Another censored (shadowbanned) Disqus comment at TheGatewayPundit


Silverman & Washburne are spectacularly wrong. From South Korean data (the best & most complete data we have), we can calculate that COVID-19 has a fatality rate of 2.5% 0.4% in the best of circumstances: i.e., with early detection and highly competent supportive care.

That's about twenty times as deadly as the typical seasonal flu.

And it is worse in most other countries, where diagnosis is typically spotty and tardy.

28 million U.S. cases would be an 8.5% infection rate. If that many Americans had really been infected, then nearly everyone would have been exposed by now. There would be no remaining large populations free of the disease.

If that were the case, then the sudden, explosive outbreaks seen when populations like nursing homes, ships & prisons are infected could not happen. They only happen because those large populations, of hundreds or thousands of individuals, start out with no infections at all. If 8.5% of the U.S. population had really been infected then there would be no remaining large, uninfected populations.

We can work backward from the number of deaths to estimate the number of people who were infected 10-14 days earlier. I did that arithmetic a couple of days ago. Here are my calculations (now 2.5 days out of date):

South Korea's mortality rate is 2.5 0.4%...

The U.S. currently has 678,210 known infections...

If we (optimistically!) assume that our true COVID-19 mortality rate is as low as S. Korea's, then our 34,641 COVID-19 deaths would imply that we had actually about 34,641 / 0.025 = 1,385,640 infections some period Td of time ago, where Td is the average amount of time from infection to death, for those who die of the disease. If Td is 10 days, that would mean that on April 7 we had 1,385,640 infections.

On April 7 we had 403,531 identified cases. 1,385,640 / 403,531 = 3.434, suggesting that we had about 2.4 unidentified infections for every identified case.

If, however, we (pessimistically) assume that our our true fatality rate is 4% (i.e., closer to the current naively-calculated rate of 5.11%), and Td = 10 days, then 34,641 / 0.04 = 866,025 infections on April 7. 866,025 / 403,531 = 2.146, suggesting that we had only about 1.1 unidentified infections for every identified case.

Since (unfortunately!) the U.S. currently tests few asymptomatic individuals, and about half of the people infected are thought to be asymptomatic, it is doubtful that the number of unidentified infections could be any lower than that.

However, if Td is 14 days, rather than 10 days, then the denominator is 247,729 (the known case count on April 2). A 2.5% mortality rate yields 1,385,640 / 247,729 = 5.59, suggesting that we had 4.59 undiagnosed infections for every identified case. A 4% mortality rate yields 866,025 / 247,729 = 3.50, suggesting that we had 2.5 diagnosed infections for every identified case.

That pretty much brackets the plausible range: between 1.1 and 4.6 undiagnosed infections for every identified case. Call it 2.85 1.75 undiagnosed cases per known case.

Assuming that ratio has not changed in the last 10-14 days (though it's actually probably come down a bit -- at least I hope so!), then our current known case count of 678,210 suggests that our true number of infected to date is 1.4 to 3.8 million, with a mid-range guess of 2.6 million = 0.8% of the American population.

As of this morning, the U.S. confirmed case count is up to 738,923, so scale up accordingly: i.e., best estimate now 2.8 million ≈ 0.85%.

In other words, Silverman & Washburne's estimate is too high by a factor of about ten.


See also:

ReasonRebellionAZ @az_reason  Apr 14
The title makes it seem more certain than it actually is. They hypothesize using state level data that some anomalous trends in influenza like illnesses (ILI) were actually COVID.