As much as I do feel COVID is a real threat and that the Sturgis Motorcycle Rally probably helped spread it somewhat, this paper (and even more so, the article) far overstates the case.
Copying over some key points from the underlying paper :
> In counties with the largest relative inflow to the event, the per 1,000 case rate increased by 10.7 percent after 24 days following the onset of Sturgis Pre-Rally Events. Multiplying the percent case increases for the high, moderate-high and moderate inflow counties by each county’s respective pre-rally cumulative COVID-19 cases and aggregating, yields a total of 263,708 additional cases in these locations due to the Sturgis Motorcycle Rally. Adding the number of new cases due to the Rally in South Dakota estimated by synthetic control (3.6 per 1,000 population, scaled by the South Dakota population of approximately 858,000) brings the total number of cases to 266,796 or 19 percent of 1.4 million new cases.
> If we conservatively assume that all of these cases were non-fatal, then these cases represent a cost of over $12.2 billion, based on the statistical cost of a COVID-19 case of $46,000 estimated by Kniesner and Sullivan (2020).
The Kniesner and Sullivan paper cited  gets to the value of $46,000 by using the Department of Transportation's "value per statistical life" of about $10 million per death (scaled down to ~$11k per asymptomatic case), which is not a public health cost estimate. It's probably far higher than what hospitals and the health system spends per case.
Not only that, but the paper claims, without any controls, that ALL case count increases in counties that sent lots of people to the Sturgis Motorcycle Rally in the weeks following it were caused by the Rally itself. They did not control for any other factors (e.g., the baseline spread of COVID in adjacent counties with lower attendance.) This is unplausible, given that other factors and events (e.g., college parties, indoors dining) may have also contributed.
The authors spend 15 pages or so describing the calculations, its limitations, and alternative calculations.
Focusing on one parameter to throw out the whole paper would be junk science.