Astral Codex Ten

Xinfadi Market

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Xinfadi Market

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Xinfadi Market is a recurring venue in the Astral Codex Ten archive, appearing 2 times across 2 issues between March 28, 2024 and April 09, 2024. The archive places it in contexts such as “the big COVID outbreak in Beijing started at Xinfadi Market, their local seafood market”; “there was an outbreak in the Xinfadi Market in Beijing”; “the outbreak at Xinfadi Market was likely to be initiated by fomite transmission”. It most often appears alongside BANAL-52, China, Connor Reed.

Metadata

  • Category: Venues
  • Mention count: 2
  • Issue count: 2
  • First seen: March 28, 2024
  • Last seen: April 09, 2024

Appears In

Source Context

Recovered passages from the original issue text. When the raw archive preserved outbound links inside the source passage, they are listed directly under the quote.

Practically-A-Book Review: Rootclaim $100,000 Lab Leak Debate
March 28, 2024 · Original source
Lineage A (left) was used by the Minoan Cretans, but has never been deciphered. Lineage B (right) was used by the Mycaeneans for lists of palace goods. This matches Saar’s story above. The lab leaked to somewhere else in Wuhan, not the wet market. The virus spread undetected in the population for a while. During this time, it mutated to Lineage B. Then one of the people with Lineage B went to the wet market and started a superspreader event. The authorities sampled the patients, found Lineage B, then started looking elsewhere. Later they detected some of the earlier Lineage A cases. The market is unlikely to be the origin of the pandemic, because the original Lineage A strain wasn’t found there. Peter: Although Lineage A is evolutionarily older, Lineage B started spreading in humans first. We know this because Lineage B is more common. Throughout the early pandemic, until the D614G variant drove all other strains extinct, a consistent 2/3 of the cases were B, compared to 1/3 A. Both strains spread at the same rate, so the best explanation is that B started earlier than A. Since COVID doubles every 3-4 days, probably Lineage B started 3-4 days earlier than Lineage A, which explains why it’s always been twice as many cases. But also, Lineage B also has more internal genetic diversity than Lineage A. In general, older viruses have more genetic diversity (the “molecular clock”). This is further evidence that B started spreading first. Pekar 2022 and Pipes 2021 do analyses with known parameters for spread rate and diversity, and find 90%+ odds that Lineage B was the first one in humans. Why did the older strain start spreading later? Probably the virus crossed from bats into raccoon-dogs on some raccoon-dog farm out in the country. It spread in the raccoon-dogs for a while, racking up mutations, including the (less mutated) Lineage A strain and the (slightly more mutated) Lineage B strain. Then several raccoon-dogs were taken to Wuhan for sale, including one with Lineage A and another with Lineage B. The one with Lineage B passed its virus to humans earlier. Then 3-4 days later, the Lineage A one passed its virus to humans. Lineage A was first found in a Wuhan neighborhood right next to the wet market (closer to the wet market than 97% of Wuhan’s population). Again, it would be a bizarre coincidence if a lab leak pandemic was first detected at a wet market. But it would be an even more bizarre coincidence if a lab leak pandemic separated into two strains, and both were first detected at a wet market! Although no known wet market cases were Lineage A, a positive Lineage A environmental sample was found at the wet market, and everyone agrees most cases went undetected. So maybe the Lineage B raccoon-dog spread its virus to a vendor, and that sub-strain mostly stayed in the market. But the Lineage A raccoon-dog spread its virus to a customer, who went back to his house nearby, and that strain spread in the neighborhoods next to the market. This is the only story that explains the evolutionary precedence of A, the greater spread and older molecular clock of B, and the fact that both strains were first found very close to the wet market. Yuri/Saar: Lineage B could be more common and diverse because it got the advantage of a super-spreader event in the wet market. There are a few scattered cases of intermediates between A and B, and a few other scattered cases of lineages that seem even more ancestral (ie closer to the bat virus) than either. This doesn’t make sense in a double spillover hypothesis. But it does make sense if the lineages separated in human transmission somewhere between the lab and the first super-spreader event at the wet market. Peter: Again, the wet market wasn’t a super-spreader event. COVID spread in the wet market at exactly its normal spread rate, doubling about once every 3.5 days. Stop calling the wet market a super-spreader event. The scattered cases of “intermediates” are sequencing errors. They were all found by the same computer software, which “autofills” unsequenced bases in a genome to the most plausible guess. Because Lineage B was already in the software, depending on which part of a Lineage A virus you sequenced, you might get one half or the other autofilled as Lineage B, which looked like an “intermediate”. We know this because all the supposed “intermediates” were partial cases sequenced by this particular software. We can confirm this by noting that there are too many intermediates! That is, where Lineage A is (T/C) and Lineage B is (C/T), the software found both (T/T) “intermediates” and (C/C) “intermediates”. But obviously there can only be one real intermediate form, and we have to dismiss one or the other. But in fact we can dismiss both, because they were both caused by the same software bug. The scattered “progenitor” cases - those closer to the ancestral bat virus than either A or B - are reversions, ie cases where a new mutation in the virus happened to hit an already-mutated base and shift it back towards the ancestral virus. We know this because all of these “progenitors” were scattered cases found months after the pandemic started, often in entirely different countries from Wuhan. If these were real progenitor viruses, they would have either fizzled out or exploded into a substantial portion of all cases, not be found one time in one guy in Malaysia. Given the number of mutations the virus developed over the course of the pandemic, it’s inevitable that some of them would be mutations that bring it closer to the original bat virus, and in fact we find the number of “progenitors” found very nicely matches the number of progenitor-appearing viruses we would expect by chance. And in many cases, we know the “progenitors” are newer than the original lineages, because they also have some of the later mutations that Lineage A or B picked up along the way, alongside their apparent ancestral-bat-virus-like mutations. Session 2: Viral Genetics Yuri: Two years before COVID, scientists at the Wuhan Institute of Virology, together with colleagues at the University of North Carolina, sent in a grant proposal for the DEFUSE program. This program, intended to locate and better understand potential future pandemic viruses, involved going into bat caves and collecting new coronaviruses. Once they had them, they would do gain-of-function: specifically, they would add a furin cleavage site to make them more infectious and see what happened. (quick interlude: COVID’s spike protein has two sections: one binds to human cells through the ACE2 receptor, the other helps fuse with the cell after binding. In order to avoid the immune system, it hides both of these into one spike. But when it reaches a cell, it needs to separate them again. It takes advantage of a human respiratory enzyme, furin, to do the separation - this also ensures that it only infects its primary target, human respiratory cells. The part of COVID that lets it get separated by furin is called the “furin cleavage site”. COVID’s bat-virus ancestors were gastrointestinal viruses; the addition of a furin cleavage site was what made them respiratory viruses.) We’ve found two close relatives of COVID: bat viruses called RATG-13 and BANAL-52. In particular, COVID looks more or less like BANAL-52 plus a furin cleavage site. There are 1500 sarbecoviruses, members of the family of viruses that includes SARS and SARS2/COVID. None of them except COVID have furin cleavage sites. BANAL-52, COVID’s closest ancestor, doesn’t even have anything resembling one that could mutate into a functional furin cleavage site like COVID’s. Instead, COVID - which mostly just resembles BANAL-52 with a few scattered single-point mutations - has twelve completely new nucleotides in a row - a fully formed furin cleavage site that came out of nowhere. There is nowhere else in the genome that COVID differs from BANAL-52 in such a profound way. It’s just BANAL-52 plus a little bit of random mutation plus a fully-formed furin cleavage site that came out of nowhere. Further, the furin cleavage site is weird. It uses the protein arginine twice. But instead of the nucleotides coding for arginine in the usual viral way, both times it uses the codons CGG - the way that higher animals code for arginine. This works fine - it’s just not how viruses do it. So the obvious conclusion is that WIV, which said in 2018 that it was going to find viruses and add furin cleavage sites to them, found a close relative of BANAL-52 and added a furin cleavage site. Since they were humans, and most familiar with the human way of encoding arginine, they added it as CGG both times. COVID seemed surprisingly optimized for infecting humans. Of fifty animals it was tested in, including the usual coronavirus intermediate hosts (pangolins, raccoon-dogs, etc), it was best at infecting human cells. Further, a virus that enters a new species will usually show a burst of mutations as it “figures out” the best way to adapt to that species’ unique biology. But COVID has had a pretty constant mutation rate in humans, from the beginning of the pandemic to the end. That suggests it was already adapted to humans. This could be because the lab screened for viruses with existing adaptations, because they passed it through humanized mice in the lab, or because it adapted in the hundreds of undetected cases that happened between the lab and detection in the wet market. Usually, research with potentially dangerous coronaviruses is done in BSL-3 or 4, ie high to very-high security. But WIV was irresponsibly doing it in BSL-2, ie medium security. The researchers weren’t even required to wear masks. In general, about 1/500 labs will leak any given pathogen they’re working on (?!). But because WIV was researching such an infectious virus in such an irresponsible way, the odds of a leak were much higher. The most likely explanation for all these facts is that WIV went ahead and did the gain-of-function research they said they were going to do (the particular DEFUSE grant proposal we know about got rejected, but it proves that Wuhan wanted to do this, and they could easily have gotten funding somewhere else, or done it out of their regular budget). They found a close relative of BANAL-52 and added a furin cleavage site as a simple twelve-nucleotide insertion, using the human method of encoding arginine that their genetic engineers were familiar with. Then it leaked, spread for a while in the general Wuhan population, and eventually made it to the wet market where it got detected. Peter: As mentioned earlier, the DEFUSE grant was rejected. Further, the grant said that the Wuhan Institute of Virology was responsible for finding the viruses, and the University of North Carolina would do all the gain-of-function research. This was a reasonable division of labor, since UNC was actually good at gain-of-function research, and WIV mostly wasn’t. They had done a few very simple gain-of-function projects before, but weren’t really set up for this particular proposal and were happy to leave it for their American colleagues. Even if WIV did try to create COVID, they couldn’t have. As Yuri said, COVID looks like BANAL-52 plus a furin cleavage site. But WIV didn’t have BANAL-52. It wasn’t discovered until after the COVID pandemic started, when scientists scoured the area for potential COVID relatives. WIV had a more distant COVID relative, RATG-13. But you can’t create COVID from RATG-13; they’re too different. You would need BANAL-52, or some as-yet-undiscovered extremely close relative. WIV had neither. Are we sure they had neither? Yes. Remember, WIV’s whole job was looking for new coronaviruses. They published lists of which ones they had found pretty regularly. They published their last list in mid-2019, just a few months before the pandemic. Although lab leak proponents claimed these lists showed weird discrepancies, this was just their inability to keep names consistent, and all the lists showed basically the same viruses (plus a few extra on the later ones, as they kept discovering more). The lists didn’t include BANAL-52 or any other suitable COVID relatives - only RATG-13, which isn’t close enough to work. Could they have been keeping their discovery of BANAL-52 secret? No. Pre-pandemic, there was nothing interesting about it; our understanding of virology wasn’t good enough to point this out as a potential pandemic candidate. WIV did its gain-of-function research openly and proudly (before the pandemic, gain-of-function wasn’t as unpopular as it