Interesting. An estimate that infections were multiple orders of magnitude higher than detected in mid-March is higher than I'd heard before, although I suppose it's probably implied by the "basically everyone in New York caught it" theory.
What is the reason behind this?
I've seen a few papers testing asymptomatic patients (identified by contact tracing or other mass testing), with mixed results. NYC uses an in-house test for which I don't believe any paper exists, so I don't think we can say anything there. The IFR from NYC's serology is higher than most other estimates, which could imply under-ascertainment but could also be real (e.g., because they forced nursing homes to accept positive patients, because they were doing early intubation that we now know is harmful, etc.).
What recent studies have shown is that while the naive herd immunity threshold is perhaps around 60% (working backwards from R0 estimates), after you factor in clustering of populations, baseline hygienic improvements, and moderate social distancing, that NY did reach an effective level of herd immunity.
I would not be surprised if it were much higher.
It does not suggest that everyone in new york caught the virus. Just that in the early days of the pandemic, when schools were open and no one knew about the virus, the model for growth was exponential with about a 25% increase in cases per day, the best estimate for the number of infections was 2^(14/3)*(1/1.5%)x deaths. Each death corresponded to about 2000 cases.
Back of the envelope based on this
* https://www.cdc.gov/nchs/nvss/vsrr/COVID19/
* https://science.sciencemag.org/content/368/6498/eabd4246
* https://worldpopulationreview.com/us-cities/new-york-city-ny...
-> about half of NYC has been infected.
At the beginning, the rate at which the number of deaths was growing was 26% per day, or doubling approximately every 3 days. This means that in the two weeks that it takes for the average person that is going to die of covid to die of covid, the number of people infected has grown by a factor of 2^4 to 2^5. So by the time that 30 people have died, It is reasonable to suspect that that the number of infections had grown by an order of magnitude since those people were infected, and those people are 1.5% of the people who had been infected two weeks ago. (This back of the envelope calculation is very sensitive to changes in the time to death distribution for people who have contracted covid, particularly to number of people that die fast.)
Furthermore, your infection fatality ratio is entirely wrong. My 1.5% was very optimistic. South Korea has the most exhaustively tested population on earth, and their case fatality rate is 2%, and it's worse among cases that have reached an endpoint. The virus could have mutated and attenuated since then, but other evidence suggests that the New York strain was more lethal than the SK strain, not less.
The Sciencemag paper that you have linked relies on a "seroprevalence of 3%", despite the parenthetical statement right next to their assumption that the confidence interval on that seroprevalence is between 0 and 3 percent. So not only have they chosen the maximum value for seroprevalence in that interval as their assumption, but the interval actually includes zero. Antibody testing cannot say with 95% confidence that any of its positive results were not false positives. That's a pretty bad test.
You don't like that fatality rate, so be it, but which one you believe in is all that really matters for this exercise given the virus spread <-> delay till death is not a huge factor at the moment in NYC.
Korea's CFR is 2.3%, the IFR 0.2%. Some special countries which could not protect the elderly have much higher IFR's of 1 - 1.5%. Remember, the IFR is 10% for over 80 years and neglectable for everybody under 50.
So far there's no evidence on different strains, but lot of evidence of different policies leading to the differences. Esp. for Belgium, Spain, Italy, US and Brazil to name the worst.
https://www.medrxiv.org/content/10.1101/2020.07.23.20160895v...
What's the theory on why other places that were hit hard early are still quite high...like California? Lower density?
The theory is that California flattened the curve in the original sense, delaying the peak in order to ensure it's moderately lower and protect the capacity of the healthcare system.
http://91-divoc.com/pages/covid-visualization/?chart=states-...
The takeaway to me is that unless you are willing to exert extremely strict border controls, localized quarantines and hard lockdowns of hotspots, and pervasive test & trace, indefinitely, then you wont keep Rt below 1 without the benefit of some herd immunity.
Hence lockdowns should either be as minimal as possible, encouraging low-risk populations to be out and about while high-risk populations shelter.... Or, you need an extreme and extraordinary response until widespread effective vaccination.
Small island nations may find they can choose the second path (although it’s not guaranteed, Hawaii has recently failed at it) but the vast majority of the world should choose the first.
And we should stop politicizing it, because largely everyone is in the same boat and will hit all the same endpoints.
The worst hit me on the weekend and I returned to work on Monday with the cough.
Around 1 week prior I attended a company holiday party at a large museum with (probably?) one thousand attendees from all over the world. They mostly came from the EU, but at least some from APAC as well.
I have no evidence that this was COVID-19, but in retrospect the symptoms matched reasonably well and I haven't been sick since.
In civilized countries the PCR test is free for critical cases (like travelling abroad or in contact with a positive), or 60 EUR if not.
That might explain why your sample is (potentially) not representative of the overall city or state.
The CDC officially became aware of coronavirus on Jan 1, and the first documented case in the USA was Jan 20. Now, we could have all had the flu, but really the flu doesn't have such a horrible deep chest cough like we all had in my opinion.
Given that some people say coronavirus was circulating as early as November 2019, I think we all had something more than the seasonal flu. By march 2020, the only people I knes who were sick were in nursing homes.