Abstract

Introduction: Since the onset of the COVID-19 pandemic, large geographic differences in mortality rates have emerged, with higher rates in predominantly Black and Latinx neighborhoods. In this analysis we examined community-level differences across the city of Chicago to better understand how geographic differences are associated with COVID19 mortality. Hypothesis: We hypothesized there would be an association between higher community-level social vulnerability and COVID19 mortality rates. Methods: We examined publicly available data from the Cook County Medical Examiner data (Illinois) of all known COVID-19 deaths as of August 21, 2020. Decedent addresses (N = 2397) were restricted to the city of Chicago, geocoded, and classified according to the 77 recognized community areas in the city. Poisson regression models were used to determine significant community-level predictors of COVID19 mortality based on community-level demographic, social, health, and healthcare characteristics collected from the Chicago Health Atlas. Results: There was at least one COVID19-related death in each Chicago community area, with a crude mortality rate ranging from 0.571 - 24.5 deaths per 10,000 persons. In the fully adjusted model with 14 community-level predictors, higher community-level population density, percentage of males, living in crowded housing, and limited food access were associated with higher rates of COVID19 mortality. Higher community-level proportion of the population aged 65+ years and having a primary care provider were associated with lower COVID19 mortality. Differences by Black and Latinx race/ethnicity community-level demographics were not significant in the final model. Conclusions: Community-level factors of greater social vulnerability (crowded living conditions, limited food access) are strong predictors of community-level COVID19 mortality. These factors may limit effective social distancing and increase the necessity to enter public areas, raising community-level COVID19 mortality.

Full Text
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