is now) so it’s not like they wanted to keep it secret because they might gain-of-function it later. Their lists very clearly showed they had no virus they could create COVID from, and they had no reason to hide it if they did. COVID’s furin cleavage site is admittedly unusual. But it’s unusual in a way that looks natural rather than man-made. Labs don’t usually add furin cleavage sites through nucleotide insertions (they usually mutate what’s already there). On the other hand, viruses get weird insertions of 12+ nucleotides in nature. For example, HKU1 is another emergent Chinese coronavirus that caused a small outbreak of pneumonia in 2004. It had a 15 nucleotide insertion right next to its furin cleavage site. Later strains of COVID got further 12 - 15 nucleotide insertions. Plenty of flus have 12 to 15 nucleotide insertions compared to other earlier flu strains. Sometimes insertions happen because of a mistake in viral replication. Other times the virus gets confused between its own RNA and its host’s, and splices a bit of the host RNA into the virus. This would neatly explain why the insertion used the unusual coding CGG for arginine, which is common in animals but rare in viruses. On the other hand, it’s not that rare in viruses - COVID uses CGG for arginine about 3% of the time. And human engineers don’t necessarily use it any more than that - Peter was able to find one example of humans adding arginine to a virus, and 0 out of the 5 arginines added were CGG. COVID’s furin cleavage site is a mess. When humans are inserting furin cleavage sites into viruses for gain-of-function, the standard practice is RRKR, a very nice and simple furin cleavage site which works well. COVID uses PRRAR, a bizarre furin cleavage site which no human has ever used before, and which virologists expected to work poorly. They later found that an adjacent part of COVID’s genome twisted the protein in an unusual way that allowed PRRAR to be a viable furin cleavage site, but this discovery took a lot of computer power, and was only made after COVID became important. The Wuhan virologists supposedly doing gain-of-function research on COVID shouldn’t have known this would work. Why didn’t they just use the standard RRKR site, which would have worked better? Everyone thinks it works better! Even the virus eventually decided it worked better - sometime during the course of the pandemic, it mutated away from its weird PRRAR furin cleavage site towards a more normal form. Further, COVID’s furin cleavage site was inserted via what seems to be a frameshift mutation - it wasn’t a clean insertion of the amino acids that formed the site, it was an insertion of a sequence which changed the context of the surrounding nucleotides into the amino acids that formed the site. This is a pointless too-clever-by-half “flourish” that there would be no reason for a human engineer to do. But it’s exactly the kind of weird thing that happens in the random chance of evolution. COVID is hard to culture. If you culture it in most standard media or animals, it will quickly develop characteristic mutations. But the original Wuhan strains didn’t have these mutations. The only ways to culture it without mutations are in human airway cells, or (apparently) in live raccoon-dogs. Getting human airway cells requires a donor (ie someone who donates their body to science), and Wuhan had never done this before (it was one of the technologies only used at the superior North Carolina site). As for raccoon-dogs, it sure does seems suspicious that the virus is already suited to them. The claim that COVID is uniquely adapted to humans is false. The paper that claimed that defined how well COVID was adapted to different animals by those animals’ difference (on the relevant cell receptors) from humans. So in its methodology, humans came out #1 by default. If you don’t do that, COVID is better-adapted to many other animals. It’s not necessarily true that viruses see a burst of mutations when they enter a new host. COVID spread to deer and mink, and in neither case was there a burst of mutations. COVID has a pretty simple job of infecting respiratory cells and is already very good at it, regardless of species. In Yuri’s model, Wuhan Institute of Virology picked up a discarded grant and decided to do the gain-of-function half allotted to a different university, despite their relative inexperience. They skipped over all the SARS-like viruses they were supposed to work on, and all the standard gain-of-function model backbones, in favor of BANAL-52, a virus which would not be discovered for another two years, but which they somehow had samples of, which they had for some reason decided to keep secret despite its total lack of interestingness. Then they would have had to eschew all usual gain-of-function practices in favor of inserting a weird furin cleavage site that shouldn’t have worked according to the theory they had at the time, via a frameshift mutation. Then they would have had to culture it, a technique beyond their limited capabilities. Then it would have had to leak, and magically show up again in front of the raccoon-dog stall at a wet market. Yuri: WIV wouldn’t have needed to keep BANAL-52 “secret” in some kind of sinister way. Plenty of researchers have backlogs of work they haven’t published yet. Probably they a found BANAL relative in one of their normal sampling trips, did some preliminary studies on it, and planned to publish it later once they cleaned up their data. Everyone works like this. The part of DEFUSE saying that they would only work on viruses that were 95% similar to SARS is unclear and might mean something else. It looks more like they say they’ll start with those viruses, but also do some work on novel viruses. BANAL-52 could have been one of the novel viruses. The furin cleavage site is weird, but the researchers might have done that on purpose, to make the virus easier to keep track of, or to test different furin cleavage sites. Depending on the exact BANAL-52 relative they used, it might not even be a frameshift; there’s a particular way to spell serine that would make the insertion more natural. The claims that COVID can’t be cultured in normal media are based on speculative original research by Peter and might not hold up. Peter: WIV did most of its virus-gathering in a trip to a Yunnan cave between 2010 and 2015. All those viruses have long since been processed and added to the database. There’s no sign that they made more trips to Yunnan caves, and no reason for them to keep that secret. So the idea that they might just have some new viruses they didn’t publish doesn’t hold up. But suppose they did make more trips. Given the amount of time between the DEFUSE proposal and COVID, if they kept to their normal virus-collection