It's worth noting that the German study in Gangelt was done because it was considered a hot-spot - this wasn't an attempt to estimate the infection rate across the country. It does however demonstrate that even in places where lots of people have had it, herd immunity still looks a long way off.

It is worth noting indeed.

However, if we apply the estimated mortality rate (0.37%) based on that to 11500 deaths in hot-spot New York, it would amount to over 3 million cases, again roughly 15% of the population.

Now perhaps Germans are so much healthier and their healthcare is so much better, making their real mortality rate so much lower. It's all speculation at this point, either way.

It wasn't a study of representative German households, but just those in a Gangelt. A small town that was basically the ground zero for the epidemic in Germany. Those numbers do not generalize to Germany as a whole, let alone other countries.

Also, the particular antibody tests they used appears to have a much higher FP rate than they claimed. Another study found 4% FPs rather than <1% like the press release for the Gangelt testing claimed.

It does generalize to my point, because we're talking about the basic reproduction number of the virus. It is not supposed to vary dramatically across populations.

If COVID-19 can spread to 15% of that particular population within that timeframe, and the estimate of a basic reproduction number of 2-3 predicts that this is not possible, then the estimate must be wrong.

> Also, the particular antibody tests they used appears to have a much higher FP rate than they claimed. Another study found 4% FPs rather than <1% like the press release for the Gangelt testing claimed.

Perhaps, but that doesn't put much of a dent into the results.

R0 isn't a fundamental constant, but just an estimated average. It's affected both by human behavior and random chance. In this case, the town had a very early superspreader event, which shifted them far ahead of the curve.

A FP rate that high will make a very significant difference in the results. (How large a difference depends on whether the 15% is a raw number or if it's been adjusted based on the expected test specificity and sensitivity. One would hope nobody would just report the raw numbers. But since all we've gotten from this study is basically a press release, expecting scientific rigor seems ill advised.)