Your browser doesn't support javascript.
loading
Overcrowding and COVID-19 mortality across U.S. counties: Are disparities growing over time?
Kamis, Christina; Stolte, Allison; West, Jessica S; Fishman, Samuel H; Brown, Taylor; Brown, Tyson; Farmer, Heather R.
Afiliação
  • Kamis C; Department of Sociology, Duke University, Durham, NC, USA.
  • Stolte A; Department of Sociology, Duke University, Durham, NC, USA.
  • West JS; Center for the Study of Aging and Human Development, Duke University, Durham, NC, USA.
  • Fishman SH; Department of Sociology, Duke University, Durham, NC, USA.
  • Brown T; Department of Sociology, Duke University, Durham, NC, USA.
  • Brown T; Department of Sociology, Duke University, Durham, NC, USA.
  • Farmer HR; Department of Human Development and Family Sciences, University of Delaware, Newark, DE, USA.
SSM Popul Health ; 15: 100845, 2021 Sep.
Article em En | MEDLINE | ID: mdl-34189244
A growing line of research underscores that sociodemographic factors may contribute to disparities in the impact of COVID-19. Further, stages of disease theory suggests that disparities may grow as the pandemic unfolds and more advantaged areas are better able to apply growing knowledge and mitigation strategies. In this paper, we focus on the role of county-level household overcrowding on disparities in COVID-19 mortality in U.S. counties. We examine this relationship across three theoretically important periods of the pandemic from April-October 2020, that mark both separate stages of community knowledge and national mortality levels. We find evidence that the percentage of overcrowded households is a stronger predictor of COVID-19 mortality during later periods of the pandemic. Moreover, despite a relationship between overcrowding and poverty at the county-level, overcrowding plays an independent role in predicting COVID-19 mortality. Our findings underscore that areas disadvantaged by overcrowding may be more vulnerable to the effects of COVID-19 and that this vulnerability may lead to changing disparities over time.
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article