rate, they would have gotten about thirty new viruses. What’s the chance that one of those was BANAL-52? There are thousands of bat viruses, and BANAL-52 is so rare that it wasn’t found until well after the pandemic started and people were looking for it very hard. So the chance that one of their 30 would be BANAL-52 is low. Also, they said in DEFUSE that they planned to go back to the same Yunnan cave. But BANAL-52 was found far away from that cave, so unless it ranged over a wide area, they probably couldn’t have found it even if they got very lucky. Session 3: Closing Arguments This third debate was supposed to be about “inference”, ie how much Bayesian evidence was provided by each of the facts given so far, and how to fit them into the Rootclaim probabilistic model. I’m going to relegate my summary of the more probabilistic half to the next section of this post, and just include the closing arguments here. Saar: Peter’s case hinges on the idea that it’s very improbable that a lab leak pandemic would first show up at a wet market. But this isn’t necessarily improbable. The Huanan Seafood Market had several factors that made it a likely location for a superspreader event. It was busy, with over 10,000 visitors a day. Many of the people there (eg the 1,000 vendors) came back daily, letting them reinfect each other. It had poor ventilation, especially in the high-positivity area near the raccoon-dog stall. It had cold wet surfaces on which the virus could survive for long periods. It was indoors, which prevented UV light from killing the virus. Given a small amount of sporadic COVID going around Wuhan, it’s not surprising for the first place it started spreading en masse to be a wet market. In fact, we have several examples of this. When China was COVID Zero, there would occasionally be small outbreaks that the authorities would have to contain. Most of these were at wet markets. For example, the big COVID outbreak in Beijing started at Xinfadi Market, their local seafood market. This couldn’t be an animal spillover, because there were no raccoon-dogs or other weird wildlife there. So it must be that wet markets are natural places for superspreader events. There are several other examples, which make up about half of the total outbreaks in Zero COVID era China, plus others in Singapore and Thailand. Since COVID clusters concentrate in wet markets even when there is no animal spillover, we should accept this as a property of the virus, and not attribute any significance to the fact that this happened in Wuhan too. Peter: About 1/10,000 citizens of Wuhan was a wet market vendor. So there’s a 1/10,000 chance that the first known COVID case should be a wet market vendor by chance alone. Weibo lists the most popular places for people to check in to their network on their phones, and the wet market was the 1600th most popular place in Wuhan, meaning that if you weight locations by busy-ness, there’s a less than 1/1600 chance that the first cases would be in the wet market. Yes, the wet market is indoors, has mediocre ventilation, has repeat visitors, etc. So do thousands of other places in Wuhan, like schools, hospitals, workplaces, places of worship. The wet market isn’t special in any way. And again, it wasn’t a superspreader event! COVID spread at the same rate in the wet market as it does everywhere else: doubling once per 3.5 days. It doesn’t matter what kinds of arguments you can come up with for why the wet market should have been the perfect superspreader event location, we can look at it and see that it wasn’t. It’s an environment that spreads COVID at exactly the normal rate. Zero COVID era Chinese outbreaks were concentrated in wet markets because they received infected animal products. We know why there was an outbreak in the Xinfadi Market in Beijing: it was because the seafood stall got frozen fish from some non-Zero-COVID country, the fish had COVID particles on it, and the vendor got infected and spread it to everyone else. Something like this is true for the other Chinese wet market based outbreaks we know about it. So this makes the opposite point you think it does: wet markets start outbreaks because there are infected goods being sold there. Then the virus spreads through the wet market at a completely normal rate. Saar: The Weibo list of 1600 places bigger than the wet market is likely inaccurate, because it's based on check-in data and people don't check in to seafood markets. Most of those 1600 places aren't amenable to superspread. The 70 markets supposedly bigger than Huanan are irrelevant, because they're supermarkets, open air markets, etc. Huanan is the largest seafood market in central China, and a more likely place for the first cluster of cases to be noticed. Markets weren't a common spillover location in SARS1, so the zoonosis hypothesis hasn't "called" this event in a way that should give them a high Bayes factor. And there’s still plenty of evidence for isolated (though not super-spreading) pre-market cases. A British expatriate in Wuhan, Connor Reed, says he got sick in November, three weeks before the first wet market case. Later the hospital tested his samples and said it was COVID. Another paper reports 90 cases before the first wet market one. Peter: Connor Reed was lying. The case wasn’t reported in any peer-reviewed paper. It was reported in the tabloid The Daily Mail, months after it supposedly happened. He also told the Mail that his cat died of coronavirus too, which is rare-to-impossible. Also, to get a positive hospital test, he would have had to go to the hospital, but he was 25 years old and almost no 25-year-olds go to the hospital for coronavirus. His only evidence that it was COVID was that two months later, the hospital supposedly “notified” him that it was. The hospital never informed anyone else of this extremely surprising fact which would be the biggest scientific story of the year if true. So probably he was lying. Incidentally, he died of a drug overdose shortly after giving the Mail that story; while not all drug addicts are liars, given all the other implausibilities in his story, this certainly doesn’t make him seem more credible. And in any case, he claimed he got his case at a market “like in the media” The other 90 cases are also fake. A lab leak guy found a paper that mentioned 90 more cases than other papers, and made up a conspiracy theory where the author was trying to secretly communicate that there had been 90 secret cases before any of the confirmed cases, even though there was nothing about this in the text of the paper. But actually that paper just counted cases differently than other papers, and they were referring to normal cases after the pandemic officially started. Again, I’ll come back to the discussion about inference