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 |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2021
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Materias: | |
Acceso en línea: | https://doaj.org/article/845ae2b8e32c447e850ef6fca873ad41 |
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