Using spatial and temporal modeling to visualize the effects of U.S. state issued stay at home orders on COVID-19

Abstract Coronavirus disease 2019 dominated and augmented many aspects of life beginning in early 2020. Related research and data generation developed alongside its spread. We developed a Bayesian spatio-temporal Poisson disease mapping model for estimating real-time characteristics of the coronavir...

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Autores principales: Rachel Carroll, Christopher R. Prentice
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
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Acceso en línea:https://doaj.org/article/845ae2b8e32c447e850ef6fca873ad41
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