4 ms·

> The IFR for Covid-19 was not 2.6%. Less than a tenth of that, actually If we take the number of Covid deaths for, for example New Jersey (the whole state) or

by sampo 2y ago

> The IFR for Covid-19 was not 2.6%. Less than a tenth of that, actually If we take the number of Covid deaths for, for example New Jersey (the whole state) or New York City from Wikipedia as: 26,795 [1] and 40,000 [2] and divide by the total population (9.5M and 8.8M), we get IFR estimates of 0.28% and 0.51% for NJ and NYC. [1] "As of January 11, 2022, 1.63 million cases were confirmed in the state, incurring 26,795 deaths." [2] "As of August 19, 2023 the city's confirmed COVID-19 deaths exceeded 45,000 and probable deaths exceeded 5,500."

timr 2y ago
I can't tell if you're agreeing or disagreeing, but: yeah, don't do what you're doing. There are lots of good publications on this question now. You don't have to make stuff up. https://pmc.ncbi.nlm.nih.gov/articles/PMC9613797/ https://pmc.ncbi.nlm.nih.gov/articles/PMC9613797/ > we identified 40 eligible national seroprevalence studies covering 38 countries with pre-vaccination seroprevalence data. For 29 countries (24 high-income, 5 others), publicly available age-stratified COVID-19 death data and age-stratified seroprevalence information were available and were included in the primary analysis. The IFRs had a median of 0.034% (interquartile range (IQR) 0.013–0.056%) for the 0–59 years old population, and 0.095% (IQR 0.036–0.119%) for the 0–69 years old. The median IFR was 0.0003% at 0–19 years, 0.002% at 20–29 years, 0.011% at 30–39 years, 0.035% at 40–49 years, 0.123% at 50–59 years, and 0.506% at 60–69 years. IFR increases approximately 4 times every 10 years. Including data from another 9 countries with imputed age distribution of COVID-19 deaths yielded median IFR of 0.025–0.032% for 0–59 years and 0.063–0.082% for 0–69 years. Meta-regression analyses also suggested global IFR of 0.03% and 0.07%, respectively in these age groups.
- whimsicalism 2y ago
  how do you square this claim about ancestral strains IFR with the NYC death rate?
  - timr 2y ago
    The NYC death rate is based on a biased sample. If you read the various studies, you will see that there can be significant differences in regional IFR measurements based on legitimate factors (population age, health, etc.) as well as biases (e.g. invalid statistics). NYC probably has a mix of both -- older/sicker people, as well as just fundamentally bad statistics. Particularly on the question of "how many people have the virus?" NYC was laughably, objectively bad at measuring anything of relevance. They made sure that they counted everyone who died, though!
    - sampo 2y ago
      > The NYC death rate is based on a biased sample. It is not based on a sample. It is all reported Covid deaths divided by the population of NYC. Full set, not a subset.
      - timr 2y ago
        I don't know if your claim is correct, but if that is truly the ratio, it isn't meaningful or useful at all.
    - whimsicalism 2y ago
      hmm, i think you’re missing the point to be frank. take care
- jsnell 2y ago
  If there's good studies supporting your claim, you might want to link to one of them rather than that paper. Yes, of course if you exclude the people most likely to die from the count, you can get a low number. But it's a pretty useless number too. The only motivation here is for Ioannidis to pretend he wasn't repeatedly and grossly wrong.
  - timr 2y ago
    That paper is literally a meta-analysis of every study. It's also methodologically fine. > Yes, of course if you exclude the people most likely to die from the count, you can get a low number....The only motivation here is for Ioannidis to pretend he wasn't repeatedly and grossly wrong. OK, you're not objective.
    - jsnell 2y ago
      I'm not sure of what you're claiming here. Are you trying to suggest that this study actually didn't exclude the most vulnerable segment of the population from the results? Because they very explicitly excluded ages >=70. It is clear from the abstract, it is clear from the methodology, and it is clear from the results section. This wasn't something that was forced on them by the source data, they made a deliberate choice to exclude the people most likely to die. Or are you arguing that it's reasonable to make claims about the IFR with data that exludes the most vulnerable part of the population? If you are, I'd love to hear why. > OK, you're not objective. I mean, what other motive could they have had for making that age cutoff in this paper? The fact is that Ioannidis predicted 10k dead in the US. He claimed that it would probably be less dangerous than the flu. He claimed that the CFR would be 0.1%. Not the IFR, but the CFR. All of that was horribly wrong, sometimes by multiple orders of magnitude.
      - timr 2y ago
        > Are you trying to suggest that this study actually didn't exclude the most vulnerable segment of the population from the results? Because they very explicitly excluded ages >=70. > I mean, what other motive could they have had for making that age cutoff in this paper? Because that's the point? If you were even remotely trying to be objective, you'd know that the same authors published multiple papers estimating IFR and seroprevalence in the most vulnerable cohorts you're talking about. They cite them, and talk about them, in this paper as well. Here's one: https://pmc.ncbi.nlm.nih.gov/articles/PMC8934243/ https://pmc.ncbi.nlm.nih.gov/articles/PMC8934243/ > Median IFR in community-dwelling elderly and elderly overall was 2.9% (range 1.8–9.7%) and 4.5% (range 2.5–16.7%) without accounting for seroreversion (2.2% and 4.0%, respectively, accounting for 5% monthly seroreversion). Multiple sensitivity analyses yielded similar results. IFR was higher with larger proportions of people > 85 years. The IFR of COVID-19 in community-dwelling elderly is lower than previously reported. It isn't surprising or controversial (to mathematically literate scientists, anyway) that old, sick people disproportionately died from Covid. What random HN commenters, CNN, etc., continue to deny is that the threat to younger people was far lower. The paper I cited is explicitly trying to show that, even for cohorts as old as 70, the risk was far, far lower than most people believe. You're basically arguing that because they didn't mix up old, sick people with young, healthy people the result about young people is somehow wrong.
- sampo 2y ago
  > https://pmc.ncbi.nlm.nih.gov/articles/PMC9613797/ https://pmc.ncbi.nlm.nih.gov/articles/PMC9613797/ When it comes to Covid, John Ioannidis is a contrarian thinker [1]. He aligns with the Great Barrington Declaration [2] authors. This is the "covid is mild" school. Here [3] is a study that we can maybe think of coming from the more mainstream "covid is serious" school: "We estimate that the overall COVID-19 IFR ranges from 0.15–0.43% in low-income countries to 0.79–1.82% in high-income countries, with the differences in those ranges reflecting the older demography of high-income settings." And here [4] is a meta-analysis that also reports notably larger estimates than the study you linked. Also, Sweden had excess all-cause mortality in the range 0.05% to 0.1% in year 2020 [4], which in my opinion sets a pretty firm lower limit for any IFR estimate for a Western country. [1] https://en.wikipedia.org/wiki/John_Ioannidis#COVID-19 https://en.wikipedia.org/wiki/John_Ioannidis#COVID-19 [2] https://en.wikipedia.org/wiki/Great_Barrington_Declaration https://en.wikipedia.org/wiki/Great_Barrington_Declaration [3] https://www.nature.com/articles/s43856-022-00106-7 https://www.nature.com/articles/s43856-022-00106-7 [4] https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(21)02867-1/fulltext https://www.thelancet.com/journals/lancet/article/PIIS0140-6... [5] https://academic.oup.com/eurpub/article/34/4/737/7675929 https://academic.oup.com/eurpub/article/34/4/737/7675929

