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Comment by John Janik

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Physicist and Substack author writing on COVID-19 origins and Bayesian analysis
The WHO’s own expert panel published its final report. When you apply formal probability to their findings, the conclusions point somewhere the authors were unwilling to go.
AI Unverifiable (Feb 28, 2026)
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John Janik, "The Math Doesn’t Lie: A Bayesian Analysis of COVID-19’s Origin," Dr. John Janik, February 28, 2026.
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The clustering of early cases around the Huanan market reflects where the COVID-19 virus emerged, not just where testing looked
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AI Unverifiable The source URL does resolve to a Substack page titled “The Math Doesn’t Lie: A Bayesian Analysis of COVID-19’s Origin,” associated with the “Dr. John Janik” publication, and that publication bio is corroborated by the matching Bluesky profile. However, the fetched Substack page exposes only a JavaScript gate rather than the article body, and the submitter-provided passage is only a bibliographic citation line, not the quoted text itself. I therefore could not confirm that the quoted wording appears verbatim on the source URL or verify the stated publication date from accessible evidence. ([open.substack.com](https://open.substack.com/pub/johnjanik/p/the-math-doesnt-lie-a-bayesian-analysis?r=31yu6j&showWelcomeOnShare=true&utm_campaign=post&utm_medium=web)) · YouCongress gpt-5.4-2026-03-05 · 1h ago
replying to John Janik