In:
The Journal of Infectious Diseases, Oxford University Press (OUP), ( 2023-08-24)
Abstract:
Because COVID-19 case data do not capture most SARS-CoV-2 infections, the actual risk of severe disease and death per infection is unknown. Integrating sociodemographic data into analysis can show consequential health disparities. Methods Data were merged from September 2020 to November 2021 from 6 national surveillance systems in matched geographic areas and analyzed to estimate numbers of COVID-19–associated cases, emergency department visits, and deaths per 100 000 infections. Relative risks of outcomes per infection were compared by sociodemographic factors in a data set including 1490 counties from 50 states and the District of Columbia, covering 71% of the US population. Results Per infection with SARS-CoV-2, COVID-19–related morbidity and mortality were higher among non-Hispanic American Indian and Alaska Native persons, non-Hispanic Black persons, and Hispanic or Latino persons vs non-Hispanic White persons; males vs females; older people vs younger; residents in more socially vulnerable counties vs less; those in large central metro areas vs rural; and people in the South vs the Northeast. Discussion Meaningful disparities in COVID-19 morbidity and mortality per infection were associated with sociodemography and geography. Addressing these disparities could have helped prevent the loss of tens of thousands of lives.
Type of Medium:
Online Resource
ISSN:
0022-1899
,
1537-6613
DOI:
10.1093/infdis/jiad357
Language:
English
Publisher:
Oxford University Press (OUP)
Publication Date:
2023
detail.hit.zdb_id:
1473843-0