In the very article you link to the case of New York is mentioned by Bergstrom, specifically to critique that estimate, and point that New York disproves it.
I verified that claim:
We know that the antibody tests in NYC gave the estimate of "all infected" of 20% of all. But there were around 20K deaths, and NYC has 8.3M population. Also even if we expect that the spread will stop once the 70% of population is infected the result is: 100e3 * 0.7 / 8e6 = 0.87%
Still much more than 0.4%. That it's closer to 1% matches all the statistics of the countries of the world that did a lot of testing compared to the number of cases and deaths.
Back to the article:
Bergstrom in the article: "Given that these parameter sets underestimate fatality by a substantial margin compared to current scientific consensus, this is deeply problematic."
In the same article, even CDC disclaims that their numbers are predictions:
"The scenarios are intended to advance public health preparedness and planning. They are not predictions or estimates of the expected impact of COVID-19" the CDC says.
So it seems you intentionally misinterpret CDC, given that it's all in the very article you linked.
I verified that claim:
We know that the antibody tests in NYC gave the estimate of "all infected" of 20% of all. But there were around 20K deaths, and NYC has 8.3M population. Also even if we expect that the spread will stop once the 70% of population is infected the result is: 100e3 * 0.7 / 8e6 = 0.87%
Still much more than 0.4%. That it's closer to 1% matches all the statistics of the countries of the world that did a lot of testing compared to the number of cases and deaths.
Back to the article:
Bergstrom in the article: "Given that these parameter sets underestimate fatality by a substantial margin compared to current scientific consensus, this is deeply problematic."
In the same article, even CDC disclaims that their numbers are predictions:
"The scenarios are intended to advance public health preparedness and planning. They are not predictions or estimates of the expected impact of COVID-19" the CDC says.
So it seems you intentionally misinterpret CDC, given that it's all in the very article you linked.