5. How big of an underestimate is it? We can get a ballpark figure by looking at the relative age-specific CFR rates from the Wu and McGoogan JAMA study, weighting each by UN data about the demographic structure of Denmark.pic.twitter.com/EgAM1ylIv2
Epidemiologist. Writer (Guardian, Observer etc). "Well known research trouble-maker". PhDing at @UoW Host of @senscipod Email gidmk.healthnerd@gmail.com he/him
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5. How big of an underestimate is it? We can get a ballpark figure by looking at the relative age-specific CFR rates from the Wu and McGoogan JAMA study, weighting each by UN data about the demographic structure of Denmark.pic.twitter.com/EgAM1ylIv2
6. When you go through this process, you find that the population IFR should be almost exactly twice the IFR in the 20-69 category. (I don't have data to extend down to age 17). This yields a population IFR estimate of something like 0.16% with approximate CI 0.12-0.31.
7. This is very close to the data coming out of California, data that I have publicly criticized. This is puzzling. With 0.15% of New York City's population dead from COVID19, that seems to be a very hard lower bound on IFR. Realistically, 0.7-1.0% seems more likely for NYC.
8. Other estimates of IFR also land in that range 0.5%-1%. While the authors of the Danish study discuss some limitations, I don't see obvious glaring flaws. Lag times to death may come into play. What, if anything, am I missing?
Carl T. Bergstrom Retweeted Carl T. Bergstrom
9. @kearnsneuro quickly picked up one thing. The age distribution of blood donor population is probably not representative of the age distribution in the population at large.https://twitter.com/i/status/1255759911570386944 …
Carl T. Bergstrom added,
10. Why does this matter? If younger people are more likely to be infected *and* more likely to give blood, the procedure described in the paper would yield an underestimate of IFR. Still I'd be surprised if this gets us all the way up to the NYC numbers.pic.twitter.com/bGTAyuWG4A
Carl T. Bergstrom Retweeted Ben Gardiner
11. @BendyGardiner correctly points out that I made things much too complicated with my silly IFR scaling to the population as a whole, and in the process got an odd result. I think I know why, but first his objection:https://twitter.com/BendyGardiner/status/1255767241410428929 …
Carl T. Bergstrom added,
12. We still need the demographic pyramid, but there's no need to use Chinese CFR estimates to make this correction. I see slightly different numbers than Ben reports, but let's work with these.pic.twitter.com/vfsaS56ybF
13. Approximately 73% of the Danish population is aged 20-69 (again, I don't have the data for 17-69). IFR 20-69 = deaths 20-69 / cases 20-69. IFR pop = all deaths / all cases. Assume cases are uniform across age. The paper gives us total deaths as well as deaths 17-69.
14. To get the population IFR, we take the IFR for 20-69 year olds and numerator by a factor of 370/53 and the denominator by 1/0.73. This gives us a 5.4-fold increase for a population IFR of 0.44%, CI (0.32-0.83%), closer in line with what I would have expected.
I'd guess if you then corrected for right censoring you'd end up with a rate very much in line with the usual estimates
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