Bayesian space-time SIR modeling of Covid-19 in two US states during the 2020–2021 pandemic

This paper describes the Bayesian SIR modeling of the 3 waves of Covid-19 in two contrasting US states during 2020–2021. A variety of models are evaluated at the county level for goodness-of-fit and an assessment of confounding predictors is also made. It is found that models with three deprivation...

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Detalles Bibliográficos
Autores principales: Lawson, Andrew B., Kim, Joanne
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9778953/
https://www.ncbi.nlm.nih.gov/pubmed/36548256
http://dx.doi.org/10.1371/journal.pone.0278515
Descripción
Sumario:This paper describes the Bayesian SIR modeling of the 3 waves of Covid-19 in two contrasting US states during 2020–2021. A variety of models are evaluated at the county level for goodness-of-fit and an assessment of confounding predictors is also made. It is found that models with three deprivation predictors and neighborhood effects are important. In addition, the work index from Google mobility was also found to provide an increased explanation of the transmission dynamics.

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