later, but for now, here’s a table of both sides’ reasoning. This exact presentation comparing both analyses is mine3, but you can see Saar’s version here, and Peter’s starting at 45:33 of this video. Slightly made up; the two sides didn’t express their probabilities in the same way and I had to make editorial decisions to match them. Note that these aren't entirely comparable because Peter is being laxer about out-of-model probability than Saar. Although Saar's final odds here are 533-to-1, this just the central estimate. Rootclaim’s real final probability is 94% lab leak. You can see their analysis here. And The Winner Is . . . … … … … … Peter and the zoonosis hypothesis. This was a decisive victory. There were two judges, who each gave separate verdicts (or were allowed to declare a draw). Both judges decided in favor of Peter. You can see the judges’ own summary of their reasoning here (Will, Eric) Manifold agreed with the judges. There was a prediction market on who would win. It started out 70-30 in favor of lab leak. As the videos came out, zoonosis started doing better and better. I don’t want to take the exact final numbers too seriously, since I think some of the later price increases involved hints from the participants’ behavior. But it’s clear which way viewers thought the wind was blowing4. Around the same time, the Good Judgment Project - Philip Tetlock’s group studying superforecasters - put out a report on the lab leak hypothesis. After studying it in depth, his forecasters ended up 75-25 in favor of zoonosis. The Rootclaim debate was one of ten sources they said they found especially interesting. And also around the same time, and unrelated to any of this, the Global Catastrophic Risks Institute surveyed experts (“168 virologists, infectious disease epidemiologists, and other scientists from 47 countries”) and found the same thing (though see here for some potential problems with the survey): For what it’s worth, I was close to 50-50 before the debate, and now I’m 90-10 in favor of zoonosis. III. The Math And The Aftermath The third debate session was about “inference”, how to put evidence together. I put this part off until after disclosing the winner, because I wanted to talk about some of these issues at more length. The Math: Judges Both judges included a probabilistic analysis in their written decision. Here’s the same table as above, expanded to add the judges: I shoehorned the judges’ factors into the categories I already had; some of them were actually subtly different from Peter’s, Saar’s, and each other’s. The “priors” category is especially a mess here. We’ll go over these later, but I get the impression that they both thought of probabilistic analyses as an afterthought. For example, Judge Eric wrote 30,000 words about which considerations moved him, and only then includes the analysis, saying: I am not convinced that this Bayesian calculation is even an appropriate way to estimate the relative posterior probability of Z and LL; it just seemed fair that after criticizing Rootclaim’s calculations at length I should make an attempt at it myself. Judge Will’s decision ran to 10,000 words. He said he independently tried both reasoning it out intuitively, and running the Bayesian analysis, and was relieved when these two methods returned the same result. He said: I am skeptical that the Bayesian decision making/evaluation methods are any more "objective" than [intuitive reasoning]. I think they maximize legibility, not objectivity, and tend to hide the intuitive/heuristic portion in the data inclusion step and values, where it’s harder to see . . . I am not skilled in the Bayesian method, and I am sure I made significant mistakes. More time and practice would improve and refine my estimates. At the fundamental rules of the universe level, Bayesian analysis must be the best way to evaluate evidence. However, I am unsure that it’s a good strategy for a human given our cognitive limitations, and doubly unsure it’s truly being used (in the dispassionate sense) where the outcome is social desirability/fame/Twitter likes. I’m focusing on this because Saar’s opinion is that the debate went wrong (for his side) because he didn’t realize the judges were going to use Bayesian math, they did the math wrong (because Saar hadn’t done enough work explaining how to do it right), and so they got the wrong answer. I want to discuss the math errors he thinks the judges made, but this discussion would be incomplete without mentioning that the judges themselves say the numbers were only a supplement for their intuitive reasoning. That having been said, let’s look deeper into some of Saar’s concerns. The Math: Extreme Odds Saar complained that Peter’s odds were too extreme. For example, Peter said there was only a 1/10,000 chance that a lab leak pandemic would first show up at a wet market. Peter’s argument went something like: obviously a zoonotic pandemic would start at a site selling weird animals. But a lab leak pandemic - if it didn’t start at the lab - could show up anywhere. 1/10,000 Wuhan citizens work at the wet market. So if a lab leak was going to show up somewhere random, the wet market was a 1/10,000 chance. Saar had specific arguments against this, but he also had a more general argument: you should rarely see odds like 1/10,000 outside of well-understood domains. In his blog post, he gave this example: A prosecutor shows the court a statistical analysis of which DNA markers matched the defendant and their prevalence, arriving at a 1E-9 probability they would all match a random person, implying a Bayes factor near 1E9 for guilty. But if we try to estimate p(DNA|~guilty) by truly assuming innocence, it is immediately evident how ridiculous it is to claim only 1 out of a billion innocent suspects will have a DNA match to the crime scene. There are obviously far better explanations like a lab mistake, framing, an object of the suspect being brought by someone to the scene, etc. So the real p(wet market|lab leak) isn’t the 1/10,000 chance a pandemic arising in a random place hits the wet market, but the (higher?) probability that there’s something wrong with Peter’s argument. Then Saar tried to show specific things that might be wrong with Peter’s argument. I didn’t find his specific examples convincing. But maybe the question shouldn’t be whether I agreed with him. It should be whether I’m so confident he’s wrong that I would give it 10,000-to-1 odds. This makes total sense, it’s absolutely true, and I want to be really, really careful with it. If you take this kind of reasoning too far, you can convince yourself that the sun won’t rise tomorrow morning. All you have to do is propose 100 different reasons the sunrise might not happen. For example: The sun might go nova.
