Quantifying the impact of COVID-19 control measures using a Bayesian model of physical distancing.

Quantifying the impact of COVID-19 control measures using a Bayesian model of physical distancing.

Extensive non-pharmaceutical and physical distancing measures are currently the primary interventions against coronavirus disease 2019 (COVID-19) worldwide. It is therefore urgent to estimate the impact such measures are having. We introduce a Bayesian epidemiological model in which a proportion of...

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Bibliographic Details
Main Authors: Sean C Anderson, Andrew M Edwards, Madi Yerlanov, Nicola Mulberry, Jessica E Stockdale, Sarafa A Iyaniwura, Rebeca C Falcao, Michael C Otterstatter, Michael A Irvine, Naveed Z Janjua, Daniel Coombs, Caroline Colijn
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2020-12-01
Series:PLoS Computational Biology
Online Access:https://doi.org/10.1371/journal.pcbi.1008274

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https://doi.org/10.1371/journal.pcbi.1008274

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