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Predicting coronavirus disease (COVID-19) outcomes in the United States early in the epidemic

By 21 October 2020, the coronavirus disease (COVID-19) epidemic in the United States (US) had infected 8.3 million people, resulting in 61,364 laboratory-confirmed hospitalizations and 222,157 deaths. Currently, policymakers are trying to better understand this epidemic, especially the human-to-huma...

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Autores principales: Simoes, Eduardo J., Schmaltz, Chester L., Jackson-Thompson, Jeannette
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8545716/
https://www.ncbi.nlm.nih.gov/pubmed/34722135
http://dx.doi.org/10.1016/j.pmedr.2021.101624
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author Simoes, Eduardo J.
Schmaltz, Chester L.
Jackson-Thompson, Jeannette
author_facet Simoes, Eduardo J.
Schmaltz, Chester L.
Jackson-Thompson, Jeannette
author_sort Simoes, Eduardo J.
collection PubMed
description By 21 October 2020, the coronavirus disease (COVID-19) epidemic in the United States (US) had infected 8.3 million people, resulting in 61,364 laboratory-confirmed hospitalizations and 222,157 deaths. Currently, policymakers are trying to better understand this epidemic, especially the human-to-human transmissibility of the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in relation to social, populational, air travel related and environmental exposure factors. Our study used 50 US states’ public health surveillance datasets (January 1-April 1, 2020) to measure associations of confirmed COVID-19 cases, hospitalizations and deaths with these variables. Using the resulting associations and multivariate regression (Negative Binomial and Poisson), predicted cases, hospitalizations and deaths were generated for each US state early in the epidemic. Factors associated with a significantly increased risk of COVID-19 disease, hospitalization and death included: population density, enplanement, Black race and increased sun exposure; in addition, COVID-19 disease and hospitalization were also associated with morning humidity. Although predictions of the number of cases, hospitalizations and deaths due to COVID-19 were not accurate for every state, those states with a combination of large number of enplanements, high population density, high proportion of Black residents, high humidity or low sun exposure may expect more rapid than expected growth in the number of COVID-19 events early in the epidemic.
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spelling pubmed-85457162021-10-26 Predicting coronavirus disease (COVID-19) outcomes in the United States early in the epidemic Simoes, Eduardo J. Schmaltz, Chester L. Jackson-Thompson, Jeannette Prev Med Rep Regular Article By 21 October 2020, the coronavirus disease (COVID-19) epidemic in the United States (US) had infected 8.3 million people, resulting in 61,364 laboratory-confirmed hospitalizations and 222,157 deaths. Currently, policymakers are trying to better understand this epidemic, especially the human-to-human transmissibility of the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in relation to social, populational, air travel related and environmental exposure factors. Our study used 50 US states’ public health surveillance datasets (January 1-April 1, 2020) to measure associations of confirmed COVID-19 cases, hospitalizations and deaths with these variables. Using the resulting associations and multivariate regression (Negative Binomial and Poisson), predicted cases, hospitalizations and deaths were generated for each US state early in the epidemic. Factors associated with a significantly increased risk of COVID-19 disease, hospitalization and death included: population density, enplanement, Black race and increased sun exposure; in addition, COVID-19 disease and hospitalization were also associated with morning humidity. Although predictions of the number of cases, hospitalizations and deaths due to COVID-19 were not accurate for every state, those states with a combination of large number of enplanements, high population density, high proportion of Black residents, high humidity or low sun exposure may expect more rapid than expected growth in the number of COVID-19 events early in the epidemic. 2021-10-25 /pmc/articles/PMC8545716/ /pubmed/34722135 http://dx.doi.org/10.1016/j.pmedr.2021.101624 Text en © 2021 The Authors. Published by Elsevier Inc. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Regular Article
Simoes, Eduardo J.
Schmaltz, Chester L.
Jackson-Thompson, Jeannette
Predicting coronavirus disease (COVID-19) outcomes in the United States early in the epidemic
title Predicting coronavirus disease (COVID-19) outcomes in the United States early in the epidemic
title_full Predicting coronavirus disease (COVID-19) outcomes in the United States early in the epidemic
title_fullStr Predicting coronavirus disease (COVID-19) outcomes in the United States early in the epidemic
title_full_unstemmed Predicting coronavirus disease (COVID-19) outcomes in the United States early in the epidemic
title_short Predicting coronavirus disease (COVID-19) outcomes in the United States early in the epidemic
title_sort predicting coronavirus disease (covid-19) outcomes in the united states early in the epidemic
topic Regular Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8545716/
https://www.ncbi.nlm.nih.gov/pubmed/34722135
http://dx.doi.org/10.1016/j.pmedr.2021.101624
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