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Unraveling US National COVID-19 Racial/Ethnic Disparities using County Level Data Among 328 Million Americans
Daniel Li; Sheila M. Gaynor; Corbin Quick; Jarvis T. Chen; Briana J.K. Stephenson; Brent A. Coull; Xihong Lin.
Afiliación
  • Daniel Li; Harvard. T.H. Chan School of Public Health
  • Sheila M. Gaynor; Harvard T.H. Chan School of Public Health
  • Corbin Quick; Harvard T.H. Chan School of Public Health
  • Jarvis T. Chen; Harvard T.H. Chan School of Public Health
  • Briana J.K. Stephenson; Harvard T.H. Chan School of Public Health
  • Brent A. Coull; Harvard T.H. Chan School of Public Health
  • Xihong Lin; Harvard T.H. Chan School of Public Health
Preprint en En | PREPRINT-MEDRXIV | ID: ppmedrxiv-20234989
ABSTRACT
Identifying areas with high COVID-19 burden and their characteristics can help improve vaccine distribution and uptake, reduce burdens on health care systems, and allow for better allocation of public health intervention resources. Synthesizing data from various government and nonprofit institutions of 3,142 United States (US) counties as of 12/21/2020, we studied county-level characteristics that are associated with cumulative case and death rates using regression analyses. Our results showed counties that are more rural, counties with more White/non-White segregation, and counties with higher percentages of people of color, in poverty, with no high school diploma, and with medical comorbidities such as diabetes and hypertension are associated with higher cumulative COVID-19 case and death rates. We identify the hardest hit counties in US using model-estimated case and death rates, which provide more reliable estimates of cumulative COVID-19 burdens than those using raw observed county-specific rates. Identification of counties with high disease burdens and understanding the characteristics of these counties can help inform policies to improve vaccine distribution, deployment and uptake, prevent overwhelming health care systems, and enhance testing access, personal protection equipment access, and other resource allocation efforts, all of which can help save more lives for vulnerable communities. Significance statementWe found counties that are more rural, counties with more White/non-White segregation, and counties with higher percentages of people of color, in poverty, with no high school diploma, and with medical comorbidities such as diabetes and hypertension are associated with higher cumulative COVID-19 case and death rates. We also identified individual counties with high cumulative COVID-19 burden. Identification of counties with high disease burdens and understanding the characteristics of these counties can help inform policies to improve vaccine distribution, deployment and uptake, prevent overwhelming health care systems, and enhance testing access, personal protection equipment access, and other resource allocation efforts, all of which can help save more lives for vulnerable communities.
Licencia
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Texto completo: 1 Colección: 09-preprints Base de datos: PREPRINT-MEDRXIV Idioma: En Año: 2020 Tipo del documento: Preprint
Texto completo: 1 Colección: 09-preprints Base de datos: PREPRINT-MEDRXIV Idioma: En Año: 2020 Tipo del documento: Preprint