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Atomsk's Sanakan Profile picture
@AtomsksSanakan
Dec 22, 2020 • 51 tweets • 39 min read • Read on X
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1/
Many COVID-19 contrarians, including those behind the Great Barrington Declaration, *still* cite John Ioannidis' inaccurate estimate of SARS-CoV-2's fatality rate.

So let's go over how atrocious Ioannidis' paper is.



web.archive.org/web/2020111809… Image
2/
Background:

When a virus infects u, your body increases production of proteins known as antibodies, which are usually specific to that virus.

So measuring antibodies lets u estimate who was infected, and from that the infection fatality rate (IFR).

institutefordiseasemodeling.github.io/nCoV-public/an… Image
3/

Ioannidis uses antibody (a.k.a. seroprevalence) studies to estimate the number of people infected with the virus SARS-CoV-2. He then calculates IFR by dividing the number of COVID-19 deaths by the number of infected people.

Ioannidis does this badly:
medrxiv.org/content/10.110… Image
4/
It's no secret in the scientific community that Ioannidis' paper is poor. Some examples:

rapidreviewscovid19.mitpress.mit.edu/pub/p6tto8hl/r…
rapidreviewscovid19.mitpress.mit.edu/pub/6z09ucch/r…
rapidreviewscovid19.mitpress.mit.edu/pub/k2pkhufi/r…

hildabastian.net/index.php/91




web.archive.org/web/2020121700… Image
5/
Ioannidis' paper gives a median IFR estimate of 0.27%, which he corrects to 0.23%. That's a low outlier.

"[..] 0.79% (95% credible interval, 0.68–0.92%) [...], with a median range of 0.24–1.49%"
nature.com/articles/s4158…



web.archive.org/web/2020121700… Image
6/
Beware when folks cherry-pick Ioannidis' outlier of ~0.23% as if its credible.

Public Health Agency of Sweden:
"Globally, it is estimated that 0.5–1 percent of those who are infected with COVID-19 die"
web.archive.org/web/2020103000…



sciencedirect.com/science/articl… Image
7/
Also beware of people who try to mislead you into thinking the World Health Organization agrees with Ioanndis' low IFR estimate, or with his claims that SARS-CoV-2 has an IFR similar to that of seasonal influenza.



October 12:
who.int/publications/m… Image
8/
The points above have been made before. So what will this thread add?

Well, I'll go through each of the 61 studies Ioannidis cites to support his IFR estimate, + show they don't adequately support his estimate.

A numbered list of the studies:
web.archive.org/web/2020111809… ImageImage
9/
Antibody studies can use a *representative* sample of the population to accurately estimate the number of infections. Otherwise, one could over-estimate the number of infections + under-estimate IFR.

Scientists know how to get representative samples.

sciencedirect.com/science/articl… Image
10/
Re: "Scientists know how to get representative samples."

For instance:

link.springer.com/article/10.100…
wwwnc.cdc.gov/eid/article/26…
link.springer.com/article/10.100…

cdc.gov/nceh/casper/ov…
web.archive.org/web/2020101623…

sci-hub.se/https://www.jc…

ncbi.nlm.nih.gov/pmc/articles/P… Image
11/
Ioannidis mostly cites studies that use non-representative sampling. That causes him to over-estimate seroprevalence + thus under-estimate IFR.

Studies with non-representative sampling may be useful for other purposes, but not for estimating population-wide IFR.
12/
For instance, blood donor studies:

- under-sample older people, a population more likely to die of COVID-19
- include people who go outside to donate blood, + are thus more likely to interact with people and get infected



link.springer.com/article/10.100… Image
13/
So one can exclude the following blood donor studies from Ioannidis' list of 61 studies in part 8/:

9 studies:
11, 14, 17, 29, 33, 35, 44, 46, 61



Image
14/
Studies of leftover samples from hospital visitors are non-representative. For instance:

- one can get infected at a hospital (nosocomial infection)
- some visit hospitals due to concern they're infected with SARS-CoV-2



link.springer.com/article/10.100… Image
15/
So one can exclude the following 'residual sera / hospital visitors' studies from Ioannidis' list of 61 studies in part 8/:

13 studies:
2, 9, 23, 27, 30, 31, 36, 39, 40, 42, 47, 59, 60

academic.oup.com/cid/advance-ar…

academic.oup.com/cid/advance-ar… Image
16/
Volunteers who hear antibody testing is occurring, but were not targeted for testing by random selection, may ask to be tested because they think they're infected (ex: they have symptoms, known prior exposure to an infected person, etc.).

uoflnews.com/post/uofltoday… Image
17/
A similar problem occurs for studies with non-randomized (non-probabilistic) sampling steps after initial randomization.

