniform | Unit: deaths | Click to view details, calculation & sources\">310 million (95% CI: 200 million-340 million)</a>"
"war_environmental_destruction_since_1900": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-war_environmental_destruction_since_1900\" class=\"parameter-link\" data-source-ref=\"brown-costs-of-war-environmental\" data-source-type=\"definition\" data-confidence=\"low\" title=\"Cumulative environmental destruction from wars since 1900 (2024 USD). Nuclear testing, Agent Orange, Gulf War oil fires, DU contamination, Zone Rouge, military CO2 emissions, land mines. | ? Low confidence | 95% CI: [$2T, $10T] | Dist: Lognormal | Unit: USD | Click to view details, calculation & sources\">$5T (95% CI: $2T-$10T)</a>"
"war_life_years_lost_since_1900": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-war_life_years_lost_since_1900\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Total life-years stolen by war since 1900 (deaths x avg years lost per death) | Calculated from 2 inputs | ✓ High confidence | Formula: WAR_DEATHS_SINCE_1900 × WAR_AVG_YEARS_LIFE_LOST_PER_DEATH | Unit: life-years | Click to view details, calculation & sources\">8.37 billion life-years</a>"
"war_life_years_lost_since_1900_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-war_life_years_lost_since_1900\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Total life-years stolen by war since 1900 (deaths x avg years lost per death) | Calculated from 2 inputs | ✓ High confidence | Formula: WAR_DEATHS_SINCE_1900 × WAR_AVG_YEARS_LIFE_LOST_PER_DEATH | Unit: life-years | Click to view details, calculation & sources\">8.37 billion</a>"
"war_life_years_lost_since_1900_latex": "$$\n\\begin{gathered}\nYLL_{war,total} \\\\\n= Deaths_{war,1900} \\times YLL_{war} \\\\\n= 310M \\times 27 \\\\\n= 8.37B\n\\end{gathered}\n$$"
"war_property_destruction_since_1900": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-war_property_destruction_since_1900\" class=\"parameter-link\" data-source-ref=\"harrison-economics-wwii\" data-source-type=\"definition\" data-confidence=\"low\" title=\"Cumulative property and infrastructure destruction from major wars since 1900 (2024 USD). WWI ~$5T, WWII ~$23T, Korea ~$0.5T, Vietnam ~$1T, post-9/11 ~$8T, other ~$7.5T. | ? Low confidence | 95% CI: [$30T, $60T] | Dist: Uniform | Unit: USD | Click to view details, calculation & sources\">$45T (95% CI: $30T-$60T)</a>"
"war_qaly_value_lost_since_1900": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-war_qaly_value_lost_since_1900\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Economic value of life-years destroyed by war since 1900, at $150K/QALY | Calculated from 2 inputs | ✓ High confidence | Formula: WAR_LIFE_YEARS_LOST_SINCE_1900 × STANDARD_ECONOMIC_QALY_VALUE_USD | Unit: USD | Click to view details, calculation & sources\">$1.26 quadrillion (95% CI: $837T-$1.67 quadrillion)</a>"
"war_qaly_value_lost_since_1900_latex": "$$\n\\begin{gathered}\nV_{war,QALY} \\\\\n= YLL_{war,total} \\times Value_{QALY} \\\\\n= 8.37B \\times \\$150K \\\\\n= \\$1260T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nYLL_{war,total} \\\\\n= Deaths_{war,1900} \\times YLL_{war} \\\\\n= 310M \\times 27 \\\\\n= 8.37B\n\\end{gathered}\n$$"
"war_total_cost_since_1900": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-war_total_cost_since_1900\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"low\" title=\"Total historical sunk cost of war since 1900: military spending ($170T) + property destruction ($45T) + environmental ($5T) + QALY value of lives ($810T). | Calculated from 4 inputs | ? Low confidence | Formula: CUMULATIVE_MILITARY_SPENDING_FED_ERA + WAR_PROPERTY_DESTRUCTION_SINCE_1900 + WAR_ENVIRONMENTAL_DESTRUCTION_SINCE_1900 + WAR_QALY_VALUE_LOST_SINCE_1900 | Unit: USD | Click to view details, calculation & sources\">$1.48 quadrillion (95% CI: $1.05 quadrillion-$1.89 quadrillion)</a>"
"war_total_cost_since_1900_latex": "$$\n\\begin{gathered}\nC_{war,hist} \\\\\n= Spending_{mil,cum,fed} + D_{property} + D_{env} \\\\\n+ V_{war,QALY} \\\\\n= \\$170T + \\$45T + \\$5T + \\$1260T \\\\\n= \\$1480T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nV_{war,QALY} \\\\\n= YLL_{war,total} \\times Value_{QALY} \\\\\n= 8.37B \\times \\$150K \\\\\n= \\$1260T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nYLL_{war,total} \\\\\n= Deaths_{war,1900} \\times YLL_{war} \\\\\n= 310M \\times 27 \\\\\n= 8.37B\n\\end{gathered}\n$$"
"water_fluoridation_annual_benefit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-water_fluoridation_annual_benefit\" class=\"parameter-link\" data-source-ref=\"clean-water-sanitation-roi\" data-source-type=\"external\" data-confidence=\"high\" title=\"Estimated annual global economic benefit from water fluoridation programs | ✓ High confidence | Unit: USD/year | Click to view details, calculation & sources\">$800M</a>"
"water_fluoridation_annual_benefit_cite": "@clean-water-sanitation-roi"
"water_fluoridation_roi": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-water_fluoridation_roi\" class=\"parameter-link\" data-source-ref=\"clean-water-sanitation-roi\" data-source-type=\"external\" data-confidence=\"high\" title=\"Return on investment from water fluoridation programs | ✓ High confidence | Unit: ratio | Click to view details, calculation & sources\">23</a>"
"water_fluoridation_roi_cite": "@clean-water-sanitation-roi"
"who_qaly_threshold_cost_effective": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-who_qaly_threshold_cost_effective\" class=\"parameter-link\" data-source-ref=\"who-cost-effectiveness-threshold\" data-source-type=\"external\" data-confidence=\"high\" title=\"Cost-effectiveness threshold widely used in US health economics ($50,000/QALY, from 1980s dialysis costs) | ✓ High confidence | Unit: USD/QALY | Click to view details, calculation & sources\">$50K</a>"
"who_qaly_threshold_cost_effective_cite": "@who-cost-effectiveness-threshold"
"willing_trial_participants_global": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-willing_trial_participants_global\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Global chronic disease patients willing to participate in trials (2.4B × 44.8%) | Calculated from 2 inputs | ~ Medium confidence | Formula: CURRENT_DISEASE_PATIENTS_GLOBAL × PATIENT_WILLINGNESS_TRIAL_PARTICIPATION_PCT | Unit: people | Click to view details, calculation & sources\">1.08 billion people (95% CI: 843 million people-1.34 billion people)</a>"
