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