Besides studies in part 18/, many of the other studies Ioannidis cites use non-targeted volunteers.



link.springer.com/article/10.100… Image
18/
So one can exclude the following 'non-targeted volunteers / non-probabilistic step' studies from Ioannidis' list of 61 studies in part 8/:

10 studies:
12, 13, 15, 34, 38, 48, 50-52, 54

rapidreviewscovid19.mitpress.mit.edu/pub/p6tto8hl/r… Image
19/
People in schools, workplaces, shoppers, etc. are not necessarily representative of the general population. For instance, they're socially interacting in a closed setting, increasing their risk of infection.



Image
20/
So one can exclude the following 'workplaces / schools / shops' studies from Ioannidis' list of 61 studies in part 8/:

6 studies:
10, 16, 19, 20, 22, 58



ncbi.nlm.nih.gov/pmc/articles/P… Image
21/
So out of 61 studies Ioannidis cites in part 8/, only 23 have at least decently representative sampling:

1, 3-5, 7, 8, 18, 21, 24-26, 28, 32, 37, 41, 43, 45, 49, 53, 55-57

(note: part 13/ should include 10 studies, not 9, since paper #6 is also blood donor study).
22/
But papers 4, 5, 7, + 8 should be dropped from IFR calculations, since they sample regions included in paper 3.

That leaves 19 papers.

Sampling the same region multiple times unfairly skews the results, as per collinearity.



who.int/bulletin/onlin… Image
23/
Paper 18 should be dropped, since it implies only ~365 infections, which is much too small a number to derive a robust IFR estimate.

It's telling that Ioannidis tried to infer an IFR of 0.00% from that.

wwwnc.cdc.gov/eid/article/26… Image
24/
Re: "It's telling that Ioannidis tried to infer an IFR of 0.00% from that."

Ioannidis states it's risky to draw inferences from a sample size of less than 500... but doesn't let that stop him from using ~365 infections to infer a low IFR.

who.int/bulletin/onlin… Image
25/
Paper 37 (Karachi, Pakistan) should also be dropped, because Ioannidis uses an unsound method of getting the COVID-19 deaths he applies in his IFR calculation.

medrxiv.org/content/10.110…
aku.edu/news/Pages/New…



who.int/bulletin/onlin… Image
26/
That leaves 16 studies:
1, 3, 21, 24-26, 28, 32, 41, 43, 45, 49, 53, 55-57

(note: part 21/ should read say "only 22", not "only 23")

That's barely a quarter of the 61 studies Ioannidis said supported his IFR estimate. But at least the studies are now of better quality.
27/
Yet problems remain.

Take the example of paper 3 (for Brazil). Months ago when I first saw what Ioannidis did with paper 3, I lost any remaining confidence I had in the credibility of his paper and in his IFR work in general



who.int/bulletin/onlin… Image
28/
Paper 3 stated an IFR of ~1.0%.

If Ioannidis' paper was really a *systematic* review, then he would have used that IFR to start with, as he did for some other studies he cited.

Instead Ioannidis was non-systematic + biased.



medrxiv.org/content/10.110… Image
29/
To avoid paper 3's larger stated IFR, Ioannidis invented a new calculation based on his misinterpretation of figure 3 from the paper. In doing so, he contradicted paper 3 and used reasoning that makes no sense.



who.int/bulletin/onlin… Image
30/
Suppose a country of 10,001,000 people contains:
- city X: 10,000,000 people
- ten other towns: 100 people per town

Obviously, X predominately determines the country's IFR. But Ioannidis' method gives the same weight to X as to one of the towns. 🤦‍♂️

medrxiv.org/content/10.110… Image
31/
There are other IFR calculation issues. For example, Ioannidis gives an uncorrected IFR of 0.45% for paper 43 for Geneva (see image on the right side in part 8/).

But co-authors of paper 43 later used the paper's data to calculate an IFR of 0.64%:
thelancet.com/journals/lanin… Image
32/
Addressing those obvious issues for papers 3 and 43 leaves one with the following median IFR from the 16 studies in part 26/:

~0.5%

Similar median IFR @GidMK showed previously, but now with the removal of residual sera studies, collinearity, etc.

Image
33/
This median estimate of ~0.5% would likely go up once one corrected other issues with Ioannidis's paper.

