/covid-workplace-risk

A simulation-based stochastic contact network to assess the cumulative incidence of COVID-19 in workplaces.

Primary LanguagePythonGNU General Public License v3.0GPL-3.0

COVID-19 model for Workplace Outbreaks

Guo, X.; Gupta, A.; Sampat, A; Wei, C. A Stochastic Contact Network Model for Assessing Outbreak Risk of COVID-19 in Workplaces.

A simulation-based stochastic contact network to assess the cumulative incidence of COVID-19 in workplaces.

Getting started

This code is written in python:3, and is expected to work in a standard python environment with the following libraries.

Dependencies

numpy
scipy

Quick Usage

In a terminal, type the following command to save 10,000 simulations of cumulative incidence in a workplace after 10 days in a csv file.

python covid_workplace_model.py -e 1000 -c 0.001 -o 'workplace_outbreak.csv'

The required arguments are -e, -c, and -o for number of employees, daily new case rate, and output file location, respectively.

Configuration

The following arguments are accepted -

-e | --employees

Required: True
Type: Integer

-c | --caserate

Required: True
Type: Float [0., 1.]

-o | --outfile

Required: True
Type: String filepath

--contacts

Required: False
Type: Integer
Default: 6

--sar

Required: False
Type: Float [0., 1.]
Default: 0.051

--days

Required: False
Type: Integer
Default: 10

--sims

Required: False
Type: Integer
Default: 10000

--prob_sustain

Required: False
Type: Float [0., 1.]
Default: 0.6

-v | --verbosity

Required: False
Type: Integer {0, 1, 2}
Default: 0

-l | --logfile

Required: False
Type: String filepath
Default : None

Advanced Usage

The python file provides functions for other equations from the paper. These functions can be used by importing them in an ipython terminal or another python project.

from covid_workplace_model import *

The following functions are provided -

  • get_activity_multiplier - Returns speaking activity multiplier for a given speaking volume in dB.
  • get_activity_virion - Returns the activity virions based on speaking percentage and volume
  • get_sar_from_speaking_airflow - Returns the SAR values, given design airflow in ACH, filteration, speaking percentage, speaking volume, and mask effectiveness ratio
  • get_betadist_parameters - Returns alpha and beta parameters for a Beta distribution given the average SAR
  • get_sar_given_betadist_parameters - Returns average SAR values, given alpha and beta parameters for a Beta distribution
  • get_probability_introduction_each_day - Returns the probability of case introduction based on employees, and daily new case rate
  • calculate_nday_workplace_incidence - Returns the cumulative incidence in a workplace over N days

Contributing

If you'd like to contribute, please fork the repository and use a feature branch. Pull requests are warmly welcome.

Licensing

The code in this project is licensed under GNU General Public License v3.0.