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There are many nuanced reasons to dismiss this "analysis" but the headline to me is the claim that across the board the ratio has been 3 undetected : 1 detected case.

There are actual estimates of these numbers, and if whoever slapped together this Excel sheet was interested in reality they would have used them. E.g. https://covidestim.org/

Michael Droy

"If we believe the calculation, then the U.S. has sacrificed over half a million of our fellow citizens in the name of herd immunity. Is this the lesson of the Covid-19 pandemic?"
That is the dishonest way of describing it.
An honest assessment would be to estimate the life years lost.
Probably a couple of million.
Whereas how many extra life years are created by each year of normal economic progress and improved health services? 10 years increase Life expectancy in 60 years implies about 60 million years of life years gained per year, each and every year.
That is the basic QALY calculation that needs to put Covid deaths into context. And very crude numbers work very well for that.


MVE: I missed the column where they multiplied cases by 4 so yes they are using the assumption that only 25% of infections are detected. Given that we don't do random testing, how is that factor of 4 derived?

Now, the model used by that website is filled with assumptions as well, and they admit "As diagnostic guidelines loosen and testing availability improves, we expect to see more cases, though the underlying incidence of disease may or may not have changed. Lags in diagnosis, diagnostic delays, and changing diagnostic guidelines will all impact case reports, and bias estimates of Rt." Magically, they claim all these complications disappear when they look at new infections per day. I have no idea what they are talking about.

It's very sad to look at the cumulative infection curves at that site. It illustrates exactly my point about sacrificing lives.

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