Some of these issues include:

- under-estimated COVID-19 deaths via right-censoring



thelancet.com/journals/lanin…

link.springer.com/article/10.100… Image
34/
- under-estimating deaths b/c of death reporting



ncbi.nlm.nih.gov/pmc/articles/P…
ncbi.nlm.nih.gov/pmc/articles/P…

ijmr.org.in/article.asp?is…
medrxiv.org/content/10.110…
medrxiv.org/content/10.110…
medrxiv.org/content/10.110…
bmj.com/content/370/bm…

sciencedirect.com/science/articl… Image
35/
- over-estimating seroprevalence for papers 21, 28, 49 (Gangelt, Guilan, Los Angeles), and papers 56 + 57 under-estimating seroprevalence by a smaller proportion



Image
36/
Take-home messages:

- Ioannidis predominately uses studies with non-representative sampling
- excluding the most non-representative studies doubles his IFR to ~0.5%
- correcting his other mistakes would most likely increase his stated IFR even more

37/
Re: "doubles [Ioannidis'] IFR to ~0.5%"

Ironic.



"Ioannidis told viewers that the virus has an “infection fatality rate that is in the same ballpark as seasonal influenza.”"
buzzfeednews.com/article/stepha…


who.int/publications/m… Image
38/
The difference between an IFR of ~0.6% and IFR of ~0.2% is 3X less COVID-19 deaths (with the same number of infections).

Ex: the USA now has ~320,000 reported COVID-19 deaths. IFR 3X lower would be ~213,000 more people alive



Image
39/
Alongside parts 5/ and 6/:
"[IFR in a typical low-income country:] 0.23% (0.14-0.42 [...]) [...].
[In a typical high income country:] 1.15% (0.78-1.79 [...])"
web.archive.org/web/2020110103…

From May, before move evidence on IFR:
[mdpi.com/2076-393X/8/2/…]
sciencedirect.com/science/articl… Image
40/
There are other oddities that individually wouldn't mean much, but taken together show Ioannidis is biased towards showing a lower IFR.

For example, he uses an 0.09% IFR for paper 26 in part 8/, when his source gives a higher value:

medrxiv.org/content/10.110… Image
41/
Similarly, Ioannidis gives an IFR on 0.28% for paper 21 in part 8/, even though his cited source gives a higher IFR.

In any event, his source likely under-estimates IFR by at least a factor of 4.




medrxiv.org/content/10.110… Image
42/
Ioannidis uses PCR results for paper 56, even though PCR-positive antibody-test-negative people would be less likely to die in time to be included in his IFR.

That allows him to reduce paper's 56's IFR from 1.67% to 0.91%.



medrxiv.org/content/10.110… Image
43/
And Ioannidis reports a 1.16% IFR for paper 45 from part 8/ (for England, without excluding nursing home deaths), while the source he cites gives an IFR of 1.43%.



medrxiv.org/content/10.110… Image
44/
Jay Bhattacharya uses Ioannidis' age-specific result to influence governments:

"For people 70 and over, the infection survival rate is 95%. For people under 70, it is 99.95%"
web.archive.org/web/2020120920…

^^^That doesn't hold up.



link.springer.com/article/10.100… Image
45/
Paper 37 has three phases of testing, occurring one after the other. Ioannidis knew of phases 1 and 2.

He left out phase 1, + gave phase 2 an IFR of 0.08%.




An update today rebuts that:

medrxiv.org/content/10.110… Image
46/
Some try to support Ioannidis' paper by cherry-picking studies with a lower population-wide IFR.

Ex: a ~0.3% IFR for Iceland.








47/
But population-wide IFR tends to be higher in:
- older countries
- places with a greater proportion of infections in older people

Accounting for that reveals an age-specific IFR higher than in Ioannidis' paper (see part 44/)



nejm.org/doi/suppl/10.1… Image
48/
The WHO publishing Ioannidis' paper in their journal doesn't mean they agree with him (ex: a journal can have 2 papers that contradict each other)

WHO officials endorse an IFR estimate >2X larger than Ioannidis' (see part 7/)


who.int/bulletin/discl… Image
49/
Below is a thread that uses the same method to analyze 4 other seroprevalence-based multi-country IFR estimates:

50/
The population fatality rate, or PFR (i.e. COVID-19 deaths per capita), should be less than IFR, since you can't have more people infected than actually exist.

Yet in at least 3 instances, Ioannidis gives 'corrected' IFRs that are less than PFR.

51/
Re: "Ioannidis gives 'corrected' IFRs that are less than PFR"

For the paper #'s in part 8/, with IFR listed before PFR:

#6
0.11% , 0.19%
transparencia.registrocivil.org.br/especial-covid

#46
0.07% , 0.15%
coronavirus.data.gov.uk/details/deaths…

#50
0.00% , 0.04%
coronavirus.jhu.edu/us-map

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More from @AtomsksSanakan

Atomsk's Sanakan Profile picture
Feb 23
71/J

I recently got a copy of Dr. Judith Curry's book without buying it myself.

