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Overview

This software supports the results in the paper: https://www.medrxiv.org/content/10.1101/2020.04.29.20085134v1.article-metrics

The algorithm simulates a covid-19 epidemic for Austin, Tx, and determines triggers to enact social distancing orders to avoid exceeding hospital capacity. Chosen triggers attempt to minimize the total number of days that a city is in lock-down.

Structure of the code

threshold_policy.py

  • Main module to launch the search
  • Functions to excude the search and find optimized thresholds to enact lock-downs.
  • Iterators for traing and testing
  • Calendar generation (ad-hoc for Austin instance)

SEIYHARD_sim.py:

  • Simulator engine
  • Parallelizarion functions
  • Calander utils class (SimCalendar)

epi_parameters.py

  • Class EpiSetup to characterize the simulation and recompute contact matrices as needed.

intervention.py

  • Class intervention defining its properties and used in the simulator.
  • Helper function to create multiple interventions

utils.py

  • Timing function
  • Rounding functions

intances/austin.py

  • Module summarizing the input of the simulator.
  • Creates an instance of EpiSetup

Guidelines

  • Create new branches to test new features
  • Create a pull request to merge with master