Economists Say Sturgis Motorcycle Rally May Have Caused 250,000 Coronavirus Infections

South Dakota governor Kristi Noem and Johns Hopkins University researchers are skeptical about the massive infection numbers reported in the new study.

A motorcycle rider outside the Full Throttle Saloon during the 80th Annual Sturgis Motorcycle Rally in Sturgis
Michael Ciaglo / Getty Images

Smash Mouth seemed to think they could keep coronavirus away from their fans at the Sturgis Motorcycle Rally by throwing attitude at the pathogen. Unfortunately, economists—not epidemiologists or late 90s pop-punk hitmakers—crunched the cell phone data tracking user’s movements as well as recent COVID-19 case information to conclude that yes, the motorcycle rally might have caused up to 250,000 new infections. 

If that large figure makes you sit back and say, “wow,” don’t freak out just yet—this is an early estimate and neither epidemiologists nor government officials have come out agreeing with the number. 

Health economist Andrew Friedson tweeted about the study on Sept. 6. 

Along with three other economists Friedson authored a paper titled “Contagion Externality of Super-spreader” (PDF) for the Center for Health Economics & Policy Studies (CHEPS). According to his tweet, they estimated “that over 250,000 of the reported cases between August 2 and September 2 are due to the Sturgis Rally. Roughly 19 percent of the national cases during this timeframe.”

South Dakota’s conservative governor, Kristi Noem, was vocally skeptical. She issued a statement saying in part that the CHEPS report was “fiction.” 

“Under the guise of academic research, this report is nothing short of an attack on those who exercised their personal freedom to attend Sturgis,” Governor Noem said.

“Predictably, some in the media breathlessly report on this non-peer-reviewed model, built on incredibly faulty assumptions that do not reflect the actual facts and data. At one point, academic modeling also told us that South Dakota would have 10,000 COVID patients in the hospital at our peak. Today, we have less than 70. I look forward to good journalists, credible academics, and honest citizens repudiating this nonsense.”

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CBS News reported that researchers from prestigious Johns Hopkins University were skeptical of this research. Johns Hopkins Bloomberg School of Public Health statistician and associate dean Elizabeth Stuart reportedly reviewed the CHEPS  study and speaking to CBS MoneyWatch said, “Do I believe that number is 200,000 or more? I am not sure.”

Per CBS, here are the points Johns Hopkins reviewers made to mitigate the dramatic conclusions of the economists’ study:

  • The San Diego researchers didn’t compare geographic areas that were hit by coronavirus infections from Sturgis with other nearby areas. For example, a county in Arizona was compared to counties in Maine and Hawaii despite significant differences in the populations and mask-wearing habits of the two areas.
  • The Sturgis rally likely caused more people to get a coronavirus test given the numerous warnings before the event about the potential health risks. That increase in testing — not direct transmission from people at the rally — could explain the jump in reported cases.
  • The method used to put a public health cost of $12 billion on the Sturgis rally is simplistic because it fails to reflect that the costs of treating people with COVID-19 can vary widely around the country.

What’s at issue is not really whether there was an increase in cases so much as the size of that increase. Was it normal, considering the circumstances, or surprisingly huge?

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Study co-author Joseph Sabia said in an email to CBS that they believe “that the Sturgis Motorcycle Rally was the cause of this spike,” and the CDC “stated that large in-person gatherings of individuals who do not socially distance and who have traveled from outside the local area are at ‘highest risk’ for COVID-19 spread. The Sturgis Rally had all of these elements on steroids.”

Due to lagging indicators—statistics that take extra time to get factored into reports on events like this and could change the ultimate real infection statistics—the truth is we don’t entirely know the toll from any superspreader event. It may take years to truly nail down the coronavirus toll worldwide.