Data Analytics Blueprint for Future Outbreaks

Overview

This is a template repository containing all of the necessary ingredients for crafting analytical outputs for future outbreaks. Please note that only those with read permissions for this template repository can use it as a template (info).

Flowchart

Folder Structure

.
├── xmart
|   ├── model_script        
|   └── reporting_templates 
├── data                           # Aggregate, line list, phylogentic data, etc.
├── inst                           # Images, assets, etc.
├── R                                     
│   ├── funcs                      # Custom functions
│   ├── scripts                    # Scripts for common analytics tasks
│   └── xmart_generator                       
├── outbreak_global.Rmd            # REPORT 
├── report_components              # Sections of report
│   ├── 1_overview.Rmd
│   ├── 2_1_1_epicurves.Rmd
│   ├── 2_1_2_epicurve_by_country.Rmd
│   ├── 2_1_2_epicurve_by_country_shiny.Rmd
│   ├── 2_1_3_epicurve_by_adm1.Rmd
│   ├── 2_2_recent_trends.Rmd
│   ├── 2_3_maps_and_tables_adm0.Rmd
│   ├── 2_3_maps_and_tables_adm1.Rmd
│   ├── 3_1_1_coverage.Rmd
│   ├── 3_1_2_coverage_internal.Rmd
│   ├── 3_2_1_trends.Rmd
│   ├── 3_2_2_epicurves_by_country.Rmd
│   ├── 3_2_2_epicurves_by_country_shiny.Rmd
│   ├── 3_2_3_epicurves_by_adm1.Rmd
│   ├── 3_2_4_epicurves_by_group.Rmd
│   ├── 3_3_case_profile.Rmd
│   ├── 3_4_case_profile_subgroup.Rmd
│   ├── 3_4_case_profile_subgroup_shiny.Rmd
│   ├── 3_5_case_profile_recent.Rmd
│   ├── 3_6_symptoms.Rmd
│   ├── 4_projections.Rmd
│   ├── 5_region_in_focus.Rmd
│   └── 6_final_sections.Rmd
├── outbreak_blueprint.Rproj    
└── README.md 

Custom Functions

This repository includes several useful functions which can be tailored to the user's needs. These functions perform common tasks associated with retrieving, processing, and visualizing outbreak data.

• compliance_table_external(): Creates table showing completeness of line list data, by WHO region
• compliance_table_internal(): Creates table showing completeness of line list data, by country
• download_all_data(): Downloads xMart data
• process_case_profile(): Creates table showing frequency and % of traits among cases
• vis_agesex(): Visualizes age-sex pyramid
• vis_agg_epicurve(): Plots epicurve using aggregate data
• vis_categoricals(): Visualizese key categorical variables (e.g., exposure setting, transmission route)
• vis_ll_epicurve(): Plots epicurve using line list data
• vis_reporting_delay(): Plots reporting delay distribution
• vis_symptoms(): Visualizes symptomatology data