"willing_trial_participants_global_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-willing_trial_participants_global\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"medium\" title=\"Global chronic disease patients willing to participate in trials (2.4B × 44.8%) | Calculated from 2 inputs | ~ Medium confidence | Formula: CURRENT_DISEASE_PATIENTS_GLOBAL × PATIENT_WILLINGNESS_TRIAL_PARTICIPATION_PCT | Unit: people | Click to view details, calculation & sources\">1.08 billion (95% CI: 843 million-1.34 billion)</a>"
"willing_trial_participants_global_latex": "$$\n\\begin{gathered}\nN_{willing} \\\\\n= N_{patients} \\times Pct_{willing} \\\\\n= 2.4B \\times 44.8\\% \\\\\n= 1.08B\n\\end{gathered}\n$$"
"wishocratic_crowd_alpha": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-wishocratic_crowd_alpha\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Allocation alpha from wishocratic crowd decision-making. Crowds pick correctly 91% vs experts at 65% (Surowiecki). Applied to the return spread between best/worst sectors. This is the floor: politicians (the real 'experts') are worse than 65% because they are being paid by one of the answer choices. | Calculated from 3 inputs | ✓ High confidence | Formula: (CROWD_DECISION_ACCURACY - EXPERT_DECISION_ACCURACY) × ALLOCATION_DECISION_SPREAD | Unit: percent | Click to view details, calculation & sources\">2.08% (95% CI: 1.3%-2.84%)</a>"
"wishocratic_crowd_alpha_latex": "$$\n\\begin{gathered}\n\\alpha_{crowd} \\\\\n= S_{alloc} \\times (Acc_{crowd} - Acc_{expert}) \\\\\n= 8\\% \\times (91\\% - 65\\%) \\\\\n= 2.08\\%\n\\end{gathered}\n$$"
"wishonia_disease_cure_fraction_15yr": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-wishonia_disease_cure_fraction_15yr\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Wishonia disease-cure fraction over 15 years under full implementation. Uses full trial-capacity scaling and applies an upper bound of 100% of untreated disease classes. | Calculated from 5 inputs | ✓ High confidence | Formula: min(1.0, NEW_DISEASE_FIRST_TREATMENTS_PER_YEAR * min(DFDA_TRIAL_CAPACITY_MULTIPLIER * (WISHONIA_MILITARY_REALLOCATION_PHYSICAL_MAX_SHARE / 0.01), DFDA_MAX_TRIAL_CAPACITY_MULTIPLIER_PHYSICAL) * 15 / DISEASES_WITHOUT_EFFECTIVE_TREATMENT) | Unit: rate | Click to view details, calculation & sources\">100%</a>"
"wishonia_disease_cure_fraction_15yr_latex": "$$\n\\begin{gathered}\nf_{cure,15,wish} \\\\\n= \\min\\left(1.0, Treatments_{new,ann} \\times min(k_{capacity} \\times \\left(\\frac{s_{mil,max}}{0.01}\\right), k_{capacity,max}) \\times \\frac{15}{N_{untreated}}\\right)\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\ns_{mil,max} = Cut_{WW2} = 87.6\\% = 87.6\\%\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCut_{WW2} \\\\\n= 1 - \\frac{Spending_{US,1947}}{Spending_{US,1945}} \\\\\n= 1 - \\frac{\\$176B}{\\$1.42T} \\\\\n= 87.6\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity,max} \\\\\n= \\frac{N_{willing}}{Slots_{curr}} \\\\\n= \\frac{1.08B}{1.9M} \\\\\n= 566\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{willing} \\\\\n= N_{patients} \\times Pct_{willing} \\\\\n= 2.4B \\times 44.8\\% \\\\\n= 1.08B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$"
"wishonia_disease_cure_fraction_20yr_full": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-wishonia_disease_cure_fraction_20yr_full\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Wishonia disease-cure fraction over 20 years under full implementation. Uses full trial-capacity scaling and applies an upper bound of 100% of untreated disease classes. | Calculated from 5 inputs | ✓ High confidence | Formula: min(1.0, NEW_DISEASE_FIRST_TREATMENTS_PER_YEAR × min(DFDA_TRIAL_CAPACITY_MULTIPLIER × (WISHONIA_MILITARY_REALLOCATION_PHYSICAL_MAX_SHARE ÷ 0.01), DFDA_MAX_TRIAL_CAPACITY_MULTIPLIER_PHYSICAL) × 20 ÷ DISEASES_WITHOUT_EFFECTIVE_TREATMENT) | Unit: rate | Click to view details, calculation & sources\">100%</a>"
"wishonia_disease_cure_fraction_20yr_full_latex": "$$\n\\begin{gathered}\nf_{cure,20,wish} \\\\\n= \\min\\left(1.0, Treatments_{new,ann} \\times min(k_{capacity} \\times \\left(\\frac{s_{mil,max}}{0.01}\\right), k_{capacity,max}) \\times \\frac{20}{N_{untreated}}\\right)\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\ns_{mil,max} = Cut_{WW2} = 87.6\\% = 87.6\\%\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCut_{WW2} \\\\\n= 1 - \\frac{Spending_{US,1947}}{Spending_{US,1945}} \\\\\n= 1 - \\frac{\\$176B}{\\$1.42T} \\\\\n= 87.6\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity,max} \\\\\n= \\frac{N_{willing}}{Slots_{curr}} \\\\\n= \\frac{1.08B}{1.9M} \\\\\n= 566\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{willing} \\\\\n= N_{patients} \\times Pct_{willing} \\\\\n= 2.4B \\times 44.8\\% \\\\\n= 1.08B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$"
"wishonia_extra_hale_gain_year_15": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-wishonia_extra_hale_gain_year_15\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Additional healthy years at year 15 from optimal-governance public-health improvements plus partial realization of longer-run longevity gains. This removes the implicit cap at today's life expectancy and lets Wishonia exceed it for non-arbitrary reasons. | Calculated from 4 inputs | ✓ High confidence | Formula: WISHONIA_DISEASE_CURE_FRACTION_15YR × (BEST_PRACTICE_LIFE_EXPECTANCY_GAIN + LIFE_EXTENSION_YEARS × HALE_LONGEVITY_REALIZATION_SHARE_YEAR_15) | Unit: years | Click to view details, calculation & sources\">11.1 years (95% CI: 8.46 years-20 years)</a>"
"wishonia_extra_hale_gain_year_15_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-wishonia_extra_hale_gain_year_15\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Additional healthy years at year 15 from optimal-governance public-health improvements plus partial realization of longer-run longevity gains. This removes the implicit cap at today's life expectancy and lets Wishonia exceed it for non-arbitrary reasons. | Calculated from 4 inputs | ✓ High confidence | Formula: WISHONIA_DISEASE_CURE_FRACTION_15YR × (BEST_PRACTICE_LIFE_EXPECTANCY_GAIN + LIFE_EXTENSION_YEARS × HALE_LONGEVITY_REALIZATION_SHARE_YEAR_15) | Unit: years | Click to view details, calculation & sources\">11.1 (95% CI: 8.46-20)</a>"
