> But even if the actual case fatality rate were 10 times lower – about 5% – it would still be a serious virus to contend with. The case fatality rate for the ancestral strain of Covid-19 was estimated to be around 2.6%, for example.
Ugh. The news media never learns [1]:
1) The IFR for Covid-19 was not 2.6%. Less than a tenth of that, actually (yes, even for the ancestral strains).
2) "CFR" is a made up number, because it depends on what cases you count. If you count only a sample of people in the ICU, you can make the CFR look horrible for pretty much any illness. We made this mistake during covid!
3) You can see the same mistake in progress here, because you can't just take this sample of deaths you looked for, divide it by the cases you know about, scale it down by a random factor (that you pulled out of your butt), and then panic about the result [2].
[1] or more likely: never wants to learn, because fear drives clicks.
[2] 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.
- "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,
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.
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?
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.
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.
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.
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.
> 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.
> 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.
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.
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:
> 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?
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.
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!
This is concerning, but not worth panicking about yet. The person had direct contact with infected birds, so there is no evidence of human-to-human transmission.
For those wanting to learn more about bird flu, and flu in general, I highly recommend the recent Scott Alexander post:
This article is great - enlightening and quit funny:
> Pigs can be infected by both human and bird viruses, so they are a common place for this reassortment to take place. If reassortment is sort of like viral sex, pigs are sort of like Tinder.
There's already a (regular) flu outbreak in Louisiana and people are probably dying from it but it's not considered newsworthy because people die from flu every year.
I am not going to panic about it at this point. But, if it does develop into a pandemic, I am quite certain that the initial response will be more along the lines of "let's just see what happens. Gotta keep the economy going, right?"
Neither was Covid - it was always a silly idea with zero actual evidence for it. The steel man case for a lab leak was a leak of a natural virus, but even that has no evidence.
In the leak of existing virus scenario, you’d just need an existing virus kept secret from the entire worlds scientific and intelligence apparatus that accidentally escaped. In the gain of function one, you’d need that same virus as the backbone but also you’d need a lab to have discovered and used a new, unpublished and less effective insert (PRRAR) that accidentally created the worlds first artificial pandemic virus… again, all completely under the scientific and intelligence radar.
The number of people who would need to be involved and kept quiet in the latter quickly reaches implausible numbers. I don’t consider it much of a steel man to create a huge conspiracy when a simple mistake would suffice.
Are you telling me its crazy that a scientist accidentally caught an undocumented strain of the virus and spread it? Why would there need to be a cover up if they can't even find patient zero. And even if there was a cover up, both the US and China have massive incentives to cover it up.
> if there was a cover up, both the US and China have massive incentives to cover it up.
China saving face, that one is clear (although unlikely to survive, remember that doctor who risked his career and life to expose that the Chinese government was downplaying Covid? Why do you think nobody would expose a cover-up?). What incentive was there for the US, or any other impacted country?
Especially the Trump White House… they repeatedly exaggerated the available evidence to insinuate a lab leak… it would’ve been a huge political boon if they had any actual proof of malfeasance.
They are saying that the lab leak scenario is extremely unlikely, yes.
People have had lengthy moderated debates on this, with independant judges and $100K USD or personal money on the line .. and even when setup by confident pro lab leak debaters they've still failed to carry the argument as likely or probable - it's still possible but unlikely.
I don't know if this will help anyone, but my sister is an expert in this area. She is an infectious disease epidemiologist with a couple decades of experience. She was the head of vaccine-preventable epidemiology for one of the states in the U.S., and is now the head of epidemiology data and informatics for that state.
Over the holidays, I was asking her about bird flu because some of the things I was reading were frightening, but I wasn't sure what to make of them.
Everyone will react differently to the flu. There are kids in her exact situation that have that kind of reaction to the normal flu. However, it is still concerning. If the virus does cause more severe illness overall and it does mutate to become person-to-person, we are in trouble.
That is the hardest thing about public health—you just don't know which way things will swing. So you are always on the edge of either overreacting or underreacting.
The sister's answer is the answer pretty much any doc knowing the bare minimum about flu would give. This was already the case before the last pandemic. The flu virus is closely monitored for this exact reason: medical authorities and the WHO have been expecting a problematic flu pandemic for at least two decades. No one can know when the 'big one' will appear, but this one's a good candidate.
Can we just preemptively start vaccinating against this strain? we have the vaccine and seems like a low risk thing to get started on. even if no evidence of human to human transmission.
There is however some promising work on designing antibodies which might be broadly effective against all flus including H5N1: https://pubmed.ncbi.nlm.nih.gov/21320540/
But that's a decade away from deployment - though fortunately likely highly motivated if it works because the other promise is long-term immunity, rather then yearly boosters.
Ugh. The news media never learns [1]:
1) The IFR for Covid-19 was not 2.6%. Less than a tenth of that, actually (yes, even for the ancestral strains).
2) "CFR" is a made up number, because it depends on what cases you count. If you count only a sample of people in the ICU, you can make the CFR look horrible for pretty much any illness. We made this mistake during covid!
3) You can see the same mistake in progress here, because you can't just take this sample of deaths you looked for, divide it by the cases you know about, scale it down by a random factor (that you pulled out of your butt), and then panic about the result [2].
[1] or more likely: never wants to learn, because fear drives clicks.
[2] 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.
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