Inline links: Pekar 2022, Pipes 2021, says, 3, here, this video, https://substackcdn.com/image/fetch/$s_!8aU2!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F815fe32d-d7ea-401b-b3a2-d8cd25b52ee8_490x780.png, https://substackcdn.com/image/fetch/$s_!0Tm_!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fd0492f69-7b7e-4611-9d76-64ef8d7f59d5_511x511.png, Will, Eric, agreed, 4, put out a report on the lab leak hypothesis, https://substackcdn.com/image/fetch/$s_!g7k2!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F37f1b493-b556-41ec-925e-03f9d8bc26cb_1456x849.webp, surveyed experts, see here, https://substackcdn.com/image/fetch/$s_!Zejl!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fe9c88e87-b6ca-4c6d-840e-24da726f50b7_975x365.png, https://substackcdn.com/image/fetch/$s_!T5rV!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4983e2cd-4151-42de-9685-08037ef7a8e8_635x788.png
Highlights From The Comments On The Lab Leak Debate
April 09, 2024 · Original source
This collapses the ‘extreme coincidence’ claim, which as explained above, turns lab-leak into the leading hypothesis. My strongest disagreement is with his Point 3 - the inference from other seafood-market-based COVID spread events. Saar writes: A common objection to this method is that these outbreaks are caused by cold-chain products brought into these markets. However, this still fails to explain why markets form these early clusters and not the many other places where cold chain products are delivered to. Additionally, this only demonstrates the importance of cold wet surfaces in preserving SARS2 infectivity, further strengthening the hypothesis in method 1 that a crowded location with many wet surfaces like HSM is highly conducive for rapid SARS2 spread. Last, it also opens the possibility that the HSM outbreak was also caused by cold-chain products. This would reduce the significance of Wuhan being the outbreak location (as the product could have come from anywhere), but since the other evidence for lab-leak is so strong, Wuhan can be given no weight and still lab-leak would be highly likely – Rootclaim’s conclusion will only drop from 94% to 92%. Most of these outbreaks have been traced back to either a migrant worker (eg a fisherman from a country with COVID sells fish at the market of a country with Zero COVID) or a cold chain product. For example, here’s Dai et al on the Xinfadi outbreak, the most important event of this type: According to a joint publication by the Beijing CDC and 13 research institutions, the outbreak at Xinfadi Market was likely to be initiated by fomite transmission from contaminated foods imported via cold-chain logistics (Pang et al., 2020; Beijing Daily, 2020b). Based on the epidemiological investigations at the Xinfadi Market, the researchers preliminarily concluded that booth #S14 in the aquaculture product selling area on the basement floor of the primary trading hall was the source of the initial transmission. Specifically, five customers were tested positive for IgG/IgM antibodies against SARS-CoV-2 in serological screenings, all of whom visited booth #S14 on May 30 and 31, 2020. On May 30, 2020, the owner of booth #S14 procured imported and fully packaged salmon from a company's cold storage warehouse, then cut and processed the salmon for sale at the Xinfadi Market. Laboratory tests showed that sample swabs from five salmon fish from this supplier were tested positive by examining all salmon in the original sealed packages (n = 3582) in the cold storage facility. Viral genome sequencing showed that the viral strain isolated from one of the positive salmon swabs was homologous to that isolated from the infected persons and environmental samples at the Xinfadi Market (Beijing Daily, 2020b). The joint study reported that an ancestral strain isolated from the Xinfadi Market in Beijing was markedly different from the strains identified in two preceding outbreaks in China and the sequences obtained in March 2020 in Beijing. Phylogenetic analysis assigned the ancestral Xinfadi strain to clade B.1.1. Given the fact that the ancestral sequences were mainly identified in Europe, the strain was more likely to be imported to Beijing rather than derived from strains previously circulating in China (Pang et al., 2020). I know China has a bias towards believing frozen food COVID explanations, but this all sounds pretty convincing to me. Why is it more often markets than other places with cold chain products? Partly it’s the migrant workers - a lot of seafood markets are right next to seaports, and the contact tracing eventually traces back to a fisherman who came in through the seaport - I don’t think this is any more mysterious than epidemics often starting via airport or any other transportation hub. But even just keeping the focus on cold chain products, - there have also been outbreaks in seafood distribution warehouses, on docks, and in a seafood processing work area. Markets have many more people than any of those locations, and maybe (total speculation) cutting on cutting boards could aerosolize bits of fish. The strongest evidence that the Wuhan / Huanan Seafood Market epidemic wasn’t caused by migrant workers or imported seafood products is that there was no previous COVID-infected source of workers or seafood. If there had been, we would have noticed when the outbreak there spread (see Section 1.4 on Brazil). Responses to a few of Saar’s other points below: How many locations other than markets provide an interface with wildlife? Were markets actually identified in advance to be high-risk spillover locations or only in retrospect? I think scientists had called wet markets as an especially dangerous potential transmission location in advance. See for example Infectious Diseases Emerging From Chinese Wet Markets, published in 2006, which says: » “In Chinese wet-markets, unique epicenters for transmission of potential viral pathogens, new genes may be acquired or existing genes modified through various mechanisms such as genetic reassortment, recombination and mutation. The wet-markets, at closer proximity to humans, with high viral burden or strains of higher transmission efficiency, facilitate transmission of the viruses to humans.” In 2004, a paper on an emerging bird flu expressed hope that it would not spread too widely, but concluded that: » “Even in the event of yet another lucky escape, more measures must be taken to limit the amplification of viruses with pandemic potential in the wet markets around the world.” In 2007, Reuters published an investigation: Chinese Markets May Be Breeding Ground For Deadly Viruses, which