Social Disadvantage, Politics, and SARS-CoV-2 Trends: A County-Level Analysis of United States Data

Journal Article

AbstractBackgroundUnderstanding the epidemiology of SARS-CoV-2 is essential for public health control efforts. Social, demographic, and political characteristics at the US county level might be associated with the trajectories of SARS-CoV-2 case incidence.ObjectiveTo understand how underlying social, demographic, and political characteristics at the US county level might be associated with the trajectories of SARS-CoV-2 case incidence.DesignRetrospective analysis of the trajectory of reported SARS-CoV-2 case counts at the US county level during June 1, 2020 – June 30,2020 and social, demographic, and political characteristics of the county.SettingUnited States.ParticipantsReported SARS-CoV-2 cases.ExposuresMetropolitan designation, Social Deprivation Index (SDI), 2016 Republican Presidential Candidate Victory.Main Outcomes and MeasuresSARS-CoV-2 case incidence.Results1023/3142 US counties were included in the analysis. 678 (66.3%) had increasing SARS-CoV-2 case counts between June 1 – June 30, 2020. In univariate analysis, counties with increasing case counts had a significantly higher SDI (median 48, IQR 24 – 72) than counties with non-increasing case counts (median 40, IQR 19 – 66; p=0.009). In the multivariable model, metropolitan areas of 250,000 – 1 million population, higher percentage of Black residents and a 10-point or greater Republican victory were independently associated with increasing case counts.LimitationsThe data examines county-level voting patterns and does not account for individual voting behavior, subjecting this work to the potential for ecologic fallacy.ConclusionIncreasing case counts of SARS-CoV-2 in the US are likely driven by a combination of social disadvantage, social networks, and behavioral factors. Addressing social disadvantage and differential belief systems that may correspond with political alignment will be essential for pandemic control.

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Duke Authors

Cited Authors

  • Mourad, A; Turner, NA; Baker, AW; Okeke, NL; Narayanasamy, S; Rolfe, R; Engemann, JJ; Cox, GM; Stout, JE

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Digital Object Identifier (DOI)

  • 10.1101/2020.07.11.20151647