This project enables users to analyze COVID-19 mortality data and generate random and biased (disease) testing distributions.
Please run the files in excess_deaths to compute different mortality measures and analyze COVID-19 mortality data for different jurisdictions. (Make sure that you download the most recent source data, see below.) The coefficient of variation (CV) of the infection fatality ratio (IFR) can be directly calculated via IFR_CV.py.
To study the influence of different type I and II errors (or false-positive and false-negative rates) on disease testing distributions, you can use the examples testing_analytical_replacement_false.py and testing_analytical_replacement_true.py in the src folder and plot the generated results with testing_plot.py. The resulting plot will be similar to the one shown below:
- https://raw.githubusercontent.com/nytimes/covid-19-data/master/live/us-states.csv
- https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_daily_reports
- https://github.com/TheEconomist/covid-19-excess-deaths-tracker
- L. Böttcher, M. R. D'Orsogna, T. Chou, Using excess deaths and testing statistics to determine estimates of COVID-19 mortalities, European Journal of Epidemiology (2021)
- L. Böttcher, M. R. D'Orsogna, T. Chou, A statistical model of COVID-19 testing in populations: effects of sampling bias and testing errors, Philosophical Transactions of the Royal Society A (2022)
Please cite our works if you use our data analysis and disease testing frameworks.
@article{bottcher2021using,
title={Using excess deaths and testing statistics to improve estimates of COVID-19 mortalities},
author={B{\"o}ttcher, Lucas and D'Orsogna, Maria and Chou, Tom},
journal={European Journal of Epidemiology},
volume={36},
pages={545--558},
year={2021}
}
@article{bottcher2021statistical,
title={A statistical model of COVID-19 testing in populations: effects of sampling bias and testing errors},
author={B{\"o}ttcher, Lucas and D'Orsogna, Maria R and Chou, Tom},
journal={Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences},
volume={380},
pages={20210121},
year={2022}
}