***In fact, there appear to have been 2 separate spillover events. No early cases cluster around any other location, such as the WIV, so this already suspicious event essentially happened twice! ***
Note these claims have been seriously challenged in the past few months:
Lv et al (2024) find the multiple spillover theory is unlikely. A single point of emergence is more likely with lineage A coming first. So market cases are not the primary cases (all market linked cases were lineage B). Their findings are consistent with Caraballo-Ortiz (2022), Bloom (2021). t.co/50kFV9zSb6
Jesse Bloom showed again the available market samples don't support market origin. t.co/rorquFs1wm
Michael Weissman uses a mathematical argument to show ascertainment bias in early case data. (George Gao, the Chinese CDC head at the time, acknowledged this to the BBC last year - they focused too much on and around the market and may have missed cases on the other side of the city).
The Account that identified errors in Pekar et. al. leading to an erratum last year has found another significant error. Single spillover again looks more likely. t.co/GAPihZu51P
***In fact, there appear to have been 2 separate spillover events. No early cases cluster around any other location, such as the WIV, so this already suspicious event essentially happened twice! ***
Note these claims have been seriously challenged in the past few months:
Spatial statistics experts Stoyan and Chiu (2024) dispute the analysis that Huanan Seafood Market was necessarily early epicenter. https://academic.oup.com/jrsssa/advance-article-abstract/doi/10.1093/jrsssa/qnad139/7557954
Lv et al (2024) find the multiple spillover theory is unlikely. A single point of emergence is more likely with lineage A coming first. So market cases are not the primary cases (all market linked cases were lineage B). Their findings are consistent with Caraballo-Ortiz (2022), Bloom (2021). t.co/50kFV9zSb6
Jesse Bloom showed again the available market samples don't support market origin. t.co/rorquFs1wm
Michael Weissman uses a mathematical argument to show ascertainment bias in early case data. (George Gao, the Chinese CDC head at the time, acknowledged this to the BBC last year - they focused too much on and around the market and may have missed cases on the other side of the city).
arxiv.org/abs/2401.08680 (now published but paywalled https://academic.oup.com/jrsssa/advance-article/doi/10.1093/jrsssa/qnae021/7632556)
The Account that identified errors in Pekar et. al. leading to an erratum last year has found another significant error. Single spillover again looks more likely. t.co/GAPihZu51P
Weissman's Bayesian analysis provides a thorough overview and is probably as good a case for lab origin as any. https://michaelweissman.substack.com/p/an-inconvenient-probability