Relationship between Socio-Demographics and COVID-19: A Case Study in Three Texas Regions

Abstract

The COVID-19 is a global pandemic and crisis of public health. Although studies investigate the spatial factors of COVID-19, most of them are based on the macro-level. There is a rising demand to examine the emerging patterns of socio-demographic and COVID-19, especially for preventing the second-peak of COVID-19 outbreaks. This study was based on the recent release of zip code level data of COVID-19 and explore spatial relationships between socio-demographics and COVID-19 density through ordinary least squares (OLS) and geographically weighted regression (GWR). OLS results indicate that rates of poverty, rates of African Americans, and rates of Hispania were influential factors. Results of GWR are complementary to the OLS results. They suggest that associations between socio-demographics and COVID-19 density should be various in different postal areas. We argued that socio-demographics could play significant roles in COVID-19 outbreaks, which may be evidence that socio-demographic disparities happened during the COVID-19 crisis. We suggested that policymakers work on implementations involving interventions and prevention based on different priority levels. Also, it may be more productive for policymakers to implement strategies depending on local situations instead of globally.

Note: Funding: This project was supported by the Good System Grand Challenge and the Cooperative Mobility for Competitive Megaregions (CM2) center both at The University of Texas at Austin. Declaration of Interest: None to declare

Keywords: COVID-19, Geographically Weighted Regression, Socio-demographic disparities, Neighborhood, GIS