"wishonia_extra_hale_gain_year_15_latex": "$$\n\\begin{gathered}\n\\Delta HALE_{wish,extra,15} \\\\\n= f_{cure,15,wish} \\times (\\Delta LE_{best} \\\\\n+ T_{extend} \\times \\rho_{HALE,15})\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nf_{cure,15,wish} \\\\\n= \\min\\left(1.0, Treatments_{new,ann} \\times min(k_{capacity} \\times \\left(\\frac{s_{mil,max}}{0.01}\\right), k_{capacity,max}) \\times \\frac{15}{N_{untreated}}\\right)\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\ns_{mil,max} = Cut_{WW2} = 87.6\\% = 87.6\\%\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCut_{WW2} \\\\\n= 1 - \\frac{Spending_{US,1947}}{Spending_{US,1945}} \\\\\n= 1 - \\frac{\\$176B}{\\$1.42T} \\\\\n= 87.6\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity,max} \\\\\n= \\frac{N_{willing}}{Slots_{curr}} \\\\\n= \\frac{1.08B}{1.9M} \\\\\n= 566\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{willing} \\\\\n= N_{patients} \\times Pct_{willing} \\\\\n= 2.4B \\times 44.8\\% \\\\\n= 1.08B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\Delta LE_{best} \\\\\n= \\max\\left(LE_{CH}, LE_{SG}\\right) - LE_{global}\n\\end{gathered}\n$$"
"wishonia_hale_gain_year_15": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-wishonia_hale_gain_year_15\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"HALE improvement at year 15 under Wishonia Trajectory. It includes closing the current HALE gap, reaching today's best-practice life expectancy through optimal governance/public health, and a conservative partial realization of longer-run longevity gains. | Calculated from 4 inputs | ✓ High confidence | Formula: WISHONIA_DISEASE_CURE_FRACTION_15YR × GLOBAL_HALE_GAP + WISHONIA_EXTRA_HALE_GAIN_YEAR_15 | Unit: years | Click to view details, calculation & sources\">26.8 years (95% CI: 23.8 years-36.5 years)</a>"
"wishonia_hale_gain_year_15_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-wishonia_hale_gain_year_15\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"HALE improvement at year 15 under Wishonia Trajectory. It includes closing the current HALE gap, reaching today's best-practice life expectancy through optimal governance/public health, and a conservative partial realization of longer-run longevity gains. | Calculated from 4 inputs | ✓ High confidence | Formula: WISHONIA_DISEASE_CURE_FRACTION_15YR × GLOBAL_HALE_GAP + WISHONIA_EXTRA_HALE_GAIN_YEAR_15 | Unit: years | Click to view details, calculation & sources\">26.8 (95% CI: 23.8-36.5)</a>"
"wishonia_hale_gain_year_15_latex": "$$\n\\begin{gathered}\n\\Delta HALE_{wish,15} \\\\\n= f_{cure,15,wish} \\times \\Delta_{HALE} \\\\\n+ \\Delta HALE_{wish,extra,15}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nf_{cure,15,wish} \\\\\n= \\min\\left(1.0, Treatments_{new,ann} \\times min(k_{capacity} \\times \\left(\\frac{s_{mil,max}}{0.01}\\right), k_{capacity,max}) \\times \\frac{15}{N_{untreated}}\\right)\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\ns_{mil,max} = Cut_{WW2} = 87.6\\% = 87.6\\%\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCut_{WW2} \\\\\n= 1 - \\frac{Spending_{US,1947}}{Spending_{US,1945}} \\\\\n= 1 - \\frac{\\$176B}{\\$1.42T} \\\\\n= 87.6\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity,max} \\\\\n= \\frac{N_{willing}}{Slots_{curr}} \\\\\n= \\frac{1.08B}{1.9M} \\\\\n= 566\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{willing} \\\\\n= N_{patients} \\times Pct_{willing} \\\\\n= 2.4B \\times 44.8\\% \\\\\n= 1.08B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\Delta HALE_{wish,extra,15} \\\\\n= f_{cure,15,wish} \\times (\\Delta LE_{best} \\\\\n+ T_{extend} \\times \\rho_{HALE,15})\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\Delta LE_{best} \\\\\n= \\max\\left(LE_{CH}, LE_{SG}\\right) - LE_{global}\n\\end{gathered}\n$$"
"wishonia_hale_value_per_capita": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-wishonia_hale_value_per_capita\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Economic value of Wishonia Trajectory HALE gains at year 15 using the standard QALY value. | Calculated from 2 inputs | ✓ High confidence | Formula: WISHONIA_HALE_GAIN_YEAR_15 × STANDARD_ECONOMIC_QALY_VALUE_USD | Unit: USD/person | Click to view details, calculation & sources\">$4.02M (95% CI: $2.47M-$7.28M)</a>"
"wishonia_hale_value_per_capita_latex": "$$\n\\begin{gathered}\nValue_{HALE,wish} \\\\\n= \\Delta HALE_{wish,15} \\times Value_{QALY} \\\\\n= 26.8 \\times \\$150K \\\\\n= \\$4.02M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\Delta HALE_{wish,15} \\\\\n= f_{cure,15,wish} \\times \\Delta_{HALE} \\\\\n+ \\Delta HALE_{wish,extra,15}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nf_{cure,15,wish} \\\\\n= \\min\\left(1.0, Treatments_{new,ann} \\times min(k_{capacity} \\times \\left(\\frac{s_{mil,max}}{0.01}\\right), k_{capacity,max}) \\times \\frac{15}{N_{untreated}}\\right)\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\ns_{mil,max} = Cut_{WW2} = 87.6\\% = 87.6\\%\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCut_{WW2} \\\\\n= 1 - \\frac{Spending_{US,1947}}{Spending_{US,1945}} \\\\\n= 1 - \\frac{\\$176B}{\\$1.42T} \\\\\n= 87.6\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity,max} \\\\\n= \\frac{N_{willing}}{Slots_{curr}} \\\\\n= \\frac{1.08B}{1.9M} \\\\\n= 566\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{willing} \\\\\n= N_{patients} \\times Pct_{willing} \\\\\n= 2.4B \\times 44.8\\% \\\\\n= 1.08B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\Delta HALE_{wish,extra,15} \\\\\n= f_{cure,15,wish} \\times (\\Delta LE_{best} \\\\\n+ T_{extend} \\times \\rho_{HALE,15})\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\Delta LE_{best} \\\\\n= \\max\\left(LE_{CH}, LE_{SG}\\right) - LE_{global}\n\\end{gathered}\n$$"
"wishonia_military_reallocation_physical_max_share": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-wishonia_military_reallocation_physical_max_share\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Maximum physically demonstrated military reallocation share, anchored to post-WW2 US demobilization. | Calculated from 1 input | ✓ High confidence | Formula: POST_WW2_MILITARY_CUT_PCT | Unit: rate | Click to view details, calculation & sources\">87.6%</a>"