by sampo 2y ago

timr 2y ago

I can't tell if you're agreeing or disagreeing, but: yeah, don't do what you're doing. There are lots of good publications on this question now. You don't have to make stuff up. https://pmc.ncbi.nlm.nih.gov/articles/PMC9613797/ https://pmc.ncbi.nlm.nih.gov/articles/PMC9613797/ > we identified 40 eligible national seroprevalence studies covering 38 countries with pre-vaccination seroprevalence data. For 29 countries (24 high-income, 5 others), publicly available age-stratified COVID-19 death data and age-stratified seroprevalence information were available and were included in the primary analysis. The IFRs had a median of 0.034% (interquartile range (IQR) 0.013–0.056%) for the 0–59 years old population, and 0.095% (IQR 0.036–0.119%) for the 0–69 years old. The median IFR was 0.0003% at 0–19 years, 0.002% at 20–29 years, 0.011% at 30–39 years, 0.035% at 40–49 years, 0.123% at 50–59 years, and 0.506% at 60–69 years. IFR increases approximately 4 times every 10 years. Including data from another 9 countries with imputed age distribution of COVID-19 deaths yielded median IFR of 0.025–0.032% for 0–59 years and 0.063–0.082% for 0–69 years. Meta-regression analyses also suggested global IFR of 0.03% and 0.07%, respectively in these age groups.

