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This is the (tentative) conclusion of a meta-analysis found on the WHO's website, written by John Ioannidis, which in its abstract says:

Across 51 locations, the median COVID-19 infection fatality rate was 0.27% (corrected 0.23%). [...] In people < 70 years, infection fatality rates ranged from 0.00% to 0.31% with crude and corrected medians of 0.05%.

[... and in its conclusion... ]

Most locations probably have an infection fatality rate less than 0.20%.

Ioannidis also self-cites that in a later paper to say a bit more concisely:

Global infection fatality rate is 0.15-0.20% (0.03-0.04% in those <70 years)

According to Wikipedia, Ioannidis was criticized for some previous (primary) studies on the matter. So is this meta-analysis essentially correct or possibly misleading in some way?

Note 1: according to the mods, this a distinct question from Did WHO publish a bulletin stating that COVID-19 is “equivalent in lethality to seasonal flu”?, although it's obviously related as it was considered in an answer there as being what someone (else) implicitly referred to.

Note 1-bis: That meta-analysis has also been cited in a letter to the editor of the BMJ (by a certain Eshani M King) to say that

A recent peer-reviewed paper by one of the world’s most cited and respected scientist, Professor John Ioannidis of Stanford University, quotes an infection fatality rate (IFR) for Covid of 0.00-0.57% (0.05% for under 70s), far lower than originally feared and no different to severe flu. This paper is published on WHO’s own Bulletin but ignored by UK mainstream media.

(emphasis mine). But Ioannidis himself never seems to make an explicit comparison with flu and there are some other questions here on Skeptics about the appropriateness of the comparison, so let's stick with the original/technical claim in Ioannidis' own paper(s) for this Skeptics question.

(The sub-claim in that letter of the paper being ignored by the press is somewhat inaccurate. The Daily Mail, for instance, did cover the paper in a stand-alone article.)

Note 2: infection fatality rate is not case fatality rate. The former includes in the denominator all those infected, even if asymptomatic.

  • There was actually press coverage even before the manuscript was officially accepted by the WHO Bulletin, presumably based on the preprint apnews.com/article/fact-checking-9243914747 – Fizz Jan 13 at 8:57
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    Not sure if that is the same paper that made rounds rather early in the pandemic, but I vaguely remember lots of criticism of cherry-picking the studies for the meta analysis there. And on the IFR comparison to the flu I've seen a few comparisons recently between typical flu season deaths and Covid, and it's not even close, so that might be one way to answer this by comparing it directly to previous flu seasons as that is more straightforward than the IFR calculations – Mad Scientist Jan 13 at 9:06
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    @MadScientist: I guess you've missed the (recent?) mod-trend to ask more narrow questions (See skeptics.stackexchange.com/questions/50105/…). Even regarding Covid-19 vs flu we have had somewhat narrow questions like skeptics.stackexchange.com/questions/49864/… I think a generic question "is it worse than" would be somewhat undesirable at this point... – Fizz 2 days ago
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    Ionnadis' work, in particular, has been terrible throughout the Covid epidemic. He's infamous for predicting that there would be fewer than 5,000 deaths in the US, and then quickly revising that to 10,000 as events rapidly overtook his cherry-picked statistics. It's become clear that his papers on the subject reflect his biases rather than scientific reasoning. – antlersoft 2 days ago
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    The UK Corona Infection Survey reported in Nov 2020 that 8.7% of the population had antibodies, at which time 0.08% of the population had been killed by it. So that's closer to a 1% infection fatality rate. – Tom Goodfellow 2 days ago
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The World Odometer Info site quotes a 'recovery' figure, globally, of 67,424,101 and a fatality figure of 2,019,358.

Thus if one accepts that the 'cases with outcomes' (that is to say, recovery or death) is 'recoveries' plus 'deaths' (total = 69,443,459) then the death rate is 'deaths' over 'recoveries plus deaths'.

Thus the global death rate (all locations) is 2.9 % of all infections of Covid-19.

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    Yes, but the figure aggregated there depends on the reporting standards of the country for "cases", which may or may not include the asymptomatic. So, it's hard to say if that's IFR, CFR (see note-2 in the q) or something in between because different countries may report different things as (confirmed) cases... Nonetheless, this is a useful "sanity check", because even if we assume three or four times more asymptomatic but undiagnosed exist, it still doesn't quite come close to Ioannidis' figures. – Fizz 1 hour ago
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    To get the Ioanidis figure of 0.2% IFR, one needs 500 times more infected than dead, i.e. 1 billion people must have had the virus. – Fizz 1 hour ago
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If you take a closer look at the paper, then you will notice that the methodology to detect infected people was based on studies which tested more or less randomly selected people for antibodies against SARS-CoV-2, looked at the percentage of people with antibodies, extrapolated that number to the whole population of the region from which the tested people were drawn, and then compared that to the reported number of deaths from COVID-19 in that region.

The assumption is that anyone with antibodies already had an infection with SARS-CoV-2, but might not have realized it because they were asymptomatic and there was no reason for them to get tested during their infection.

This is based on a couple assumption which might or might not be true:

  • The antibodies measured in these tests are actually from a SARS-CoV-2 infection and not from an infection with a similar but less dangerous virus (there are lots and lots of coronaviruses, and many of them are not nearly as dangerous as the Coronavirus SARS-CoV-2)
  • The antibodies detected are sufficient to prevent a(nother) SARS-CoV-2 infection.

The official numbers you can see on various COVID-19 dashboards (like the one from the John Hopkins university) list only confirmed active infections vs. deaths. With that methodology, you come to a fatality rate of ~2% with regional differences ranging from 1% to up to 10%. These regional differences can be explained by prevalence of testing (less testing usually means only obviously sick people get tested and reported, who are usually people who are less likely to survive) and quality of health care.

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