said things like: » “We face similar threats from other viruses and such epidemics can happen because we continue to have very crowded markets in China," said Lo Wing-lok, an infectious disease expert in Hong Kong. "Even though official measures are in place, they are not faithfully followed. We are not talking about just civet cats, but all animals," he added.” Wet Markets, A Continuing Source Of SARS And Influenza, published 2004, is admittedly focusing on the next SARS1 outbreak instead of on SARS2, but gets bonus points for mentioning both wet markets and labs as likely causes of the next pandemic: » “Will SARS reappear? This question confronts public-health officials worldwide, particularly infectious disease personnel in those regions of the world most affected by the disease and the economic burden of SARS, including China, Taiwan, and Canada. Will the virus re-emerge from wet markets or from laboratories working with SARS CoV, or are asymptomatic infections ongoing in human beings? Similar questions can be asked about a pandemic of influenza that is probably imminent. Knowledge of the ecology of influenza in wet markets can be used as an early-warning system to detect the reappearance of SARS or pandemic influenza.” Saar mentions that there are several other possible sources like restaurants or farms. I think Peter demonstrated during the debate that pandemics are unlikely to start in rural areas, so farms aren’t that important. Restaurants mostly source their products from wet markets. During SARS1, some pandemics started in restaurants because they kept the civets in cages next to the diners (like how some Western restaurants keep lobsters). After SARS1, restaurants stopped doing that and became a less likely spillover location. Saar again: Scott quotes Peter, who implies that under the lab-leak hypothesis, we would expect the confirmed early cases to be centered around the WIV. However, cases are not expected to center on the lab. The lab is not spraying viruses into the air or hosting thousands of locals daily. If a worker gets infected, they spread the virus to their friends and family at completely different locations. In most places with an outbreak of known origin, epidemics show some geographic clustering. This has been true ever since the very beginning of epidemiology, when John Snow successfully traced a cholera outbreak back to its origin at a contaminated water pump by taking the center of the map of cholera cases. This isn’t a 100% law of nature; an infected lab worker might get lucky and not pass it to any of his lab co-workers. Still, we might expect him to infect his family, the stores he went to, or the restaurants he went to. If he lived near his workplace, these might also be near the lab. If he didn’t - let’s say he lived on the other side of town and had a long commute - he would start a cluster near his house, or his favorite store, or his favorite restaurant. Then the people there would infect their families/co-workers/stores/restaurants. The cluster would start somewhere! Sure, some people would infect nobody close to their work or home, and instead just infect one person a hundred miles away who they breathed on during a trip - but this is the exception, not the rule. So you wouldn’t expect a totally random distribution of cases all around Wuhan. There would be one center, or maybe several centers. But none of the claims that COVID was quietly spreading for months before the wet market have pointed to some alternate center of cases. If COVID was spreading for months before the lab, it somehow spread in a completely diffuse geographical pattern, with people exactly as likely to infect people far away from them as close to them - until it reached the wet market in December, and then spread in the normal center-radiating-outward way that every other infection spreads. All the evidence trying to support a spillover at the market is based on complex models with many single points of failure, built from unreliable and biased data. Therefore, it is difficult to give this evidence significant weight as there is always a possibility of errors in the data or its interpretation. More on this in the UFO comment below. Disagree. “First known case was at a wet market” is as simple as it comes. Certainly it’s less complex than “the virus has a 12 nucleotide insertion at the furin cleavage site, and even though those sometimes happen by natural recombination probably this one didn’t, and even though it looks out of frame maybe there was some weird thing going on with serine that made it in frame this one time only”, which is Saar’s star piece of evidence. I understand Saar thinks he can come up with lots of objections to “seen near wet market is suspicious for wet market origin”, then claim that getting over those objections requires “complexity”. But if Peter had no dignity, he could also come up with lots of objections to “seen in same city as Wuhan Institute of Virology is suspicious". He could say that maybe the civet farms of Hubei province were uniquely blah blah blah, and then Saar would have to prove that the civet farms weren’t uniquely blah blah blah, and then he could say “Oh, sure seems like you have a complex model with lots of unique points of failure, it all depends on fifty facts about the regulation of civet farms.” To illustrate what a market looks like in a real zoonotic pandemic, consider this study from SARS1. The researchers went to a random market and sampled the wildlife sold there. 4 of 6 civets sampled were positive, and 3 of them were phylogenetically distinct (i.e. infected in completely different places). A scientist I talked to says the 3 phylogenetically distinct lineages were most likely sampling errors. Still, this seems irrelevant to me since, again, no raccoon-dogs were tested. Scott explains that Covid’s closest known relative, BANAL-52, is rare and so it’s highly unlikely the WIV would’ve had it available as the starting point to engineer Covid . . . This is a basic mistake. SARS2 is not based on BANAL-52 but a relative of it. There is nothing unlikely here. No BANAL-52 relative close enough to create COVID from has ever been discovered. By mentioning BANAL-52, I was trying to be maximally charitable to the lab leak side. In order to create COVID, they would need a virus very close to COVID. But in years and years of searching, nobody has ever discovered a virus like this. Therefore it must be rare. As a way of bounding how rare, let’s see how rare the closest virus ever discovered is. That’s BANAL-52. It is very rare. Therefore, the COVID ancestor must be rarer than