"wishonia_military_reallocation_physical_max_share_latex": "$$\ns_{mil,max} = Cut_{WW2} = 87.6\\% = 87.6\\%\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCut_{WW2} \\\\\n= 1 - \\frac{Spending_{US,1947}}{Spending_{US,1945}} \\\\\n= 1 - \\frac{\\$176B}{\\$1.42T} \\\\\n= 87.6\\%\n\\end{gathered}\n$$"
"wishonia_personal_upside_blend": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-wishonia_personal_upside_blend\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Blended personal upside under Wishonia Trajectory: lifetime income gain plus valued healthy-life gains. | Calculated from 2 inputs | ✓ High confidence | Formula: WISHONIA_TRAJECTORY_LIFETIME_INCOME_GAIN_PER_CAPITA + WISHONIA_HALE_VALUE_PER_CAPITA | Unit: USD/person | Click to view details, calculation & sources\">$51.2M (95% CI: $16.3M-$294M)</a>"
"wishonia_personal_upside_blend_latex": "$$\n\\begin{gathered}\nUpside_{blend,wish} \\\\\n= \\Delta Y_{lifetime,wish} + Value_{HALE,wish} \\\\\n= \\$47.2M + \\$4.02M \\\\\n= \\$51.2M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\Delta Y_{lifetime,wish} \\\\\n= Y_{cum,wish} - Y_{cum,earth} \\\\\n= \\$48.3M - \\$1.1M \\\\\n= \\$47.2M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nY_{cum,wish} \\\\\n= \\bar{y}_0 \\cdot \\frac{(1+g_{pc,wish})((1+g_{pc,wish})^{20}-1)}{g_{pc,wish}} \\\\\n+ \\bar{y}_{wish,20} \\cdot \\frac{(1+g_{pc,base})((1+g_{pc,base})^{T_{remaining}-20}-1)}{g_{pc,base}}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{y}_{0} \\\\\n= \\frac{GDP_{global}}{Pop_{global}} \\\\\n= \\frac{\\$115T}{8B} \\\\\n= \\$14.4K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{y}_{wish,20} \\\\\n= \\frac{GDP_{wish,20}}{Pop_{2045}} \\\\\n= \\frac{\\$10700T}{9.2B} \\\\\n= \\$1.16M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nGDP_{wish,20}=GDP_0(1+g_{ramp})^{3}(1+g_{full})^{17}\n$$\n\nwhere:\n\n$$\ns_{mil,max} = Cut_{WW2} = 87.6\\% = 87.6\\%\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCut_{WW2} \\\\\n= 1 - \\frac{Spending_{US,1947}}{Spending_{US,1945}} \\\\\n= 1 - \\frac{\\$176B}{\\$1.42T} \\\\\n= 87.6\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nf_{cure,20,wish} \\\\\n= \\min\\left(1.0, Treatments_{new,ann} \\times min(k_{capacity} \\times \\left(\\frac{s_{mil,max}}{0.01}\\right), k_{capacity,max}) \\times \\frac{20}{N_{untreated}}\\right)\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity,max} \\\\\n= \\frac{N_{willing}}{Slots_{curr}} \\\\\n= \\frac{1.08B}{1.9M} \\\\\n= 566\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{willing} \\\\\n= N_{patients} \\times Pct_{willing} \\\\\n= 2.4B \\times 44.8\\% \\\\\n= 1.08B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{y}_{base,20} \\\\\n= \\frac{GDP_{base,20}}{Pop_{2045}} \\\\\n= \\frac{\\$188T}{9.2B} \\\\\n= \\$20.5K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nGDP_{base,20} = GDP_{global} \\times (1 + g_{base})^{20}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{remaining} \\\\\n= LE_{global} - Age_{median} \\\\\n= 79 - 30.5 \\\\\n= 48.5\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nY_{cum,earth} \\\\\n= \\bar{y}_0 \\cdot \\frac{(1+g_{pc,base})((1+g_{pc,base})^{T_{remaining}}-1)}{g_{pc,base}}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nValue_{HALE,wish} \\\\\n= \\Delta HALE_{wish,15} \\times Value_{QALY} \\\\\n= 26.8 \\times \\$150K \\\\\n= \\$4.02M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\Delta HALE_{wish,15} \\\\\n= f_{cure,15,wish} \\times \\Delta_{HALE} \\\\\n+ \\Delta HALE_{wish,extra,15}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nf_{cure,15,wish} \\\\\n= \\min\\left(1.0, Treatments_{new,ann} \\times min(k_{capacity} \\times \\left(\\frac{s_{mil,max}}{0.01}\\right), k_{capacity,max}) \\times \\frac{15}{N_{untreated}}\\right)\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\Delta HALE_{wish,extra,15} \\\\\n= f_{cure,15,wish} \\times (\\Delta LE_{best} \\\\\n+ T_{extend} \\times \\rho_{HALE,15})\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\Delta LE_{best} \\\\\n= \\max\\left(LE_{CH}, LE_{SG}\\right) - LE_{global}\n\\end{gathered}\n$$"
"wishonia_projected_hale_year_15": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-wishonia_projected_hale_year_15\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Projected global HALE at year 15 under Wishonia Trajectory. Full implementation closes the entire disease gap, pushing HALE toward life expectancy. | Calculated from 2 inputs | ✓ High confidence | Formula: GLOBAL_HALE_CURRENT + WISHONIA_HALE_GAIN_YEAR_15 | Unit: years | Click to view details, calculation & sources\">90.1 years (95% CI: 84.9 years-102 years)</a>"
"wishonia_projected_hale_year_15_nounit": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-wishonia_projected_hale_year_15\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Projected global HALE at year 15 under Wishonia Trajectory. Full implementation closes the entire disease gap, pushing HALE toward life expectancy. | Calculated from 2 inputs | ✓ High confidence | Formula: GLOBAL_HALE_CURRENT + WISHONIA_HALE_GAIN_YEAR_15 | Unit: years | Click to view details, calculation & sources\">90.1 (95% CI: 84.9-102)</a>"
"wishonia_projected_hale_year_15_latex": "$$\n\\begin{gathered}\nHALE_{wish,15} \\\\\n= HALE_{0} + \\Delta HALE_{wish,15} \\\\\n= 63.3 + 26.8 \\\\\n= 90.1\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\Delta HALE_{wish,15} \\\\\n= f_{cure,15,wish} \\times \\Delta_{HALE} \\\\\n+ \\Delta HALE_{wish,extra,15}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nf_{cure,15,wish} \\\\\n= \\min\\left(1.0, Treatments_{new,ann} \\times min(k_{capacity} \\times \\left(\\frac{s_{mil,max}}{0.01}\\right), k_{capacity,max}) \\times \\frac{15}{N_{untreated}}\\right)\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\ns_{mil,max} = Cut_{WW2} = 87.6\\% = 87.6\\%\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCut_{WW2} \\\\\n= 1 - \\frac{Spending_{US,1947}}{Spending_{US,1945}} \\\\\n= 1 - \\frac{\\$176B}{\\$1.42T} \\\\\n= 87.6\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity,max} \\\\\n= \\frac{N_{willing}}{Slots_{curr}} \\\\\n= \\frac{1.08B}{1.9M} \\\\\n= 566\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{willing} \\\\\n= N_{patients} \\times Pct_{willing} \\\\\n= 2.4B \\times 44.8\\% \\\\\n= 1.08B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\Delta HALE_{wish,extra,15} \\\\\n= f_{cure,15,wish} \\times (\\Delta LE_{best} \\\\\n+ T_{extend} \\times \\rho_{HALE,15})\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\Delta LE_{best} \\\\\n= \\max\\left(LE_{CH}, LE_{SG}\\right) - LE_{global}\n\\end{gathered}\n$$"
