Economists' "super-spreader" study of the Sturgis motorcycle rally — was methodologically unsupported COVID nonsense

© 2020 Peter Free

 

10 September 2020

 

 

Eyebrows grow tired from being so frequently raised . . .

 

. . . by the United States' 100 percent inability to get a handle on COVID-19's true (not made up) epidemiology.

 

The latest blaring example of evidence-lacking "assumptionalizing" showed up in the following purported study.

 

It claims that the Sturgis Motorcycle Rally increased COVID's American impact by "263,708 additional cases" — at a cost of "$12.2 billion" in increased healthcare costs:

 

 

© 2020 Dhaval Dave, Andrew I. Friedson, Drew McNichols and Joseph J. Sabia, The Contagion Externality of a Superspreading Event: The Sturgis Motorcycle Rally and COVID-19, IZA Institute of Labor Economics (September 2020) (at page 30)

 

 

Notice the claim — "Superspreading event"

 

However, when we read the paper's too-casual methodology, we recognize that its investigation is the equivalent of piling one unproven assumption atop another.

 

 

Inadequate methods

 

The authors used anonymous cell phone data to trace the influx of motorcycling outsiders into Sturgis and then back again to their home grounds.

 

They too conveniently assumed that increases in COVID cases — subsequently reported by travel-receiving jurisdictions — had been entirely due to the Sturgis gathering.

 

No contact tracing was done.

 

Nor was any effort put into figuring out whether there might have been simultaneous reasons why COVID infections might have escalated, during the claimed super-spreading.

 

No medical investigation went into discovering actual morbidity and mortality figures accompanying the supposed phenomenon.

 

We are still left with no idea how potently infectious or medically "bad" (for randomly chosen people) SARS-CoV-2 is.

 

 

Adding Moron Insult to Imbecile Injury . . .

 

. . . is the authors' completely unsupported economics guess.

 

Twelve point two billion dollars is quite a large number, given how the authors do not know whether being infected with SARS-CoV-2 necessarily means being ill (it doesn't) or how much ill, if one is sick.

 

Nor do the authors know — even in approximated fashion — the comparative population distributions of those wildly differing possibilities. These unknown distributions have obvious relationships to healthcare costs.

 

This is bad thinking, even by Economics' long-demonstrated low standards.

 

 

The moral? — Sensationalized fluff from a team of medically ignorant economists

 

Nevertheless, their paper's poorly reasoned looseness did not keep it from being authoritatively quoted in the American Lamestream.

 

The Perfect Storm of American Demise continues.