Researcher ORCID Identifier


Graduation Year


Date of Submission


Document Type

Open Access Senior Thesis

Degree Name

Bachelor of Arts



Reader 1

Laura Grant


This paper examines the joint effect of political party affiliation and the urban landscape, as measured by access to parks, on case rates during the COVID-19 pandemic in the United States. The 2016 and 2020 U.S. Presidential Election returns are used as a proxy for a county’s political party affiliation prior to and during the COVID-19 pandemic. A county population’s spatial relationship to its parks encapsulates the green open space within an urban environment. The data set controls for features of the built environment, socioeconomic and demographic characteristics (race, gender, income, education), COVID-19 government regulations, and presidential election returns. Using an OLS model, I estimate how political party affiliation in the 2016 election and access to parks affect COVID-19 case rates. I conclude that Democratic counties are associated with increased case rates. I identify that greater park access in Republican counties is correlated with increased case rates. Using a regression discontinuity, I conclude that as 2020 Republican counties lean Democratic, case rates fall. While Democratic counties are correlated with lower case rates, as they lean heavily Democratic case rates rise. Greater park access is correlated with a slight increase in case rates prior to the 2020 election. The paper recommends that future research should define political party affiliation and the urban landscape at a more granular level and use pooled cross section or panel data.