"wishonia_trajectory_avg_income_year_15": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-wishonia_trajectory_avg_income_year_15\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Average income (GDP per capita) at year 15 under the Wishonia Trajectory. | Calculated from 2 inputs | ✓ High confidence | Formula: WISHONIA_TRAJECTORY_GDP_YEAR_15 / GLOBAL_POPULATION_2040_PROJECTED | Unit: USD | Click to view details, calculation & sources\">$504K (95% CI: $234K-$1.87M)</a>"
"wishonia_trajectory_avg_income_year_15_latex": "$$\n\\begin{gathered}\n\\bar{y}_{wish,15} \\\\\n= \\frac{GDP_{wish,15}}{Pop_{2040}} \\\\\n= \\frac{\\$4480T}{8.9B} \\\\\n= \\$504K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nGDP_{wish,15}=GDP_0(1+g_{ramp})^{3}(1+g_{full})^{12}\n$$\n\nwhere:\n\n$$\ns_{mil,max} = Cut_{WW2} = 87.6\\% = 87.6\\%\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCut_{WW2} \\\\\n= 1 - \\frac{Spending_{US,1947}}{Spending_{US,1945}} \\\\\n= 1 - \\frac{\\$176B}{\\$1.42T} \\\\\n= 87.6\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nf_{cure,15,wish} \\\\\n= \\min\\left(1.0, Treatments_{new,ann} \\times min(k_{capacity} \\times \\left(\\frac{s_{mil,max}}{0.01}\\right), k_{capacity,max}) \\times \\frac{15}{N_{untreated}}\\right)\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity,max} \\\\\n= \\frac{N_{willing}}{Slots_{curr}} \\\\\n= \\frac{1.08B}{1.9M} \\\\\n= 566\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{willing} \\\\\n= N_{patients} \\times Pct_{willing} \\\\\n= 2.4B \\times 44.8\\% \\\\\n= 1.08B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$"
"wishonia_trajectory_avg_income_year_20": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-wishonia_trajectory_avg_income_year_20\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Average income (GDP per capita) at year 20 under the Wishonia Trajectory. | Calculated from 2 inputs | ✓ High confidence | Formula: WISHONIA_TRAJECTORY_GDP_YEAR_20 / GLOBAL_POPULATION_2045_PROJECTED | Unit: USD | Click to view details, calculation & sources\">$1.16M (95% CI: $395K-$6.22M)</a>"
"wishonia_trajectory_avg_income_year_20_latex": "$$\n\\begin{gathered}\n\\bar{y}_{wish,20} \\\\\n= \\frac{GDP_{wish,20}}{Pop_{2045}} \\\\\n= \\frac{\\$10700T}{9.2B} \\\\\n= \\$1.16M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nGDP_{wish,20}=GDP_0(1+g_{ramp})^{3}(1+g_{full})^{17}\n$$\n\nwhere:\n\n$$\ns_{mil,max} = Cut_{WW2} = 87.6\\% = 87.6\\%\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCut_{WW2} \\\\\n= 1 - \\frac{Spending_{US,1947}}{Spending_{US,1945}} \\\\\n= 1 - \\frac{\\$176B}{\\$1.42T} \\\\\n= 87.6\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nf_{cure,20,wish} \\\\\n= \\min\\left(1.0, Treatments_{new,ann} \\times min(k_{capacity} \\times \\left(\\frac{s_{mil,max}}{0.01}\\right), k_{capacity,max}) \\times \\frac{20}{N_{untreated}}\\right)\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity,max} \\\\\n= \\frac{N_{willing}}{Slots_{curr}} \\\\\n= \\frac{1.08B}{1.9M} \\\\\n= 566\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{willing} \\\\\n= N_{patients} \\times Pct_{willing} \\\\\n= 2.4B \\times 44.8\\% \\\\\n= 1.08B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$"
"wishonia_trajectory_cagr_year_20": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-wishonia_trajectory_cagr_year_20\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Compound annual growth rate implied by Wishonia Trajectory GDP trajectory over 20 years. | Calculated from 2 inputs | ✓ High confidence | Formula: (WISHONIA_TRAJECTORY_GDP_YEAR_20 ÷ GLOBAL_GDP_2025)^(1/20) - 1 | Unit: rate | Click to view details, calculation & sources\">25.4% (95% CI: 18.8%-36.4%)</a>"
"wishonia_trajectory_cagr_year_20_latex": "$$\n\\begin{gathered}\ng_{wish,CAGR} \\\\\n= \\left(\\frac{GDP_{wish,20}}{GDP_{global}}\\right)^{\\frac{1}{20}} - 1\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nGDP_{wish,20}=GDP_0(1+g_{ramp})^{3}(1+g_{full})^{17}\n$$\n\nwhere:\n\n$$\ns_{mil,max} = Cut_{WW2} = 87.6\\% = 87.6\\%\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCut_{WW2} \\\\\n= 1 - \\frac{Spending_{US,1947}}{Spending_{US,1945}} \\\\\n= 1 - \\frac{\\$176B}{\\$1.42T} \\\\\n= 87.6\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nf_{cure,20,wish} \\\\\n= \\min\\left(1.0, Treatments_{new,ann} \\times min(k_{capacity} \\times \\left(\\frac{s_{mil,max}}{0.01}\\right), k_{capacity,max}) \\times \\frac{20}{N_{untreated}}\\right)\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity,max} \\\\\n= \\frac{N_{willing}}{Slots_{curr}} \\\\\n= \\frac{1.08B}{1.9M} \\\\\n= 566\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{willing} \\\\\n= N_{patients} \\times Pct_{willing} \\\\\n= 2.4B \\times 44.8\\% \\\\\n= 1.08B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$"
"wishonia_trajectory_cumulative_lifetime_income": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-wishonia_trajectory_cumulative_lifetime_income\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Cumulative per-capita income over an average remaining lifespan under Wishonia Trajectory. Uses implied per-capita CAGR for years 1-20, then current-trajectory per-capita growth from the year-20 level. Conservative: assumes no further acceleration beyond year 20. | Calculated from 4 inputs | ✓ High confidence | Formula: Phase 1: y0*(1+g_pc,wish)*((1+g_pc,wish)^20-1)/g_pc,wish + Phase 2: y20*(1+g_pc,base)*((1+g_pc,base)^(T-20)-1)/g_pc,base | Unit: USD | Click to view details, calculation & sources\">$48.3M (95% CI: $14.9M-$288M)</a>"
"wishonia_trajectory_cumulative_lifetime_income_latex": "$$\n\\begin{gathered}\nY_{cum,wish} \\\\\n= \\bar{y}_0 \\cdot \\frac{(1+g_{pc,wish})((1+g_{pc,wish})^{20}-1)}{g_{pc,wish}} \\\\\n+ \\bar{y}_{wish,20} \\cdot \\frac{(1+g_{pc,base})((1+g_{pc,base})^{T_{remaining}-20}-1)}{g_{pc,base}}\n\\end{gathered}\n$$"
