The proliferation of misinformation about the risk of COVID-19 has created headwinds on gaining an upper hand on the virus. Since the delta variant gave the nation a public health body blow in the summer of 2021, and with omicron waiting in the wings to possibly add more weight to this damage, schisms in belief in what is the truth have been ubiquitous.
The extreme points of view about the risks associated with COVID-19 are surreal. On one extreme, some believe that it is a deadly disease and that every precaution should be taken to prevent infections. On the other extreme, COVID-19 is like a common cold, furthered by false claims that government has created the spin to poison people with vaccines and invade personal freedoms.
NPR recently reported the results of a study that suggests that people in counties that strongly supported Donald TrumpDonald TrumpBiden heading to Kansas City to promote infrastructure package Trump calls Milley a ‘f—ing idiot’ over Afghanistan withdrawal First rally for far-right French candidate Zemmour prompts protests, violence MORE over Joe BidenJoe BidenChina eyes military base on Africa’s Atlantic coast: report Biden orders flags be flown at half-staff through Dec. 9 to honor Dole Biden heading to Kansas City to promote infrastructure package MORE in the 2020 presidential election were 2.7 times more likely to die from COVID-19 than those living in pro-Biden counties. “Strongly supported” means that Trump had 60 percent or more of the vote. The analysis points to political polarization and misinformation.
This makes for a great sound bite on social media. However, what does it mean?
The answer: not much.
When conducting data studies, one needs look “under the hood” at the data to gain an appreciation for the story that it tells.
First and foremost, association is not causality, as the study alludes to. Using data and identifying possible associations are exactly that, associations or statistical relationships. They do not provide the reason why two factors are related. In this case, strong pro-Trump counties are seeing more COVID-19 deaths per capita than pro-Biden counties. There is no reason to doubt this, and the data analysis support such an association. However, voting for Trump or Biden is just one indicator for the beliefs and values of the people in these counties.
A closer look at the election results reveals the picture of a divided America. Of the nation’s 3,184 counties, 2,564 supported Trump, while 520 supported Biden (as of Feb. 26, 2021). Yet Biden won over 7 million more votes. According to the Brooking Institution, 71 percent of the nation’s GDP was generated in pro-Biden counties. The majority of pro-Trump counties are part of rural America, with smaller populations and generally less affluent residents.
For example, the largest county that Trump won was Suffolk County in New York State, although his margin of victory was exceedingly small (0.03 percent), so it would not be considered a strong Trump county. The second largest was Collin County in Texas, with a 5 percent margin of victory, also not qualifying as a strong Trump county.
Deaths per capita can be problematic when comparing risk in sparsely populated rural counties versus densely populated urban and suburban counties. Death per capita obfuscates COVID-19 death risk, since in small counties, each death carries more per capita weight than in large counties. Sparsely populated rural counties also means that these people have fewer touch points with other humans, which may actually reduce their risk compared to people living in densely populated urban and suburban counties.
Using the outcome of the 2020 presidential election as an indicator for COVID-19 death risk is misleading. It creates a message based on an association but does not get to the root cause, which is where solutions typically reside.
We know that those living in rural areas are less likely to be vaccinated than those living in urban and suburban areas. From the Brookings data, one can infer that those living in counties that are more affluent are less likely to die from COVID-19 than those living in poorer counties. The NPR study could have been headlined with these factors rather than focusing on the voting trends in the 2020 election.
The takeaway from the NPR study is that it creates more division than unity. We know that people who are vaccinated, and more recently boosted, are less likely to die from COVID-19 than those who have remained unvaccinated. This is independent of where they live and who they voted for. It is a function of their perspective and their level of trust in medicine, science and government. Certain biases may lead them to have been Trump supporters, but how they voted is not the factor of interest.
COVID-19 has exposed a divided America, whether it is based on affluence, access to healthcare, education, geography or lifestyle. These factors certainly contribute to how people vote. Yet, focusing on their voting or political affiliation is a coarse indicator at best.
Sheldon H. Jacobson, Ph.D., is a founder professor of Computer Science and the Carle Illinois College of Medicine at the University of Illinois at Urbana-Champaign. He applies his expertise in data-driven risk-based decision-making to evaluate and inform public health policy.