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Monday, December 09, 2019 {{ new Date().getDay() }}

Photo by Gage Skidmore/ CC BY-SA 2.0

Reprinted with permission from DailyKos

It's been clear from the beginning that Donald Trump's no-mask, no-social distancing, no-common sense rallies were a very bad idea. Trump's very first COVID-era event in Tulsa took that city to record numbers. It also marked the very last public appearance of former Republican presidential candidate Herman Cain before he died of the virus. But then, Trump probably thinks that Cain had the wrong kind of genes.

There's been a lot of reporting about individual cases and clusters of COVID-19 associated with Trump's events. The number of cases associated with the Amy Coney Barrett introduction event, including Trump's own, was a vivid reminder of just what an awful idea it is to gather even a smaller group of people at a time when the pandemic is exploding across the whole nation.


But now researchers at Stanford University have turned Trump's rallies into a case study in wrongness. Looking just at rallies held between June 20 and Sept. 22, they came up with a total of 30,000 cases. That means Donald Trump isn't just ignoring the pandemic, or even encouraging herd immunity. He's the nation's single largest vector of disease.

The researchers worked entirely with data that's available to everyone—including the news media. They started with a list of Trump's rallies taken from a page on Wikipedia, then verified the time, date, and scale of each rally, using local news reports. They also specifically flagged the settings for those rallies, looking for those that were held inside, rather than on an airport tarmac.

Then they turned to COVID-19 data from the place that everyone seems to doomscroll 20 times a day: Johns Hopkins' Center for Systems Science and Engineering. But the researchers didn't just look at the bottom line and sigh; they used the latitude and longitude of each rally location and constructed a measure to surrounding counties. Then they did something others have also done, by compiling the data into weekly sets in an effort to minimize the noise created by daily variations in testing rate. To test their data, the researchers also created "fake rallies," selecting dates and locations where Trump did not have an event, and running the same kind of analysis for comparison.

After all this, what did they find?

Our results suggest that the rallies resulted in more than 30,000 incremental cases and likely led to more than 700 deaths.
[...]
Our analysis strongly supports the warnings and recommendations of public health officials concerning the risk of COVID-19 transmission at large group gatherings, particularly when the degree of compliance with guidelines concerning the use of masks and social distancing is low. The communities in which Trump rallies took place paid a high price in terms of disease and death.

The unsurprising results of the analysis are that not listening to health officials, holding large indoor events, refusing to wear masks at events, and crowding people together for hours in defiance of health guidelines is … bad.

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