Hacker News Reader

- "for those who wonder: the right way to do this is random sampling -- you at least have to sample the population randomly to estimate seroprevalence correctly"

There was a recent experiment that found 7% antibody prevalence in US diary workers,

https://www.cdc.gov/mmwr/volumes/73/wr/mm7344a3.htm

The death rate of people that are noticeably sick is interesting actually, especially if lots of people are getting noticeably sick.

Like probably not interesting enough to start shooting people you think might be sick (panic), but maybe interesting enough to encourage voluntary social distancing measures (a measured response).

> Like probably not interesting enough to start shooting people you think might be sick (panic), but maybe interesting enough to encourage voluntary social distancing measures (a measured response).

...a "measured response" that caused huge harm, did generational damage to children, and shouldn't be used casually. Certainly not without proof that it works for some important, clear goal [1].

[1] for reference: "because we're scared and we think it might help" is not a clear goal.

If you think social distancing and masking caused more generational harm to kids than Covid deaths of friends and relatives you're going to have a very interesting time trying to survive the next pandemic.

Nobody said anything about "masking". But yes, "social distancing" is what closed down a lot of schools around the US, and kept them closed for years.

NYC, for example, kept kids out of school based on "social distancing" for a year and a half [1], not counting the years of follow-on silliness that some schools still do to this day.

[1] https://www.nytimes.com/2021/09/13/world/reopening-timeline-...

Staying away from me when you’re sick actually works pretty well, as everyone knows.

It literally does not work for a respiratory virus. It didn't work for Covid.

I can't believe we're still having this debate.

Do you happen to have a study stating that social distancing literally didn't work? Anecdotally, all people I know who never got COVID were very remote and had little contact with others, perhaps a form of extreme social distancing one might say.

Source?

Social distancing has been a proven method to combat the spread of ilnesses, including respiratory viruses, for centuries. And it still works, and it did work for Covid.

A good example for that is France that did 3 lockdowns, each time when the main factor optimised for, % of hospital beds occupied, started to go up dagenrously. And in each one, the number of confirmed cases went down, and hospital tension eased (after ~1-2 weeks). Are you stating that this was some sort of... mass placebo? Something completely unrelated? What actually is your claim?

> Source?

Well, for starters: https://www.cebm.net/covid-19/what-is-the-evidence-to-suppor...

You'll see that there's no high-quality evidence supporting basically any of it. It's either based on bad data [1], confounded studies, or worse.

...but to be clear, you have to define "social distancing" more specifically. If you define it as "hiding it in your basement to avoid colds", then the answer is going to be different than, say, "standing on spots in the elevator", or (more to my original point) "doing alternate day in-person education because teachers want fewer students in the classroom".

I'd still argue that we need a shred of decent evidence for any of it, but we should at least start by being specific about our claims.

> Social distancing has been a proven method to combat the spread of ilnesses, including respiratory viruses, for centuries. And it still works, and it did work for Covid.

It's pretty funny how you demand sources from other people, but then just make stuff up.

[1] Classic example: asking people if they "social distanced", then asking those same people if they remember getting sick. There are so many "studies" like this in public health "science", and if you exclude them from meta-analysis on the grounds that they're total bullshit, partisans start accusing you of "cherry-picking", because that's often the full extent of the affirmative evidence for whatever thing they're advocating.

Read what I said more carefully instead of reacting to what you want it to say. I wasn't referencing Covid measures.

There should be an incapacitation rate metric which quantifies what percentage of the population becomes unable to function for some significant period while infected.

A 1% IFR is very bad, but you're still going to have serious problems with a virus that doesn't kill anyone but makes most of the population very ill for a month or so - showstopper lights-go-out kinds of problems.

The problem now of course is that a significant percentage of the population has been propagandised into irrational lunacy, and will refuse to wear masks and get vaccinated even if their close relatives die.

We should really have spent some time trying to prevent mental and emotional contagion in populations, as well as physical illness.

So your point is that even with a IFR of less than 2.6% bodies had to be stored in freeze trucks? Ugh.

> 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."

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/

> 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.

how do you square this claim about ancestral strains IFR with the NYC death rate?

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!

> 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.

I don't know if your claim is correct, but if that is truly the ratio, it isn't meaningful or useful at all.

hmm, i think you’re missing the point to be frank.

take care

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.

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.

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.

> 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/

> 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.

No, I'm arguing that your claim about IFR being less than 0.26% is incorrect, for the western population distributions that are relevant to this discussion.

You're the one who chose that paper excluding the elderly as the sole reference for your claims about the IFR. Why?

> 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

[2] https://en.wikipedia.org/wiki/Great_Barrington_Declaration

[3] https://www.nature.com/articles/s43856-022-00106-7

[4] https://www.thelancet.com/journals/lancet/article/PIIS0140-6...

[5] https://academic.oup.com/eurpub/article/34/4/737/7675929