RACIAL/ETHNIC COUNTIES COMPOSITION EFFECTS ON COVID-19 CASE RATES AND CASE FATALITY RATIOS THROUGH SEPTEMBER 2020: A SPATIAL APPROACH
Open Access
Author:
Stiberman, Laura
Graduate Program:
Sociology
Degree:
Master of Arts
Document Type:
Master Thesis
Date of Defense:
December 17, 2020
Committee Members:
Stephen Augustus Matthews, Thesis Advisor/Co-Advisor Guangqing Chi, Committee Member Ashton Michael Verdery, Committee Member Eric P Baumer, Program Head/Chair
Keywords:
COVID-19 percentage of Blacks percentage of Hispanics spatial dependence spatial nonstationary
Abstract:
The purpose of this study is to understand in which extent racial/ethnic counties composition coupled with spatial configurations help explain COVID-19 Case Rates (CR) and Case Fatality Ratios (CFR) across the US. I assembled a county level dataset that contains COVID-19 confirmed cases and deaths as of September 23, 2020, and many sociodemographic variables from a wide array or sources. Taking ordinary least squares regression as a baseline model, I conduct spatial lag, spatial error, and geographically weighted regressions to explore the associations between percentage of Blacks, percentage of Hispanics, spatial autocorrelation and other factors that were expected to shape the differences in COVID-19 CR and CFRs outcomes across the country. Across the global models, I found that percentage of Blacks is the most important predictor of COVID-19 CR and CFRs at the county level while percentage of Hispanics is not that important. Accounting for spatial dependence helped improved COVID-19 CR and CFRs models. However, the associations between percentage of Blacks and percentage of Hispanics with COVID-19 CR and CFRs did not follow any considerable spatial pattern. Spatial analyses are critical for taking more informed decisions, redirecting resources to the places that are being more severely hit by the pandemic. More research is needed to further investigate possible spatial relationships between minorities and COVID-19 CR and CFRs.