"wishonia_trajectory_gdp_vs_current_trajectory_multiplier_year_15": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-wishonia_trajectory_gdp_vs_current_trajectory_multiplier_year_15\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Wishonia Trajectory GDP at year 15 as a multiple of current trajectory GDP at year 15. | Calculated from 2 inputs | ✓ High confidence | Formula: WISHONIA_TRAJECTORY_GDP_YEAR_15 / CURRENT_TRAJECTORY_GDP_YEAR_15 | Unit: x | Click to view details, calculation & sources\">26.9x (95% CI: 12.5x-100x)</a>"
"wishonia_trajectory_gdp_vs_current_trajectory_multiplier_year_15_latex": "$$\n\\begin{gathered}\nk_{wish:base,15} \\\\\n= \\frac{GDP_{wish,15}}{GDP_{base,15}} \\\\\n= \\frac{\\$4480T}{\\$167T} \\\\\n= 26.9\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nGDP_{wish,15}=GDP_0(1+g_{ramp})^{3}(1+g_{full})^{12}\n$$\n\nwhere:\n\n$$\ns_{mil,max} = Cut_{WW2} = 87.6\\% = 87.6\\%\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCut_{WW2} \\\\\n= 1 - \\frac{Spending_{US,1947}}{Spending_{US,1945}} \\\\\n= 1 - \\frac{\\$176B}{\\$1.42T} \\\\\n= 87.6\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nf_{cure,15,wish} \\\\\n= \\min\\left(1.0, Treatments_{new,ann} \\times min(k_{capacity} \\times \\left(\\frac{s_{mil,max}}{0.01}\\right), k_{capacity,max}) \\times \\frac{15}{N_{untreated}}\\right)\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity,max} \\\\\n= \\frac{N_{willing}}{Slots_{curr}} \\\\\n= \\frac{1.08B}{1.9M} \\\\\n= 566\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{willing} \\\\\n= N_{patients} \\times Pct_{willing} \\\\\n= 2.4B \\times 44.8\\% \\\\\n= 1.08B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nGDP_{base,15} = GDP_{global} \\times (1 + g_{base})^{15}\n$$"
"wishonia_trajectory_gdp_vs_current_trajectory_multiplier_year_20": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-wishonia_trajectory_gdp_vs_current_trajectory_multiplier_year_20\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Wishonia Trajectory GDP at year 20 as a multiple of current trajectory GDP at year 20. | Calculated from 2 inputs | ✓ High confidence | Formula: WISHONIA_TRAJECTORY_GDP_YEAR_20 ÷ CURRENT_TRAJECTORY_GDP_YEAR_20 | Unit: x | Click to view details, calculation & sources\">56.7x (95% CI: 19.3x-304x)</a>"
"wishonia_trajectory_gdp_vs_current_trajectory_multiplier_year_20_latex": "$$\n\\begin{gathered}\nk_{wish:base,20} \\\\\n= \\frac{GDP_{wish,20}}{GDP_{base,20}} \\\\\n= \\frac{\\$10700T}{\\$188T} \\\\\n= 56.7\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nGDP_{wish,20}=GDP_0(1+g_{ramp})^{3}(1+g_{full})^{17}\n$$\n\nwhere:\n\n$$\ns_{mil,max} = Cut_{WW2} = 87.6\\% = 87.6\\%\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCut_{WW2} \\\\\n= 1 - \\frac{Spending_{US,1947}}{Spending_{US,1945}} \\\\\n= 1 - \\frac{\\$176B}{\\$1.42T} \\\\\n= 87.6\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nf_{cure,20,wish} \\\\\n= \\min\\left(1.0, Treatments_{new,ann} \\times min(k_{capacity} \\times \\left(\\frac{s_{mil,max}}{0.01}\\right), k_{capacity,max}) \\times \\frac{20}{N_{untreated}}\\right)\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity,max} \\\\\n= \\frac{N_{willing}}{Slots_{curr}} \\\\\n= \\frac{1.08B}{1.9M} \\\\\n= 566\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{willing} \\\\\n= N_{patients} \\times Pct_{willing} \\\\\n= 2.4B \\times 44.8\\% \\\\\n= 1.08B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nGDP_{base,20} = GDP_{global} \\times (1 + g_{base})^{20}\n$$"
"wishonia_trajectory_gdp_year_15": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-wishonia_trajectory_gdp_year_15\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Projected global GDP at year 15 under the Wishonia Trajectory. Applies all Wishonia policy channels including military reallocation, disease-burden recovery, and Political Dysfunction Tax elimination. 3-year ramp at 50% intensity + 12 years full. | Calculated from 12 inputs | ✓ High confidence | Formula: GLOBAL_GDP_2025 * (1 + g_ramp)^3 * (1 + g_full)^12, where years 1-3 use 50% of military and non-health reallocation intensity, and years 4-15 use 100%; both include disease-burden recovery | Unit: USD | Click to view details, calculation & sources\">$4.48 quadrillion (95% CI: $2.08 quadrillion-$16.7 quadrillion)</a>"
"wishonia_trajectory_gdp_year_15_latex": "$$\nGDP_{wish,15}=GDP_0(1+g_{ramp})^{3}(1+g_{full})^{12}\n$$"
"wishonia_trajectory_gdp_year_20": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-wishonia_trajectory_gdp_year_20\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Projected global GDP at year 20 under the Wishonia Trajectory. Model applies all Wishonia policy channels and redirects the full Political Dysfunction Tax non-health opportunity pool to highest-marginal-value uses. Health recovery is modeled separately through disease burden removal to avoid overlap. Military and non-health reallocation effects are ramped at 50% intensity for the first 3 years, then 100% for years 4-20, reflecting implementation lag. Military reallocation uses a physically demonstrated upper bound (post-WW2 demobilization) rather than an arbitrary policy cap. | Calculated from 12 inputs | ✓ High confidence | Formula: GLOBAL_GDP_2025 × (1 + g_ramp)^3 × (1 + g_full)^17, where years 1-3 use 50% of military and non-health reallocation intensity, and years 4-20 use 100%; both include disease-burden recovery | Unit: USD | Click to view details, calculation & sources\">$10.7 quadrillion (95% CI: $3.64 quadrillion-$57.2 quadrillion)</a>"
"wishonia_trajectory_gdp_year_20_latex": "$$\nGDP_{wish,20}=GDP_0(1+g_{ramp})^{3}(1+g_{full})^{17}\n$$"
"wishonia_trajectory_lifetime_income_gain_per_capita": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-wishonia_trajectory_lifetime_income_gain_per_capita\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Lifetime per-capita income gain from Wishonia Trajectory vs current trajectory. Cumulative Wishonia income minus cumulative current trajectory income over average remaining lifespan. | Calculated from 2 inputs | ✓ High confidence | Formula: WISHONIA_TRAJECTORY_CUMULATIVE_LIFETIME_INCOME - CURRENT_TRAJECTORY_CUMULATIVE_LIFETIME_INCOME | Unit: USD | Click to view details, calculation & sources\">$47.2M (95% CI: $13.9M-$286M)</a>"
