Studying COVID-19 transmission in US state prisons using an agent-based modelling approach: a simulation study.

ABSTRACT:

Objectives

We aim to use an agent-based model to accurately predict the spread of COVID-19 within multiple US state prisons.

Design

We developed a semistochastic transmission model of COVID-19.

Setting

Five regional state-owned prisons within North Carolina.

Participants

Several thousand incarcerated individuals.

Primary and secondary outcome measures

We measured (1) the observed and simulated average daily infection rate of COVID-19 for each prison studied in 30-day intervals, (2) the observed and simulated average daily recovery rate from COVID-19 for each prison studied in 30-day intervals, (3) the mean absolute percentage error (MAPE) of each prison's summary statistics and the simulated results and (4) the parameter estimates of key predictors used

SUBMITTER: Owens AL 

PROVIDER: S-EPMC12706209 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature