The media have given us a stereotype of the Americans most likely to have contracted the coronavirus. You probably think of COVID-19 as a disease primarily affecting the country’s urban poor. You have probably also read the news that African-Americans, and possibly Latinos, have been stricken at a rate higher than their percentage of the population. These generalizations are accurate, but things are changing.
In a brief paper, Dr. William Frey of the Brookings Institution analyzed date compiled by the New York Times in order to compare the demographic characteristics of those counties hardest hit by the virus at different points in time.
In the above chart, the second bar from the left shows the characteristics of those counties with an infection rate of 100 or more per 100,000 population as of March 29. The bar at the left shows the population baselines. As you can see, the hardest hit counties were more likely to be in the Northeast, more urban, and more likely to have voted for Hillary Clinton in the 2016 election.
The next three bars show the characteristics of the new counties that reached the 100/100,000 rate during each of the next three weeks. These counties are increasingly located in the West, South and Midwest, they are more suburban and rural, and they are more likely than the early counties to have voted for Trump. In other words, the counties that are most affected by the coronavirus are gradually coming to resemble the demographics of the country as a whole.
This table shows a similar picture. Majority-white counties are catching up with counties with more minorities. The newly-affected counties are less likely to have a large immigrant population. The income data, however, are less consistent with the media stereotype, since the early counties contain more higher income people. I assume this is because the virus first took hold in cities with high income inequality like New York and Seattle. Over time, however, the income distribution is starting to resemble the baseline for the country.
These demographic shifts seem likely to have political implications. At the very least, white rural Republicans are not going to be able to dismiss the pandemic as somebody else’s problem. Frey suggests that they will become less receptive to Trump’s attempts to reopen American businesses. Fear of mortality will spread. In the past, such external threats have tended to help conservative candidates, but the situation is far too volatile to make a one-sided prediction. Will some people who voted for Trump in 2016 blame him for not keeping the danger away from their community?
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