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I was doubtful, now I stand corrected.


It wasn't really intellectually honest, to the point he received enough criticism from his own wife and granted that much

You can check out the initial few minutes of the following AMA

I don't feel like dealing with too many specifics here. One criticism I do take to heart if only because it came in one form from my wife is that despite my saying that I wanted to remain non judgmental and try to produce a document that the vaccine averse could actually receive without feeling denigrated in any way. I didn't try hard enough and certainly my guest Eric didn't try hard enough there. I would have to say we are guilty as charged and in truth, I'm not even sure it's the right target. I mean there's something patronizing about the claim that in order to reach the vaccine hesitant, you have to walk on eggshells. So as to not make them feel judged. Nevertheless, I do see the depressing results of the last podcast all around me. Those who were disposed to agree with me absolutely loved it and we're grateful. And those are worried about the Covid vaccines and taken in by what they've heard on Bret Weinstein's podcast or tucker Carlson, wherever thought Eric and I were totally clueless about the state of the conversation that's happening over there. I don't actually know what the solution is here because some people asked why not just have Brett on the podcast to talk about all this, But I think that would be a bad idea, not because I don't think they're adequate answers to the kinds of points he would raise. But like so many debates on fairly fringe topics, classic conspiracy theories, religious fundamentalism, many points can't be addressed in real time. Many anomalies can't be fully explained, right?


Oops, link fixed, here it is again for convenience.

I understand you say these are large numbers, but I don't know what signal we can expect to see if they can't contain the outbreak. Number of travelers from China that need isolating?
Or do you expect that the number of deaths will be considerably high?


China keeps daily cases under 50 per million through 2022: ?% → 40%. [...] We’ll know if this is failing,

How do you know that we'll know if this is failing?

I'll go with 60% that by December 31st 2022 we'll have no credible reports (or even the OWID feed) say China had any day with 50+ cases per million, at least this puts an upper bound on the resolution.

This is the sum of three things:

  1. Even if >50/mil, Information doesn’t get out, not by December 31st 2022 at least
  2. China manages to mitigate effectively
  3. China is already mostly immune. See this comment thread on ACX

Last one has low probability, certainly lower than #1, but it’s still there.

But I’m curious, what makes you think we’ll know if China will fail to contain Omicron?

Answer by ndrOct 06, 202150

Why 18?


See a reproduction of Lawrie's metastudy here.
Even without both of those constributions the result doesn't meaningfully change.


I have not managed to see Hariyanto et al reproduced yet (any help welcome), so I don't know what effect removing Elgazzar from it would have on that specific meta-study.

For Bryant et al though this is the result with both Elgazzar's in:

This is the result with both Elgazzar's out:

RR moved, but the result is fundamentally the same.
Do you think it would change the result for Hariyanto et al?


A recent preprint compares Roman et al and Bryant et al: Bayesian Meta Analysis of Ivermectin Effectiveness in Treating Covid-19 Disease

The two studies find similar RR (risk reduction as )

Bryant found RR = 0.38 [CI 95%: (0.19, 0.73)]
Roman found RR = 0.37 [CI 95%: (0.12, 1.13)]

Roman et al should conclude there's not enough evidence because they can't rule out RR >= 1 at 95% confidence. Instead they conclude:

In comparison to SOC or placebo, IVM did not reduce all-cause mortality, length of stay or viral clearance in RCTs in COVID-19 patients with mostly mild disease. IVM did not have effect on AEs or SAEs. IVM is not a viable option to treat COVID-19 patients.

Bryant and Roman use similar methods, the difference in the confidence interval is because they picked different studies.

Bryant has different estimates for mild vs severe vs all cases. 0.38 is for all-cases to allow comparison with Roman batched all-cases together and has no breakdowns.

This third Bayesian (meta-?)meta-analysis concludes:

This Bayesian meta-analysis has shown that the posterior probability for the hypothesis of a causal link between, Covid-19 severity ivermectin and mortality is over 99%. From the Bayesian meta-analysis estimates the mean probability of death of patients with severe Covid19 to be 11.7% (CI 12.6 – 34.75%) for those given ivermectin compared to 22.9% (CI 1.83 – 27.62%) for those not given ivermectin. For the severe Covid-19 cases the probability of the 7 risk ratio being less than one is 90.7% while for mild/moderate cases this probability it is 84.1%.

In our view this Bayesian analysis, based on the statistical study data, provides sufficient confidence that ivermectin is an effective treatment for Covid-19 and this belief supports the conclusions of (Bryant et al., 2021) over those of (Roman et al., 2021).

The paper has also highlighted the advantages of using Bayesian methods over classical statistical methods for meta-analysis, which is especially persuasive in providing a transparent marginal probability distribution for both risk ratio 𝑅𝑅 and risk difference, 𝑅𝐷. Furthermore, we show that using 𝑅𝐷 avoids the estimation and computational issues encountered using 𝑅𝑅 , thus making full and more efficient use of all evidence.

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