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Social determinants of COVID-19 mortality at the county level
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Social determinants of COVID-19 mortality at the county level
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Social determinants of COVID-19 mortality at the county level
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Journal Article
Social determinants of COVID-19 mortality at the county level
2020
Overview
As of August 2020, the United States is the global epicenter of the COVID-19 pandemic. Emerging data suggests that \"essential\" workers, who are disproportionately more likely to be racial/ethnic minorities and immigrants, bear a disproportionate degree of risk. We used publicly available data to build a series of spatial autoregressive models assessing county level associations between COVID-19 mortality and (1) percentage of individuals engaged in farm work, (2) percentage of households without a fluent, adult English-speaker, (3) percentage of uninsured individuals under the age of 65, and (4) percentage of individuals living at or below the federal poverty line. We further adjusted these models for total population, population density, and number of days since the first reported case in a given county. We found that across all counties that had reported a case of COVID-19 as of July 12, 2020 (n = 3024), a higher percentage of farmworkers, a higher percentage of residents living in poverty, higher density, higher population, and a higher percentage of residents over the age of 65 were all independently and significantly associated with a higher number of deaths in a county. In urban counties (n = 115), a higher percentage of farmworkers, higher density, and larger population were all associated with a higher number of deaths, while lower rates of insurance coverage in a county was independently associated with fewer deaths. In non-urban counties (n = 2909), these same patterns held true, with higher percentages of residents living in poverty and senior residents also significantly associated with more deaths. Taken together, our findings suggest that farm workers may face unique risks of contracting and dying from COVID-19, and that these risks are independent of poverty, insurance, or linguistic accessibility of COVID-19 health campaigns.
Publisher
Public Library of Science,Public Library of Science (PLoS)
Subject
/ Coronavirus Infections - epidemiology
/ Coronavirus Infections - mortality
/ COVID-19
/ Datasets
/ Demography - statistics & numerical data
/ Emigrants and Immigrants - statistics & numerical data
/ Farmers - statistics & numerical data
/ Generalized method of moments
/ Humans
/ Insurance Coverage - statistics & numerical data
/ Medicine and Health Sciences
/ Pneumonia, Viral - epidemiology
/ Pneumonia, Viral - mortality
/ Poverty
/ Research and Analysis Methods
/ Severe acute respiratory syndrome coronavirus 2
/ Workers
