County-level Predictors of Coronavirus Disease 2019 (COVID-19) Cases and Deaths in the United States: What Happened, and Where Do We Go from Here?
disparities
risk-factors
transmission
vaccine distribution
vulnerable populations
Journal
Clinical infectious diseases : an official publication of the Infectious Diseases Society of America
ISSN: 1537-6591
Titre abrégé: Clin Infect Dis
Pays: United States
ID NLM: 9203213
Informations de publication
Date de publication:
05 10 2021
05 10 2021
Historique:
received:
21
10
2020
accepted:
16
11
2020
pubmed:
20
11
2020
medline:
16
10
2021
entrez:
19
11
2020
Statut:
ppublish
Résumé
The United States has been heavily impacted by the coronavirus disease 2019 (COVID-19) pandemic. Understanding microlevel patterns in US rates of COVID-19 can inform specific prevention strategies. Using a negative binomial mixed-effects regression model, we evaluated the associations between a broad set of US county-level sociodemographic, economic, and health status-related characteristics and cumulative rates of laboratory-confirmed COVID-19 cases and deaths between 22 January 2020 and 31 August 2020. Rates of COVID-19 cases and deaths were higher in US counties that were more urban or densely populated or that had more crowded housing, air pollution, women, persons aged 20-49 years, racial/ethnic minorities, residential housing segregation, income inequality, uninsured persons, diabetics, or mobility outside the home during the pandemic. To our knowledge, this study provides results from the most comprehensive multivariable analysis of county-level predictors of rates of COVID-19 cases and deaths conducted to date. Our findings make clear that ensuring that COVID-19 preventive measures, including vaccines when available, reach vulnerable and minority communities and are distributed in a manner that meaningfully disrupts transmission (in addition to protecting those at highest risk of severe disease) will likely be critical to stem the pandemic.
Sections du résumé
BACKGROUND
The United States has been heavily impacted by the coronavirus disease 2019 (COVID-19) pandemic. Understanding microlevel patterns in US rates of COVID-19 can inform specific prevention strategies.
METHODS
Using a negative binomial mixed-effects regression model, we evaluated the associations between a broad set of US county-level sociodemographic, economic, and health status-related characteristics and cumulative rates of laboratory-confirmed COVID-19 cases and deaths between 22 January 2020 and 31 August 2020.
RESULTS
Rates of COVID-19 cases and deaths were higher in US counties that were more urban or densely populated or that had more crowded housing, air pollution, women, persons aged 20-49 years, racial/ethnic minorities, residential housing segregation, income inequality, uninsured persons, diabetics, or mobility outside the home during the pandemic.
CONCLUSIONS
To our knowledge, this study provides results from the most comprehensive multivariable analysis of county-level predictors of rates of COVID-19 cases and deaths conducted to date. Our findings make clear that ensuring that COVID-19 preventive measures, including vaccines when available, reach vulnerable and minority communities and are distributed in a manner that meaningfully disrupts transmission (in addition to protecting those at highest risk of severe disease) will likely be critical to stem the pandemic.
Identifiants
pubmed: 33211797
pii: 5992242
doi: 10.1093/cid/ciaa1729
pmc: PMC7717189
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
e1814-e1821Subventions
Organisme : Pfizer Inc
Informations de copyright
© The Author(s) 2020. Published by Oxford University Press for the Infectious Diseases Society of America.
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