Three Startling Findings from My Deep Dive into COVID’s Spread Across America
The pandemic’s deadly path from cities to farms — and from blue America to red
The coronavirus pandemic in the U.S. originated in the nation’s densely populated, left-leaning urban communities but spread to increasingly less dense suburban and rural regions, where the politics tend to lean right. My detailed analysis of COVID data provides clear evidence of the striking shift in the infection’s political colors–and demonstrates that the migration from blue to red America was more extreme than would be implied by geography alone. Instead, politics and related social attitudes bear much of the blame for COVID’s greater and more deadly march through red America.
The Context: COVID Rates Are Incredibly High Just About Everywhere
Here we go again. The third COVID-19 wave started in mid-September and quickly became the worst yet. That follows a disturbing pattern: each successive surge has been much worse than the preceding one. This latest wave crested just before Christmas, when the seven-day average soared to 230,000 cases, before easing back to under 220,000 (Figure 1) based on official government data via USA Facts. However, a post-Christmas surge like the one that commenced two weeks after Thanksgiving could push the rates back up to new records, particularly with the discovery of a new faster-spreading coronavirus variant.
Though the infection rates vary widely across the U.S., every type of community experienced surging caseloads this fall, from the densest cities to the most rural farmlands, before finally moderating last week (Figure 2).
Finding #1: COVID-19 infections were initially concentrated in Democratic-voting counties, but the share of cases in Republican counties now closely mirrors its underlying population share.
Democratic counties were home to almost three-quarters of people infected in the first weeks of the pandemic. But as the pandemic dispersed through the country, both the absolute number and the percent of cases in Republican-voting counties rose consistently to exceed that in blue counties (Figure 3). In the last three months of the year, more than half of all infections were in red counties — despite having less than half of the nation’s population.[*]
Overall, the share of infections in red and blue counties now nearly match their respective population shares: Red counties account for 48% of all confirmed cases throughout the pandemic, slightly exceeding their 46% population share.
More startling is how closely the infection rates correlate with the degree of partisanship in an area.[†] When cases mostly plagued urban areas during the initial spring wave, the pandemic was highly underrepresented in red counties and more concentrated in blue relative to their population sizes (left side of Figure 4). Moreover, the caseload closely correlates with the voting margin, whether blue or red: the larger the vote margin for the Democrat ticket, the greater the per-capita caseload and visa-versa. But the red-blue trend exactly reversed between the spring and fall: Now the relative caseload in the reddest counties exceeds its population share. In contrast, the bluest counties have below-average caseloads (right side of Figure 4).
Finding #2: Population Density Explains Part of the Partisan Split in COVID Cases. But We Must Also Blame Politics and Related Social Attitudes.
What accounts for these patterns and the sharp reversal over time? Geography clearly matters, especially population density. Since the virus transmits primarily through social interaction, it was inevitable that the nation’s most densely populated communities would be the first to incubate and spread the virus. As it happens, these large cities and urban counties generally lean left politically, so COVID-19 initially hit blue areas harder. Over time, infections spread to increasingly less dense suburban and rural regions, where the politics tend to lean right.
We can see this shift more clearly by comparing the relative infection rates in the initial spring wave versus the recent surge (left side of Figure 5). During the initial wave in March and April, the most rural counties’ case rate was just one-tenth of its population share. In sharp contrast, the ratio in the most densely populated counties was 40% greater than its population share. In other words, the per-capita case rate in big cities was 40% greater than the national average (a ratio of 1.4). Six months later, the trend has fully reversed (right side of Figure 5). The relative caseload in very rural counties now is 40% greater than their population share, and this ratio declines steadily with density. The case rate in the most densely populated counties is now less than its population share.
This geographic spread explains much of the political patterns in COVID cases. For example, more than 90% of “most rural” and “rural” counties voted Republican in the 2016 Presidential election, compared to less than 40% of the “most urban” counties.
But dig deeper, and it’s clear that more than geography alone matters. Consider the infection rates within the “suburban” counties (medium density). With 40% of all U.S. counties, this grouping presents the broadest cross-section of any density range. Though there was no evident trend in COVID infections by voting affiliation in the spring wave, a definite pattern emerges in the fall as the case rate increases with the Republican vote share (Table 1). In fact, there are similar patterns in virtually every density group covering 97% of the U.S. population: red counties consistently have higher infection rates than do blue counties for comparable population density levels, whether in cities or suburbs, though not in sparsely populated rural communities.
Thus, population density is only part of the story. Politics also plays a role. Residents of bluer counties have been more likely to follow public health guidance and thus experience generally lower infection rates than redder counties, where residents have been more resistant to this guidance. We know this because public surveys show greater support for public health measures among Democrats than Republicans. Similarly, consumer surveys show that Republicans are more likely to engage in activities — like eating in restaurants or going to the movies — that public health officials believe can raise the risk of contracting COVID. It’s also possible that blue areas learned from their early brush with COVID and thus adopted safer precautions against getting infected.
Whatever the specific behaviors, the data leaves little doubt that the incidence of COVID is higher in red American than in blue.
Finding #3 — COVID’s Charge Through Red American Has Been More Deadly
The COVID mortality rate — the percentage of cases resulting in death — dropped by about 80% from the spring to the fall, as the medical community learned how to better treat the disease. But the number of people dying from COVID each week keeps rising due to the surging infections. This scourge is hitting red communities especially hard (Figure 6). The early COVID-19 deaths were highly concentrated in the most densely populated blue counties. In the fall, however, COVID deaths surged in more rural Republican areas, while the per-capita death rate declined most significantly in the bluest areas.
Unfortunately, the death rates are climbing again in all areas but remain significantly elevated in red communities. Medical facilities are typically better and more widely available in large urban areas than in smaller rural communities, which likely explains some of the difference. But the more significant issue is simply that a greater share of people in red America is getting infected.
In short, COVID-19 started in America’s largest, bluest cities but ultimately spread more deeply through more rural red America — with deadlier consequences.
Notes: (1) This analysis is drawn from my more comprehensive study, also available on Medium, which has provides details on the data and assumptions that support the findings in this article. (2) Since I completed this analysis, the daily case rate has again surged to new higher levels in January following increased travel and family gatherings during the holidays. Though the share of cases in bluer communities has been rising again, most notably in the Los Angeles basin, overall the reversion so far is not material. I’ll return with another analysis once this winter wave finally recedes.
[*] The red/blue designations are based upon each county’s vote in the 2016 Presidential election. See additional explanation at the end of the article.)
[†] Highly partisan “deep red” and “deep blue” counties are those with at least a 10% voting margin, while the less partisan “light red” and “light blue” counties are those with less than a 10% voting margin.