Looking over it confirmed to me that it's largely misinformation.

I'll illustrate that by assessing its claims on COVID-19.



"11.3.1 COVID-19"

amazon.com/Climate-Uncert…
Image
72/J

To reiterate: Curry draws parallels between COVID-19 + climate change.

But some of the sources she cites suggest an ideologically convenient narrative misinformed her.

That becomes clearer when assessing her claims.




Image
73/J

No mention of the misinformation she + other contrarians promoted, and which conflicted with knowledge advances by experts.

(8/J - 12/J, 32J - 36/J, 44/J, 45/J, 63/J, etc.)








Image
Read 31 tweets
Atomsk's Sanakan Profile picture
Feb 17
1/J

Dr. Judith Curry recommends people read at least the 45-page preview of her new book.

I did.

It's bad enough I wouldn't recommend buying the book.
It's largely contrarian conspiracist misinformation.




amazon.com/Climate-Uncert…
Image
2/J

Many reviews laud the book without addressing whether her claims are accurate, likely because she ways what they want to hear.











netzerowatch.com/all-news/book-…
washingtontimes.com/news/2023/aug/…
Image
3/J

So I'll address the substance of her claims, with direct quotes of what she said.

That approach exposes her implausible position












realclearenergy.org/articles/2023/…
Image
Read 72 tweets
Atomsk's Sanakan Profile picture
Aug 30, 2023
PapersOfTheDay

"Executive Summary to the Royal Society report “COVID-19: examining the effectiveness of non-pharmaceutical interventions”"


"Effectiveness of face masks for reducing transmission of SARS-CoV-2: [...]"
royalsocietypublishing.org/doi/10.1098/rs…
royalsocietypublishing.org/doi/10.1098/rs…



Image
Jefferson + Heneghan don't like the papers.

Makes sense they wouldn't given their track record, especially Jefferson on the Cochrane mask review he led.







brownstone.org/articles/royal…



cochrane.org/news/statement…
Image
Read 5 tweets
Atomsk's Sanakan Profile picture
Mar 13, 2023
69/E

A reminder, since there's a resurgence in Musk + right-wing politicians trying to score political points by saying they want Fauci prosecuted:

Musk's dislike of Fauci drove him to post an easily debunked lie (57/E, 56/, 41/)


Image
70/E

Still no apology from Musk for falsely smearing Grady based on untrue things he was told, or that he made up.

"Elon Musk calls British diver in Thai cave rescue 'pedo' in baseless attack"
theguardian.com/technology/201…



thedailybeast.com/elon-musk-mock… Image
71/E

Another good example of the willful ignorance + baseless paranoia underlying Musk's lab leak conspiracism and his criticisms of Fauci.




archive.is/GZ6er#selectio…
archive.is/ughZK#selectio…
archive.is/WWKtc#selectio… ImageImageImage
Read 11 tweets
Atomsk's Sanakan Profile picture
Dec 12, 2022
1/E

Some illustrations of the pseudoskepticism that overtakes many crypto / tech bros, using the example of Elon Musk's COVID-19 claims.

"My pronouns are Prosecute/Fauci"


onlinelibrary.wiley.com/doi/full/10.11… Image
2/E

No, neither chloroquine nor hydroxychloroquine worked for SARS-CoV-2.

Fortunately, Fauci recommended neither in March 2020.

9:12 - 14:41 :



Image
3/E

About Sweden...

18 October 2020:
"Sweden at zero deaths Oct 15"


30 October 2020:
"And … Sweden is still right with zero deaths Oct 29"




ourworldindata.org/explorers/coro…

worldometers.info/coronavirus/co… Image
Read 29 tweets
Atomsk's Sanakan Profile picture
Jun 8, 2022
1/B

Thread on a myth Jay Bhattacharya (@DrJBhattacharya) continues to peddle to undermine confidence in public health agencies and to suit his policy agenda.

The myth may undermine responses to future public health emergencies.




stanfordreview.org/the-review-int…
Image
2/B

Some background:

The infection fatality rate (IFR) states the proportion of *SARS-CoV-2-infected* people who die of the disease COVID-19.

The case fatality rate (CFR) states the proportion of *reported cases* who die of COVID-19.

institutefordiseasemodeling.github.io/nCoV-public/an…
Image
3/B

Reporting systems are not perfect, so they sometimes miss infected people. That makes reported cases less than total infections, and thus CFR is higher than IFR.

The WHO was open about this since the early stages of the pandemic:

March 17, 2020:
web.archive.org/web/2020102205…
Image
Read 26 tweets

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