We estimate 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.
Scientists analyzed the Sturgis rally and the rise of #covid19 cases after people went back home. They estimated it led to over 260,000 cases.
Assuming a cost of $46,000/case, the authors estimated the rally cost $12.2 billion. “This is enough to have paid each of the estimated 462,182 rally attendees $26,553.64 not to attend,” they write.
Dave DM, Friedson AI, McNichols D, Sabia JJ. The Contagion Externality of a Superspreading Event: The Sturgis Motorcycle Rally and COVID-19. September 2020. The Contagion Externality of a Superspreading Event: The Sturgis Motorcycle Rally and COVID-19
Large in-person gatherings without social distancing and with individuals who have traveled outside the local area are classified as the “highest risk” for COVID-19 spread by the Centers for Disease Control and Prevention (CDC).
Between August 7 and August 16, 2020, nearly 500,000 motorcycle enthusiasts converged on Sturgis, South Dakota for its annual motorcycle rally. Large crowds, coupled with minimal mask-wearing and social distancing by attendees, raised concerns that this event could serve as a COVID-19 “super-spreader.”
This study is the first to explore the impact of this event on social distancing and the spread of COVID-19.
First, using anonymized cell phone data from SafeGraph, Inc. we document that
(i) smartphone pings from non-residents, and
(ii) foot traffic at restaurants and bars, retail establishments, entertainment venues, hotels and campgrounds each rose substantially in the census block groups hosting Sturgis rally events.
Stay-at-home behavior among local residents, as measured by median hours spent at home, fell.
Second, using data from the Centers for Disease Control and Prevention (CDC) and a synthetic control approach, we show that by September 2, a month following the onset of the Rally, COVID-19 cases increased by approximately 6 to 7 cases per 1,000 population in its home county of Meade.
Finally, difference-in-differences (dose response) estimates show that following the Sturgis event, counties that contributed the highest inflows of rally attendees experienced a 7.0 to 12.5 percent increase in COVID-19 cases relative to counties that did not contribute inflows. Descriptive evidence suggests these effects may be muted in states with stricter mitigation policies (i.e., restrictions on bar/restaurant openings, mask-wearing mandates).
We conclude that the Sturgis Motorcycle Rally generated public health costs of approximately $12.2 billion.
Using similar methods, some of the same authors found no evidence of a superspreader event at Trump’s Tulsa rally.
Dave DM, Friedson AI, Matsuzawa K, McNichols D, Redpath C, Sabia JJ. Risk Aversion, Offsetting Community Effects, and COVID-19: Evidence from an Indoor Political Rally. National Bureau of Economic Research Working Paper Series 2020;No. 27522. Risk Aversion, Offsetting Community Effects, and COVID-19: Evidence from an Indoor Political Rally
The Centers for Disease Control and Prevention (CDC) deems large indoor gatherings without social distancing the “highest risk” activity for COVID-19 contagion. On June 20, 2020, President Donald J. Trump held his first mass campaign rally following the US coronavirus outbreak at the indoor Bank of Oklahoma (BOK) arena.
In the weeks following the event, numerous high-profile national news outlets reported that the Trump rally was “more than likely” the cause of a coronavirus surge in Tulsa county based on time series data.
This study is the first to rigorously explore the impacts of this event on social distancing and COVID-19 spread.
First, using data from SafeGraph Inc, we show that while non-resident visits to census block groups hosting the Trump event grew by approximately 25 percent, there was no decline in net stay-at-home behavior in Tulsa county, reflecting important offsetting behavioral effects.
Then, using data on COVID-19 cases and deaths from the CDC and a synthetic control design, we find little evidence that COVID-19 grew more rapidly in Tulsa County, its border counties, or in the state of Oklahoma than each’s estimated counterfactual during the five-week post-treatment period we observe.
Difference-in-differences estimates further provide no evidence that COVID-19 rates grew faster in counties that drew relatively larger shares of residents to the event.
We conclude that offsetting risk-related behavioral responses to the rally — including voluntary closures of restaurants and bars in downtown Tulsa, increases in stay-at-home behavior, displacement of usual activities of weekend inflows, and smaller-than-expected crowd attendance — may be important mechanisms.