whimsicalism 2y ago
how do you square this claim about ancestral strains IFR with the NYC death rate?
- timr 2y ago
  The NYC death rate is based on a biased sample. If you read the various studies, you will see that there can be significant differences in regional IFR measurements based on legitimate factors (population age, health, etc.) as well as biases (e.g. invalid statistics). NYC probably has a mix of both -- older/sicker people, as well as just fundamentally bad statistics. Particularly on the question of "how many people have the virus?" NYC was laughably, objectively bad at measuring anything of relevance. They made sure that they counted everyone who died, though!
  - sampo 2y ago
    > The NYC death rate is based on a biased sample. It is not based on a sample. It is all reported Covid deaths divided by the population of NYC. Full set, not a subset.
    - timr 2y ago
      I don't know if your claim is correct, but if that is truly the ratio, it isn't meaningful or useful at all.
  - whimsicalism 2y ago
    hmm, i think you’re missing the point to be frank. take care
jsnell 2y ago
If there's good studies supporting your claim, you might want to link to one of them rather than that paper. Yes, of course if you exclude the people most likely to die from the count, you can get a low number. But it's a pretty useless number too. The only motivation here is for Ioannidis to pretend he wasn't repeatedly and grossly wrong.
- timr 2y ago
  That paper is literally a meta-analysis of every study. It's also methodologically fine. > Yes, of course if you exclude the people most likely to die from the count, you can get a low number....The only motivation here is for Ioannidis to pretend he wasn't repeatedly and grossly wrong. OK, you're not objective.
  - jsnell 2y ago
    I'm not sure of what you're claiming here. Are you trying to suggest that this study actually didn't exclude the most vulnerable segment of the population from the results? Because they very explicitly excluded ages >=70. It is clear from the abstract, it is clear from the methodology, and it is clear from the results section. This wasn't something that was forced on them by the source data, they made a deliberate choice to exclude the people most likely to die. Or are you arguing that it's reasonable to make claims about the IFR with data that exludes the most vulnerable part of the population? If you are, I'd love to hear why. > OK, you're not objective. I mean, what other motive could they have had for making that age cutoff in this paper? The fact is that Ioannidis predicted 10k dead in the US. He claimed that it would probably be less dangerous than the flu. He claimed that the CFR would be 0.1%. Not the IFR, but the CFR. All of that was horribly wrong, sometimes by multiple orders of magnitude.
    - timr 2y ago
      > Are you trying to suggest that this study actually didn't exclude the most vulnerable segment of the population from the results? Because they very explicitly excluded ages >=70. > I mean, what other motive could they have had for making that age cutoff in this paper? Because that's the point? If you were even remotely trying to be objective, you'd know that the same authors published multiple papers estimating IFR and seroprevalence in the most vulnerable cohorts you're talking about. They cite them, and talk about them, in this paper as well. Here's one: https://pmc.ncbi.nlm.nih.gov/articles/PMC8934243/ https://pmc.ncbi.nlm.nih.gov/articles/PMC8934243/ > Median IFR in community-dwelling elderly and elderly overall was 2.9% (range 1.8–9.7%) and 4.5% (range 2.5–16.7%) without accounting for seroreversion (2.2% and 4.0%, respectively, accounting for 5% monthly seroreversion). Multiple sensitivity analyses yielded similar results. IFR was higher with larger proportions of people > 85 years. The IFR of COVID-19 in community-dwelling elderly is lower than previously reported. It isn't surprising or controversial (to mathematically literate scientists, anyway) that old, sick people disproportionately died from Covid. What random HN commenters, CNN, etc., continue to deny is that the threat to younger people was far lower. The paper I cited is explicitly trying to show that, even for cohorts as old as 70, the risk was far, far lower than most people believe. You're basically arguing that because they didn't mix up old, sick people with young, healthy people the result about young people is somehow wrong.
sampo 2y ago
> https://pmc.ncbi.nlm.nih.gov/articles/PMC9613797/ https://pmc.ncbi.nlm.nih.gov/articles/PMC9613797/ When it comes to Covid, John Ioannidis is a contrarian thinker [1]. He aligns with the Great Barrington Declaration [2] authors. This is the "covid is mild" school. Here [3] is a study that we can maybe think of coming from the more mainstream "covid is serious" school: "We estimate that the overall COVID-19 IFR ranges from 0.15–0.43% in low-income countries to 0.79–1.82% in high-income countries, with the differences in those ranges reflecting the older demography of high-income settings." And here [4] is a meta-analysis that also reports notably larger estimates than the study you linked. Also, Sweden had excess all-cause mortality in the range 0.05% to 0.1% in year 2020 [4], which in my opinion sets a pretty firm lower limit for any IFR estimate for a Western country. [1] https://en.wikipedia.org/wiki/John_Ioannidis#COVID-19 https://en.wikipedia.org/wiki/John_Ioannidis#COVID-19 [2] https://en.wikipedia.org/wiki/Great_Barrington_Declaration https://en.wikipedia.org/wiki/Great_Barrington_Declaration [3] https://www.nature.com/articles/s43856-022-00106-7 https://www.nature.com/articles/s43856-022-00106-7 [4] https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(21)02867-1/fulltext https://www.thelancet.com/journals/lancet/article/PIIS0140-6... [5] https://academic.oup.com/eurpub/article/34/4/737/7675929 https://academic.oup.com/eurpub/article/34/4/737/7675929