61–70 of 73 posts
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"Your honor, the man didn't die because I pushed him down the stairs, he died because he hit his head against a wall at the bottom of those stairs.".
In the US if he tested positive for COVID after death, he would have been recorded as a COVID death. Not even joking.
I've been looking at the infection rates in the US falling over the past few weeks, and I'm wondering if it's because we achieved herd immunity for the current r0, people changed their behavior when they saw cases rising, or fewer people are getting tested because with the lag in processing time, a positive result isn't actionable.
You're looking at garbage data. The data has never been accurate or consistent.
> 108,689 (95% posterior predictive interval [95% PPI]: 1,023 to 14,182,310) So between 1000 and 14 million. Got it.
Not all of those numbers are equally likely though.
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The way that the areas that are now most resilient are the same areas with high population density which were hit very hard early on (NY, NJ, for example) tells me that we have somehow hit herd immunity. There is some evidence coming out that other coronaviruses (which cause the common cold) could have causes immunity in some unknown percentage of the population, meaning the percentage of SARS-CoV-2 infection require…
The herd immunity threshold depends on behavior. It may be at 30% infected when the population is wearing masks and social distancing, but could be 70% if restrictions are removed. I agree that parts of New York City have probably reached herd immunity for current behavior patterns, so restrictions can probably be slightly relaxed, but 70% of the population is still vulnerable to infection, so you can't throw caution…
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It's not that hard to work backward from the observed fatality rate and the death curve to the infection curve two weeks ago. That's basically all they're doing in this paper. 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…
Not 2000 cases, 200 cases (1 / 0.53%). If it were 2000 cases then 40 million new yorkers got COVID (which is larger than the population of NYC). 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.
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The herd immunity threshold depends on behavior. It may be at 30% infected when the population is wearing masks and social distancing, but could be 70% if restrictions are removed. I agree that parts of New York City have probably reached herd immunity for current behavior patterns, so restrictions can probably be slightly relaxed, but 70% of the population is still vulnerable to infection, so you can't throw caution…
It also depends on interconnectedness of social networks. If the 30% that had it is highly concentrated in one sub group, then you might see low rates now, but high rates when groups start intermingling. Herd immunity at a national level won't save nursing homes, because almost by definition, there won't be herd immunity in that local community.
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Well sure, and that is a perfectly valid comment at the micro level. However, we can relatively clearly see that the COVID-linked death reporting is under-reported from mortality baselines. Therefore it's highly likely that for a given death it is more likely to be incorrectly categorise as non-COVID when COVID was responsible, than to be incorrectly designated COVID.
For contrast the UK overcounted its COVID deaths https://www.washingtonpost.com/world/britain-says-it-overcou...
Here is some data here on excess deaths: https://www.economist.com/graphic-detail/2020/07/15/tracking...
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Not 2000 cases, 200 cases (1 / 0.53%). If it were 2000 cases then 40 million new yorkers got COVID (which is larger than the population of NYC). 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.
you have completely missed the point. You cannot compare the number of current deaths with the number of current infections without taking into consideration the rate at which the virus is spreading. 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…
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.
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Get an IgG antibody test if you want to know, should still be visible there
It isn’t a fully reliable test though. There are both false positives and false negatives.
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The herd immunity threshold depends on behavior. It may be at 30% infected when the population is wearing masks and social distancing, but could be 70% if restrictions are removed. I agree that parts of New York City have probably reached herd immunity for current behavior patterns, so restrictions can probably be slightly relaxed, but 70% of the population is still vulnerable to infection, so you can't throw caution…
It also depends on interconnectedness of social networks. If the 30% that had it is highly concentrated in one sub group, then you might see low rates now, but high rates when groups start intermingling. Herd immunity at a national level won't save nursing homes, because almost by definition, there won't be herd immunity in that local community.
In the US, there's been some push for more national action around preventing/managing the spread of covid. While I agree that more national leadership is needed, and standard guidelines around reporting and degrees of "open" would be helpful, the US is so diverse a nation-wide lockdown never made sense, and there are enough complicated factors that the decision really has to be made at local levels.
