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 Trump over Joe Biden 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...
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