Close Quarters: An Investigation of Neighborhood Effects and SARS-CoV-2 in Chicago 公开
Hancock, Clio (Spring 2022)
Abstract
The unequal impact of SARS-CoV-2 on minority communities across the United States is undeniable, with different disciplines proposing theories to understand the origins of these inequalities. Here I investigate individual behavioral predictors of SARS-CoV-2 exposure and zip code-level predictors of infection in a large COVID-19 seroprevalence study in Chicago, IL (N=7,058), conducted June-November 2020. Participants provided self-collected finger stick dried blood samples which were analyzed for the presence of antibodies against the receptor binding domain of SARS-CoV-2. Seropositivity was modeled as a function of individual variables with multilevel logistic regressions. Results show that age and household density were individual-level variables significantly associated with the odds of seropositivity. Individuals who were over 60 (OR: 0.62, 95% CI: 0.43, 0.90) had lower odds of seropositivity. Those living in a household with more than five people (OR: 2.85, 95% CI: 1.69, 4.80) had a higher chance of seropositivity. After controlling for individual-level variables, a Community COVID-19 Vulnerability Index (CCVI) was constructed to help explain the context of the zip codes being studied. This index used American Community Survey data to rank Chicago’s 57 zip codes based on variables in three risk factor categories: socioeconomic, epidemiological and occupational risk factors. Univariate regression showed that Low CCVI was significantly associated with lower chances of seropositivity (OR: 0.68, 95% CI: 0.54, 0.86), but CCVI was not significant when individual-level factors were controlled for. Spatial analysis also found clustering of COVID-19 positivity and of the CCVI throughout the city of Chicago. The Moran’s I–a measure of spatial autocorrelation–of COVID-19 rates was 0.19 (p = 0.008) and the Moran’s I of CCVI Ranking was 0.67 (p = 2.6 x 10-15). These data show that COVID-19 infections are not distributed evenly across the city, and that individual-level factors are significant predictors of SARS-CoV-2 exposure. As more infectious SARS-CoV-2 variants take hold, this analysis may help to understand the complex factors that contribute to infection.
Table of Contents
Introduction
Background
Virus Emergence and History
COVID-19 Clinical Presentation
Mechanisms of Viral Transmission
Antibody Surveillance
Pandemic-Related Inequalities
Potential Individual-Level Predictors of SARS-CoV-2 Infection
Section II: Neighborhood Effects and Health
Health and Place Theory
Health Outcomes and Place
Section III: City of Chicago and COVID-19 Impacts
The City of Chicago
Spatial Disparities
Methods
Results
Discussion
Conclusion
About this Honors Thesis
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