"wishonia_trajectory_lifetime_income_gain_per_capita_latex": "$$\n\\begin{gathered}\n\\Delta Y_{lifetime,wish} \\\\\n= Y_{cum,wish} - Y_{cum,earth} \\\\\n= \\$48.3M - \\$1.1M \\\\\n= \\$47.2M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nY_{cum,wish} \\\\\n= \\bar{y}_0 \\cdot \\frac{(1+g_{pc,wish})((1+g_{pc,wish})^{20}-1)}{g_{pc,wish}} \\\\\n+ \\bar{y}_{wish,20} \\cdot \\frac{(1+g_{pc,base})((1+g_{pc,base})^{T_{remaining}-20}-1)}{g_{pc,base}}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{y}_{0} \\\\\n= \\frac{GDP_{global}}{Pop_{global}} \\\\\n= \\frac{\\$115T}{8B} \\\\\n= \\$14.4K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{y}_{wish,20} \\\\\n= \\frac{GDP_{wish,20}}{Pop_{2045}} \\\\\n= \\frac{\\$10700T}{9.2B} \\\\\n= \\$1.16M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nGDP_{wish,20}=GDP_0(1+g_{ramp})^{3}(1+g_{full})^{17}\n$$\n\nwhere:\n\n$$\ns_{mil,max} = Cut_{WW2} = 87.6\\% = 87.6\\%\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCut_{WW2} \\\\\n= 1 - \\frac{Spending_{US,1947}}{Spending_{US,1945}} \\\\\n= 1 - \\frac{\\$176B}{\\$1.42T} \\\\\n= 87.6\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nf_{cure,20,wish} \\\\\n= \\min\\left(1.0, Treatments_{new,ann} \\times min(k_{capacity} \\times \\left(\\frac{s_{mil,max}}{0.01}\\right), k_{capacity,max}) \\times \\frac{20}{N_{untreated}}\\right)\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity,max} \\\\\n= \\frac{N_{willing}}{Slots_{curr}} \\\\\n= \\frac{1.08B}{1.9M} \\\\\n= 566\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{willing} \\\\\n= N_{patients} \\times Pct_{willing} \\\\\n= 2.4B \\times 44.8\\% \\\\\n= 1.08B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{y}_{base,20} \\\\\n= \\frac{GDP_{base,20}}{Pop_{2045}} \\\\\n= \\frac{\\$188T}{9.2B} \\\\\n= \\$20.5K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nGDP_{base,20} = GDP_{global} \\times (1 + g_{base})^{20}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{remaining} \\\\\n= LE_{global} - Age_{median} \\\\\n= 79 - 30.5 \\\\\n= 48.5\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nY_{cum,earth} \\\\\n= \\bar{y}_0 \\cdot \\frac{(1+g_{pc,base})((1+g_{pc,base})^{T_{remaining}}-1)}{g_{pc,base}}\n\\end{gathered}\n$$"
"wishonia_trajectory_lifetime_income_multiplier": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-wishonia_trajectory_lifetime_income_multiplier\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Ratio of cumulative lifetime income under Wishonia Trajectory vs current trajectory. Income-agnostic: applies as a multiplier to any individual's lifetime earnings. | Calculated from 2 inputs | ✓ High confidence | Formula: WISHONIA_TRAJECTORY_CUMULATIVE_LIFETIME_INCOME / CURRENT_TRAJECTORY_CUMULATIVE_LIFETIME_INCOME | Unit: x | Click to view details, calculation & sources\">44x (95% CI: 15x-237x)</a>"
"wishonia_trajectory_lifetime_income_multiplier_latex": "$$\n\\begin{gathered}\nk_{lifetime,wish:earth} \\\\\n= \\frac{Y_{cum,wish}}{Y_{cum,earth}} \\\\\n= \\frac{\\$48.3M}{\\$1.1M} \\\\\n= 44\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nY_{cum,wish} \\\\\n= \\bar{y}_0 \\cdot \\frac{(1+g_{pc,wish})((1+g_{pc,wish})^{20}-1)}{g_{pc,wish}} \\\\\n+ \\bar{y}_{wish,20} \\cdot \\frac{(1+g_{pc,base})((1+g_{pc,base})^{T_{remaining}-20}-1)}{g_{pc,base}}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{y}_{0} \\\\\n= \\frac{GDP_{global}}{Pop_{global}} \\\\\n= \\frac{\\$115T}{8B} \\\\\n= \\$14.4K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{y}_{wish,20} \\\\\n= \\frac{GDP_{wish,20}}{Pop_{2045}} \\\\\n= \\frac{\\$10700T}{9.2B} \\\\\n= \\$1.16M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nGDP_{wish,20}=GDP_0(1+g_{ramp})^{3}(1+g_{full})^{17}\n$$\n\nwhere:\n\n$$\ns_{mil,max} = Cut_{WW2} = 87.6\\% = 87.6\\%\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCut_{WW2} \\\\\n= 1 - \\frac{Spending_{US,1947}}{Spending_{US,1945}} \\\\\n= 1 - \\frac{\\$176B}{\\$1.42T} \\\\\n= 87.6\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nf_{cure,20,wish} \\\\\n= \\min\\left(1.0, Treatments_{new,ann} \\times min(k_{capacity} \\times \\left(\\frac{s_{mil,max}}{0.01}\\right), k_{capacity,max}) \\times \\frac{20}{N_{untreated}}\\right)\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity,max} \\\\\n= \\frac{N_{willing}}{Slots_{curr}} \\\\\n= \\frac{1.08B}{1.9M} \\\\\n= 566\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{willing} \\\\\n= N_{patients} \\times Pct_{willing} \\\\\n= 2.4B \\times 44.8\\% \\\\\n= 1.08B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\n\\bar{y}_{base,20} \\\\\n= \\frac{GDP_{base,20}}{Pop_{2045}} \\\\\n= \\frac{\\$188T}{9.2B} \\\\\n= \\$20.5K\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nGDP_{base,20} = GDP_{global} \\times (1 + g_{base})^{20}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nT_{remaining} \\\\\n= LE_{global} - Age_{median} \\\\\n= 79 - 30.5 \\\\\n= 48.5\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nY_{cum,earth} \\\\\n= \\bar{y}_0 \\cdot \\frac{(1+g_{pc,base})((1+g_{pc,base})^{T_{remaining}}-1)}{g_{pc,base}}\n\\end{gathered}\n$$"
"wishonia_trajectory_vs_treaty_trajectory_gdp_multiplier_year_20": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-wishonia_trajectory_vs_treaty_trajectory_gdp_multiplier_year_20\" class=\"parameter-link\" data-source-ref=\"\" data-source-type=\"calculated\" data-confidence=\"high\" title=\"Year-20 GDP multiplier from adding non-health dysfunction-capital reallocation on top of the Treaty Trajectory channels. | Calculated from 2 inputs | ✓ High confidence | Formula: WISHONIA_TRAJECTORY_GDP_YEAR_20 ÷ TREATY_TRAJECTORY_GDP_YEAR_20 | Unit: x | Click to view details, calculation & sources\">11.6x (95% CI: 8.39x-28x)</a>"
