Predicting and preventing COVID-19 outbreaks in indoor environments: an agent-based modeling study.

ABSTRACT: How to mitigate the spread of infectious diseases like COVID-19 in indoor environments remains an important research question. In this study, we propose an agent-based modeling framework to evaluate facility usage policies that aim to lower the probability of outbreaks. The proposed framework is individual-based, spatially-resolved with time resolution of up to 1 s, and takes into detailed account specific floor layouts, occupant schedules and movement. It enables decision makers to compute realistic contact networks and generate risk profiles of their facilities without relying on wearable devices, smartphone tagging or surveillance cameras. Our demonstrative modeling results indicate that not all facility occupants present the same risk of starting an outbreak, where the driver of outbre

SUBMITTER: Reveil M 

PROVIDER: S-EPMC9514194 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature