Infection fatality rate

We all learned a bit of epidemiological jargon over the last year, hey?

The term ‘infection fatality rate’ means:

. . . the proportion of deaths among all infected individuals, including all asymptomatic and undiagnosed subjects. It is closely related to the CFR [case fatality rate], but attempts to additionally account for inapparent infections among healthy people.

The case fatality rate means the death rate among those diagnosed with the disease and will necessarily be higher than the IFR.

I wanted to know: overall, if you get infected with Covid, what are your chances of survival? I saw a big argument about this online with some saying it was way over 1% and some saying it was way less.

Let’s get to the bottom of it.

You’d think the agreed figure would be plastered everywhere but it took some searching to find a meaningful answer.

Here’s what my beloved WHO published in October 2020. Keep in mind that all the figures that follow are pre-vaccine:

As you can see, there’s quite a spread. Locations with higher death rates per million also, unsurprisingly, reported a higher IFR.

The median IFR was 0.27% but the range of ‘uncorrected estimates’ was 0.01 to 1.63%.

I might stop here and say, there you have it, 0.27% is the answer. But the range still troubles me. It begs for an explanation because it’s the same bloody disease – how could it be so much more deadly in some places than in others?

I finally came across an article that explains it. Bizarrely, this comes from research by Imperial College London. Yep, these guys.


The COVID infection fatality ratio is around 1% in high-income countries, but substantially lower in low-income countries with younger populations . . .

Age-specific IFRs increased from 0.1% and below for individuals under 40 years to greater than 5% among individuals over 80 years

Using these age-specific estimates, the team estimates the overall IFR in a low-income country, with a population structure skewed towards younger individuals, can be expected to be approximately 0.23% (95% prediction interval 0.14-0.42).

In contrast, in high income countries, with a greater concentration of elderly individuals, the report estimates that the overall IFR can be expected to be approximately 1.15% (95% prediction interval 0.78-1.79) . . .

In addition, the researchers did not find evidence that the IFR was higher in regions with larger epidemics.

Toot toot, I called it.

Interesting that all the flash medical resources of developed countries did not outweigh or even much mitigate the impact of having older populations. Up until vaccines, that is.

There’s little benefit for Third World countries to have tight lockdowns and other restrictions because (a) their comparatively young population means the disease will be less deadly, (b) economic disruption may end up costing more lives among those already near poverty, and (c) trying to reduce infections until a vaccine comes along makes no sense if you can’t afford a mass vaccination program for several years anyway.

That’s where much of jungle Asia is at. There are still restrictions here and there, schools are closed, but I doubt they’ll get the vulnerable vaccinated even five years from now. Source: the outcome of all previous government programs.

In any case, we got the answer we set out to find: Covid’s IFR is about 0.2% in poor countries and about 1.2% in rich countries.

Also keep in mind that Covid is more than twice as contagious as influenza, meaning more sickness and death overall.

Hope that clears things up.

Edit: this study suggests a mean IFR of 0.68%, again with a very wide range between countries:

Conclusion: Based on a systematic review and meta-analysis of published evidence on COVID-19 until July 2020, the IFR of the disease across populations is 0.68% (0.53%-0.82%). However, due to very high heterogeneity in the meta-analysis, it is difficult to know if this represents a completely unbiased point estimate. It is likely that, due to age and perhaps underlying comorbidities in the population, different places will experience different IFRs due to the disease. Given issues with mortality recording, it is also likely that this represents an underestimate of the true IFR figure. More research looking at age-stratified IFR is urgently needed to inform policymaking on this front.

This backs up the Imperial/WHO figure more than it might seem. I’m guessing the two median figures only differ because the second study included more outcomes from developed countries. As to which is more accurate, it hardly seems to matter because the global average IFR is not a useful figure (after all that).

Each nation’s, and individual’s, risk level is determined by age and health. If you’re in a Toronto nursing home, average outcomes for 20-something Indonesian farmers mean nothing, and visa-versa.

In Wednesday’s post we’ll examine a table of risk levels by age that will inform our food-fight on the topic everyone fancies himself an expert on: Covid vaccines.


  1. luisman · May 24
    Ioannidis is still the best in his field. Anyway the artificial number of 0,15% IFR is not really usefull.

    Meanwhile many doctors see that the death rate among the vaccinated population goes up dramatically, as the ADE syndrom kills your natural immune system’s response to all the new variants.

    Liked by 1 person

    • Can you check that second link? It isn’t working.


      • luisman · May 24

        These are two links which the comment funktion somehow put together. Edit and put a blank and a return befor the 2nd https


    • Ioannidis link: He’s probably including more results from younger, Third World countries, hence the lower IFR. On one hand, his figure may be more accurate. On the other, I don’t think we test for influenza to the same extreme degree of sensitivity when estimating its IFR. If we did try to detect tiny amounts of another virus in the general population the same way we do for Covid, perhaps its IFR would also fall from present estimates. Probably we’re splitting hairs but it’s an interesting question. And troubling: any other disease might be blown out of proportion in the future by over-testing for trace remnants in the asymptomatic.

      Doctors for Covid Ethics: The signatories seem to be legit experts. Not sure if the risk they describe is sufficient to remove emergency approval of vaccines for the elderly given known risks of Covid but they may have a point regarding its approval for those at lower risk.

      YouTube link: The red dotted line projections are based on vaccines having a 97% efficacy rate in reducing Covid mortality. Claimed rates are lower than that, in this report only 69%, so the red line was always going to be too optimistic:
      The report adds:
      “Studies of the real-world effectiveness of vaccines against SARS-CoV-2 have reported high levels of protection against both symptomatic COVID-19 and asymptomatic disease.
      However, evidence on the effectiveness against the most severe outcome – mortality – is currently limited and has not yet been reported for most vaccines, says Lopez and colleagues.”
      I found other news reports saying the Pfizer was 97% effective against severe cases, not deaths, which is probably where the author got that figure from.

      I compared the video’s graphs to a couple of those on Worldometer.
      For Hungary, the actual death rate fell dramatically just after the video’s cut-off, which suggests vaccines helped there eventually:
      The video’s projection for India predicted very low death rates only because Covid was not spreading much when it was calculated, not because everyone was vaccinated. The vaccination rate there is still very low so the recent spike in mortality doesn’t yet disprove their efficacy.

      In tomorrow’s post I’ll point to Worldometer’s data as evidence that vaccines seem to correlate with falling infection and death rates in those countries far along with their vaccination programs so far. Have a look and see what you think. You can click on any country to get their latest data:

      Liked by 1 person

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