Neighborhood Conditions and the Initial Outbreak of COVID-19: The Case of Louisiana

Abstract

The early outbreak of COVID-19 became associated with various “hot spots” in the United States, particularly in large cities. However, despite the widespread nature of the outbreak, much of what is known about the virus’ impact and clusters is understood either for individuals, or at the state level. There are likely to be underlying differences within states and counties that predict higher rates of the disease and can help policymakers to understand why certain communities have been harder hit. Neighborhoods are smaller spatial units where residents spend their time, particularly during a quarantine, but more importantly neighborhoods shape their social circles, movement, and identities, therefore differences across neighborhoods are likely to be reflected in counts of COVID-19, as well. Using data from the Louisiana Department of Health, our contribution is the first to analyze the case count through May 3, 2020 at the census tract level and its relationship to individual and geographic neighborhood characteristics. We find a particularly high association between race and COVID-19 cases, as high minority share neighborhoods show a positive association, robust to model specification and spatial autocorrelation. In addition, neighborhoods with lower rates of poverty and those with fewer residents over 70 have fewer cases. We conclude with a discussion of the implications of the findings for health professionals, policymakers, and individuals given the continuing importance of the neighborhood context.

Note: Funding: None to declare

Declaration of Interest: None to declare

Keywords: COVID-19, Neighborhoods, Pandemic, Transmission, Health