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Social Disadvantage, Politics, and SARS-CoV-2 Trends: A County-Level Analysis of United States Data
Preprint
in English
| medRxiv
| ID: ppmedrxiv-20151647
ABSTRACT
BackgroundUnderstanding 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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Collection:
Preprints
Database:
medRxiv
Type of study:
Observational study
Language:
English
Year:
2020
Document type:
Preprint