"wishonia_trajectory_vs_treaty_trajectory_gdp_multiplier_year_20_latex": "$$\n\\begin{gathered}\nk_{wish,full:core,20} \\\\\n= \\frac{GDP_{wish,20}}{GDP_{treaty,20}} \\\\\n= \\frac{\\$10700T}{\\$919T} \\\\\n= 11.6\n\\end{gathered}\n$$\n\nwhere:\n\n$$\nGDP_{wish,20}=GDP_0(1+g_{ramp})^{3}(1+g_{full})^{17}\n$$\n\nwhere:\n\n$$\ns_{mil,max} = Cut_{WW2} = 87.6\\% = 87.6\\%\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCut_{WW2} \\\\\n= 1 - \\frac{Spending_{US,1947}}{Spending_{US,1945}} \\\\\n= 1 - \\frac{\\$176B}{\\$1.42T} \\\\\n= 87.6\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nf_{cure,20,wish} \\\\\n= \\min\\left(1.0, Treatments_{new,ann} \\times min(k_{capacity} \\times \\left(\\frac{s_{mil,max}}{0.01}\\right), k_{capacity,max}) \\times \\frac{20}{N_{untreated}}\\right)\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity} \\\\\n= \\frac{N_{fundable,dFDA}}{Slots_{curr}} \\\\\n= \\frac{23.4M}{1.9M} \\\\\n= 12.3\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{fundable,dFDA} \\\\\n= \\frac{Subsidies_{dFDA,ann}}{Cost_{pragmatic,pt}} \\\\\n= \\frac{\\$21.8B}{\\$929} \\\\\n= 23.4M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nSubsidies_{dFDA,ann} \\\\\n= Funding_{dFDA,ann} - OPEX_{dFDA} \\\\\n= \\$21.8B - \\$40M \\\\\n= \\$21.8B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nOPEX_{dFDA} \\\\\n= Cost_{platform} + Cost_{staff} + Cost_{infra} \\\\\n+ Cost_{regulatory} + Cost_{community} \\\\\n= \\$15M + \\$10M + \\$8M + \\$5M + \\$2M \\\\\n= \\$40M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nk_{capacity,max} \\\\\n= \\frac{N_{willing}}{Slots_{curr}} \\\\\n= \\frac{1.08B}{1.9M} \\\\\n= 566\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{willing} \\\\\n= N_{patients} \\times Pct_{willing} \\\\\n= 2.4B \\times 44.8\\% \\\\\n= 1.08B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nN_{untreated} \\\\\n= N_{rare} \\times 0.95 \\\\\n= 7{,}000 \\times 0.95 \\\\\n= 6{,}650\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nGDP_{treaty,20} \\\\\n= GDP_{global} \\times (1 + g_{base} + g_{redirect,treaty,20} \\\\\n+ g_{peace,treaty,20} + g_{cyber,treaty,20} \\\\\n+ g_{health,treaty,20})^{20}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{redirect,treaty,20} \\\\\n= \\bar{s}_{treaty,20} \\times \\Delta g_{30\\%} \\times m_{spillover} \\times 1.67 \\\\\n= 5.8\\% \\times 5.5\\% \\times 2 \\times 1.67 \\\\\n= 1.06\\%\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{peace,treaty,20} \\\\\n= \\left(\\frac{Benefit_{peace,soc}}{GDP_{global}}\\right) \\times \\left(\\frac{\\bar{s}_{treaty,20}}{Reduce_{treaty}}\\right) \\times \\varepsilon_{conflict}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nBenefit_{peace,soc} \\\\\n= Cost_{war,total} \\times Reduce_{treaty} \\\\\n= \\$11.4T \\times 1\\% \\\\\n= \\$114B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,total} \\\\\n= Cost_{war,direct} + Cost_{war,indirect} \\\\\n= \\$7.66T + \\$3.7T \\\\\n= \\$11.4T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,direct} \\\\\n= Loss_{life,conflict} + Damage_{infra,total} \\\\\n+ Disruption_{trade} + Spending_{mil} \\\\\n= \\$2.45T + \\$1.88T + \\$616B + \\$2.72T \\\\\n= \\$7.66T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{life,conflict} \\\\\n= Cost_{combat,human} + Cost_{state,human} \\\\\n+ Cost_{terror,human} \\\\\n= \\$2.34T + \\$27B + \\$83B \\\\\n= \\$2.45T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{combat,human} \\\\\n= Deaths_{combat} \\times VSL \\\\\n= 234{,}000 \\times \\$10M \\\\\n= \\$2.34T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{state,human} \\\\\n= Deaths_{state} \\times VSL \\\\\n= 2{,}700 \\times \\$10M \\\\\n= \\$27B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{terror,human} \\\\\n= Deaths_{terror} \\times VSL \\\\\n= 8{,}300 \\times \\$10M \\\\\n= \\$83B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDamage_{infra,total} \\\\\n= Damage_{comms} + Damage_{edu} + Damage_{energy} \\\\\n+ Damage_{health} + Damage_{transport} + Damage_{water} \\\\\n= \\$298B + \\$234B + \\$422B + \\$166B + \\$487B + \\$268B \\\\\n= \\$1.88T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDisruption_{trade} \\\\\n= Disruption_{currency} + Disruption_{energy} \\\\\n+ Disruption_{shipping} + Disruption_{supply} \\\\\n= \\$57.4B + \\$125B + \\$247B + \\$187B \\\\\n= \\$616B\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nCost_{war,indirect} \\\\\n= Damage_{env} + Loss_{growth,mil} + Loss_{capital,conflict} \\\\\n+ Cost_{psych} + Cost_{refugee} + Cost_{vet} \\\\\n= \\$100B + \\$2.72T + \\$300B + \\$232B + \\$150B + \\$200B \\\\\n= \\$3.7T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{cyber,treaty,20} \\\\\n= \\left(\\frac{Cost_{cyber}}{GDP_{global}}\\right) \\times \\bar{s}_{treaty,20} \\times \\varepsilon_{conflict}\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\ng_{health,treaty,20} \\\\\n= ((1 + f_{cure,20,treaty} \\times d_{disease} \\\\\n+ \\left(\\frac{Loss_{lag}}{GDP_{global}}\\right))^{\\frac{1}{20}}) - 1\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nf_{cure,20,treaty} \\\\\n= \\min\\left(1.0, Treatments_{new,ann} \\times (3 \\times min(k_{capacity} \\times 1, k_{capacity,max}) \\\\\n+ 4 \\times min(k_{capacity} \\times 2, k_{capacity,max}) \\\\\n+ 5 \\times min(k_{capacity} \\times 5, k_{capacity,max}) \\\\\n+ 8 \\times min(k_{capacity} \\times 10, k_{capacity,max})) / N_{untreated}\\right)\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLoss_{lag} \\\\\n= Deaths_{lag,total} \\times (LE_{global} - Age_{death,delay}) \\times Value_{QALY} \\\\\n= 102M \\times (79 - 62) \\times \\$150K \\\\\n= \\$259T\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nDeaths_{lag,total} \\\\\n= Lives_{saved,annual} \\times T_{lag} \\\\\n= 12.4M \\times 8.2 \\\\\n= 102M\n\\end{gathered}\n$$\n\nwhere:\n\n$$\n\\begin{gathered}\nLives_{saved,annual} \\\\\n= \\frac{LY_{saved,annual}}{T_{ext}} \\\\\n= \\frac{149M}{12} \\\\\n= 12.4M\n\\end{gathered}\n$$"
"workforce_with_productivity_loss": "<a href=\"/knowledge/appendix/parameters-and-calculations.html#sec-workforce_with_productivity_loss\" class=\"parameter-link\" data-source-ref=\"chronic-illness-workforce-productivity-loss\" data-source-type=\"external\" data-confidence=\"high\" title=\"Percentage of workforce experiencing productivity loss from chronic illness (28%) | ✓ High confidence | Unit: rate | Click to view details, calculation & sources\">28%</a>"
"workforce_with_productivity_loss_cite": "@chronic-illness-workforce-productivity-loss"
"_cascade_generations": "<span class=\"parameter-link\" title=\"practical sharing depth\">3</span>"
"_r0": "<span class=\"parameter-link\" title=\"Parameter: _R0\">0.15</span>"
"_social_network_pop": "<span class=\"parameter-link\" title=\"global connected population\">5 billion</span>"
"_us_base_political_spending": "<span class=\"parameter-link\" title=\"Parameter: _US_BASE_POLITICAL_SPENDING\">28.8 billion</span>"
"total_parameter_count": "643"
"total_latex_equation_count": "302"
"total_nounit_variant_count": "165"
"total_citation_count": "203"