AUTHOR=Nkouaga Florent TITLE=Exploring the link between public health compliance and voting patterns in the 2020 U.S. presidential election JOURNAL=Frontiers in Political Science VOLUME=Volume 6 - 2024 YEAR=2024 URL=https://www.frontiersin.org/journals/political-science/articles/10.3389/fpos.2024.1370243 DOI=10.3389/fpos.2024.1370243 ISSN=2673-3145 ABSTRACT=Introduction

The COVID-19 pandemic has significantly impacted society and politics, particularly in the context of the 2020 U.S. presidential election. Public officials' unpreparedness resulted in skepticism regarding government responses. Additionally, health inequities and political polarization profoundly influenced voter attitudes and behaviors.

Methods

This study employs statistical techniques to examine voting patterns, leveraging data from the 2021 African American COVID-19 Vaccine Polls (AACVP) alongside the 2020 Collaborative Multiracial Post-Election Survey (CMPS). Specifically, it utilizes logistic regression and t-tests to dissect and understand the dichotomous electoral decisions made by voters between Donald Trump and Joe Biden in the U.S. presidential election. The research analyzes the nuances of the electorate's behavior by considering many factors that may influence the binary vote decision.

Results

T-tests revealed significant mean differences in voting patterns based on public health compliance, with less compliant individuals more likely to vote for Trump and more compliant individuals favoring Biden. Logistic regression analysis showed a substantial statistical correlation between public health compliance and voting preferences, independent of confounding variables.

Discussion

The study confirmed that public health compliance during the pandemic impacted voting behavior, with a divide based on attitudes toward health measures. This reflected broader societal divisions, suggesting that public health behaviors are linked with political identities. Additionally, media sources and racial identity significantly influenced voting decisions.