Politics and COVID: Exploring the Complex Relationships between Partisanship, Policies, and COVID-19 Health Outcomes

Background and purpose: A surge of partisanship in the US is significantly influencing policymaking at the state level, resulting in wide variation in public health policies and healthcare access. These dynamics were prominent in state-level responses to the COVID-19 pandemic, with heated partisan debate about adoption of prevention strategies such as mandatory mask-wearing and vaccination requirements. Although these debates were covered widely by mainstream media, there is little exploration in scientific literature about the relationships among the political leanings of policymakers, their COVID-19 policy responses, and the resulting health impacts within states. To explore these relationships, we analyzed data about the public health measures utilized by state governments to assess a) whether certain policy approaches were associated with health outcomes, and b) whether political leanings in the states changed the relationship between policy approaches and health outcomes.

Methods: Measures of state-level policy approaches were collected from NYU’s Center for Urban Science and Progress (CUSP). Policies included duration of state of emergency declarations, movement restrictions (e.g., stay-at-home orders), individual-level interventions (e.g., mask and vaccine requirements), and income supports (e.g., temporary paid leave, unemployment benefits). Measures of 2020 voting patterns came from Dave Leip’s Atlas of U.S. Presidential Elections. Health outcomes data included the CDC’s measures of excess deaths, COVID hospitalizations, and COVID cases. All data were from 2020 and 2021. We used exploratory factor analysis to identify salient categories of policies, and cluster analysis to understand how these policy categories and state political leanings were associated with health outcomes in the different states.

Results: Significant clustering was detected among the states, with three clusters emerging as most salient in most analyses. For instance, when exploring associations of politics and policies with excess deaths, three distinct, statistically significant clusters emerged. For instance, Democratic-leaning states generally had lower rates of excess deaths, and among those states, longer durations of a state’s state of emergency were associated with lower rates of excess deaths (p<0.0001; R²=0.545). Interestingly, among Republican-leaning states, two clusters emerged in most cases, with one cluster representing states that experienced wide variation in excess deaths despite choosing not to adopt a given policy approach—e.g., never implemented a mask mandate (p<0.0001; R²=0.572)—and another cluster of states with high levels of excess deaths regardless of the length of a policy’s implementation.

Conclusions and implications: Despite existing evidence about the efficacy of interventions such as vaccinations and mask wearing, we found wide variation in adoption of these policies across the states. Political leaning in the state was strongly predictive of those policy choices, as expected, but politics did not fully explain differences in health outcomes. Our findings indicate that even within more conservative states, there was variation in the implementation of preventive policies and in the resulting health outcomes. Social workers focused on reducing health disparities, especially in communities with inequitable exposure to public health risks, need to be aware that opportunities for public health advocacy remain salient despite the strong role of partisanship in policy decisions.