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Social inequality and the syndemic of chronic disease and COVID-19: county-level analysis in the USA

Abstract

Background Given the effect of chronic diseases on risk of severe COVID-19 infection, the present pandemic may have a particularly profound impact on socially disadvantaged counties.

Methods Counties in the USA were categorised into five groups by level of social vulnerability, using the Social Vulnerability Index (a widely used measure of social disadvantage) developed by the US Centers for Disease Control and Prevention. The incidence and mortality from COVID-19, and the prevalence of major chronic conditions were calculated relative to the least vulnerable quintile using Poisson regression models.

Results Among 3141 counties, there were 5 010 496 cases and 161 058 deaths from COVID-19 by 10 August 2020. Relative to the least vulnerable quintile, counties in the most vulnerable quintile had twice the rates of COVID-19 cases and deaths (rate ratios 2.11 (95% CI 1.97 to 2.26) and 2.42 (95% CI 2.22 to 2.64), respectively). Similarly, the prevalence of major chronic conditions was 24%–41% higher in the most vulnerable counties. Geographical clustering of counties with high COVID-19 mortality, high chronic disease prevalence and high social vulnerability was found, especially in southern USA.

Conclusion Some counties are experiencing a confluence of epidemics from COVID-19 and chronic diseases in the context of social disadvantage. Such counties are likely to require enhanced public health and social support.

  • access to hlth care
  • health inequalities
  • social inequalities
  • epidemics
  • epidemiology of chronic diseases

Data availability statement

All the data used in this study are publicly available and properly cited. Please contact Nazrul.Islam@ndph.ox.ac.uk for more information.

This article is made freely available for use in accordance with BMJ’s website terms and conditions for the duration of the covid-19 pandemic or until otherwise determined by BMJ. You may use, download and print the article for any lawful, non-commercial purpose (including text and data mining) provided that all copyright notices and trade marks are retained.

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