Trends in Florida’s 2020 COVID-19 Experience: Politics

by Patrick Bernet and Leighton Dupree


Pandemics travel through social connections, testing the mettle of communities.  Arriving amidst a contentious presidential campaign, COVID-19 became part of the rhetoric, polarizing communities at a time when a shared commitment was most needed to save lives. Offering 29 electoral votes and polling as the closest contest among the five largest states, Florida received a disproportionate share of partisan messaging. Such attention has implications beyond the ballot, as a county’s political choice joins population age structure, and race, ethnicity, and nativity as community characteristics related to COVID-19 infections, emergency department (ED) use, hospitalizations, and deaths.

A tale of two Floridas

Florida is a collection of 67 counties, running the range of demographic, economic, social, and political spectrums. Viewed through the prism of 2020 presidential voting reveals the depth and breadth of these differences (Table 1). Drawn from Florida’s largest metropolitan areas, the 12 counties that voted Democratic are collectively more populous (12.5 million) than the 60 counties voting Republican (8.8 million). The Republican counties have higher proportions White non-Hispanic (71% compared with 41%), half the share of Blacks (10% versus 19%), less than half the share of Hispanics, and just one-third the proportions foreign born. Republican counties are also much older, with 26% aged 65 or over.

Sources: (1) COVID-19 cases through 12/31/2020 from the Florida Department of Health. (2) American Community Survey population demographics to compute rates per 100,000 and population proportions for [Population Measure] subgroups. (3) 2020 Presidential vote county tallies from the Florida Department of State. (4) 2018 County Health Rankings & Roadmaps.

Democratic counties are economically stronger, with higher proportions educated beyond high school (66%), and higher median household incomes ($53,899 versus $52,602). They did, however, also have higher poverty rates (14.0%). Republican counties came into the pandemic in generally worse health, with higher rates of smoking (17%), higher proportions reporting poor health (19%), and a lower life expectancy (79). Being much more rural, Republican counties also have lower primary care physician access (82 per 100,000 compared to 98).

As a group, Republican counties have significantly lower COVID-19 infection rates overall (5,346 per 100,000 compared with 7,078). Despite lower infection rates, Republican counties suffer COVID-19’s more severe consequences in elevated ED, hospitalization, and mortality rates (505, 333, and 109 per 100,000, respectively). Extending the chain of consequences, this means the odds of elevated severity are higher in Republican counties, with 9.4% of infections associated with ED visits, 6.2% of infections associated with hospitalization, and 2.0% of infections associated with death. Viewed another way, there is an average of 1 death for every 75 infections in Democratic counties, but it takes just 50 infections in Republican counties.

Turning finally to politics, the Republican candidate won the state of Florida through a combination of strong margins in Republican counties (61% compared with 56% in Democratic counties) and less severe losses in Democratic counties (43% compared with 38%). While the Democratic party successfully increased voter support in both Republican-won and Democrat-won counties (26% and 14%, respectively), the Republican party surpassed them in both (33% and 18%). This large increase indicates the high levels of political energy among voters and the volume of partisan messaging such enthusiasm might draw.

A vote by any other name

Stark differences between Republican and Democratic counties along many dimensions serve as testament to the skills of political strategists in identifying shared characteristics within different communities, then constructing a platform with a broad enough appeal to win. Touchstone attributes, such as age and race, also have a relationship with COVID-19 outcomes as demonstrated in the relationship between county infection and mortality rates (Figure 1). The overall upward slope intuitively shows that counties with more infections proportionately see more deaths. And variance above and below the statewide average diagonal line shows, for example, that counties with infection rates near 6,000 cases per 100,000 have mortality rates ranging from 50 to 150 per 100,000. Looking for explanations of this variance, the levels of key variables are noted on each quadrant. For example, while age is associated with lower infection rates, it does not dictate mortality rates (age is similar in both quadrants 2 and 3). On the individual level, age is most certainly a risk factor, but at the county level it does not explain enough. Viewed from race, income and rurality perspectives results in similar paradoxes, each capable of explaining only a part of the pattern.

Figure 1. Community Characteristics and COVID-19 Infection and Mortality Rates

In addition to the association of vote tallies with easily measured characteristics such as those catalogued in Table 2, voter choice may also serve as an indicator for latent values, such as the value placed on the health of community and family. When the same points are viewed through a political perspective another relationship emerges (Figure 2). The Democratic counties (lighter blue) never appear on the upper edge of the line, meaning these counties have low-to-medium mortality rates at any given level of infection. Like the other variables, political choice does not explain all variance, but it adds to that understanding.

Figure 2. COVID-19 Outcomes and Related Community Characteristics

Recalling the large upswing in political participation for the 2020 elections (Table 1), Floridians received increasingly partisan messaging, much from a Republican governor and president who often strayed from CDC recommendations. If one of the latent attributes revealed in voter choice includes skepticism about science, the example set by unmasked leaders seems reckless given that Republican counties are predisposed to harsher outcomes by virtue of older age and worse health.

The interactivity of Figure 3 allows comparing COVID-19 infection, ED, hospitalization, and mortality outcomes against potential determinants, including age, race, ethnicity, nativity, and infection rates. Each point can be further classified by political choice, race, and age, adding depth to lessons learned thus far. The scatterplot structure of this analysis tool reinforces the core message in this trilogy of postings regarding COVID-19 outcomes in Florida: a community’s age, race, ethnicity, nativity, and political choices all help explain pandemic history when considered one at a time. But accounting for their interaction provides a much deeper level of understanding. That depth can help guide subsequent efforts to flatten ever-higher waves and allocate vaccinations to areas where they’ll save the most lives.

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Patrick Bernet, PhD

Patrick Bernet, PhD, is an Associate Professor at Florida Atlantic University. Dr. Bernet researches pregnancy outcomes, focusing on disparities, program cost effectiveness, and the impact of bias on health from the perspectives of behavioral economics and financial analysis. He also studies the demographics of the COVID-19 pandemic. In addition to Dr. Bernet’s research, he also serves on maternal and child health committees in both Broward and Palm Beach counties and is a volunteer Medicare insurance counselor.

Leighton Dupree

Leighton Dupree is a student in the Master of Health Administration program at the University of Kentucky. His experience involves the intersection of data analytics with healthcare systems and public health.