that. I don’t know how strong this argument is, because maybe there are millions of rare viruses capable of becoming pandemics, such that getting any one of them is very easy, even though each one individually is rare. The version of this I find convincing is that it should be a probabilistic cost to say that WIV did gain-of-function on a seemingly undiscovered and so-far-very-hard-to-discover rare virus instead of on any of the usual SARS-like viruses that people do their gain-of-function research on. Overall, all attempts to portray [Connor Reed] as an unstable, delusional person were unsuccessful. He is an ordinary person who very accurately described Covid-19 symptoms in real-time and claims to have received a positive test result. The timing and location matches the lab leak hypothesis and is impossible for the HSM claim. Therefore, they must discredit him. It is worth noting here the biased evidentiary standards used by zoonotic proponents. Reed’s testimony about his sickness, given on camera to multiple outlets, is deceitful and should be ignored. Yet, an anonymous voice testimony in one Chinese publication is definitely identified as Mr. Chen (another possible pre-HSM case) and should be considered reliable. See above for why I don’t trust Connor Reed. I’m not sure why Saar attributes Mr. Chen to “an anonymous voice testimony in one Chinese publication”. When I looked for Chen information, I got this thread, where it’s attributed to two Chinese hospital doctors, cross-checked with the Chinese COVID data repository, and double-cross-checked with the supplementary table in a peer-reviewed paper published by a team of Wuhan doctors. To understand how ridiculous the claim is that the HKU1 insertion looks just as engineered as SARS2’s, here are their alignments. Hopefully that should be enough. COVID: HKU1: I’m not a virologist, but I question how this comparison works. Surely HKU1 got its insert on some specific day. If you take the virus the day before, and then the other virus the day after, there will be no differences except the insert, and it will look just like COVID (ie an insert without many other mutations). The fact that the COVID comparison has few mutations, and the HKU1 insert has many mutations, just shows that whatever older virus we chose to compare HKU1 to is more distant from HKU1 than BANAL-52 (or whatever) is from COVID. Or am I missing something here? [The evidence that China tried to cover up zoonosis from the start] is untrue. They clearly said from the start this is a zoonotic spillover at HSM, and at least part of the government went to immense efforts to identify the animal, close farms, etc. (and of course couldn’t find any infected animal). Only in late 2020 did they start suspecting an import from cold-chain products after having multiple outbreaks that seem related to cold-chain products. From a Vox article from March 2023: From the start, the Chinese government interfered with efforts by both Chinese and international experts to study the pandemic, including its origins. Reporting by the AP found that even as WHO officials were publicly praising China’s cooperation, behind the scenes they were complaining about lack of access and a refusal to share data. Within months of the beginning of the pandemic, the Chinese government imposed restrictions on academic research into the origins of the novel coronavirus … China’s intransigence wasn’t unusual — countries are rarely eager to confirm that they’re the source of a deadly disease — but it went beyond the norm. International investigators weren’t permitted to see the market until more than a year after the pandemic began and a WHO-affiliated team was allowed a highly choreographed and controlled visit. The resulting report that came out of the Wuhan visit, which dismissed the possibility of a lab origin, pointed the finger at some kind of zoonotic spillover while concluding that it was unlikely that the spread started at the market, which surprised many experts. It also found that it was “possible” that the virus had been introduced via contaminated frozen food products from abroad. While few experts took that possibility seriously, it fit a narrative the Chinese government had been pushing, against nearly all evidence, that the pandemic had in fact not originated in China. “China just doesn’t want to look bad,” Filippa Lentzos, a biosecurity expert at King’s College London, told Science last August. “They need to maintain an image of control and competence. And that is what goes through everything they do.” […] it seems clear that with more cooperation, scientists could have been looking at raccoon dogs a year or more ago. “The big issue right now is that this data exists and that it is not readily available to the international community,” Maria Van Kerkhove, the WHO’s Covid-19 technical lead, told reporters on Friday. “This is first and foremost absolutely critical, not to mention that it should have been made available years earlier, but that data needs to be made accessible to individuals who can access it, who can analyze it and who can discuss it with each other.” The irony is that by making it so difficult to properly investigate a zoonotic origin of Covid, the Chinese government has created a vacuum that has been filled by claims on all sides, including the much more damning accusation that the pandemic was the result of a lab error at the Wuhan Institute of Virology. For what it’s worth, my timeline of Chinese denials and coverups looks like this: December: COVID doesn't exist, it's all lies Early January: Fine, it exists, but it’s just some wet market thing that can't spread from person to person Late January: Fine, it can spread from person to person, but we’ve got it under control now. February: Fine, it’s out of control, but you would not believe how great our response was. We're basically heroes. March: COVID was a US bioweapon, or possibly came from Italy. April: Chinese people are banned from researching the origins of COVID without government permission. 2: Comments Arguing Against Lab Leak 2.1: Is the pandemic starting near WIV reverse correlation? randomstringofcharacters wrote: Isn't [the pandemic starting near the lab] a reverse correlation issue? The lab is situated there because it's an area where coronaviruses were found in the past. Many people had this question, but Wuhan Institute of Virology was founded in 1956, didn’t originally focus on coronaviruses, and isn’t in a coronavirus hot spot. Most of WIV’s coronavirus samples come from Yunnan, about a thousand miles away. COVID’s closest relatives were found in Laos, almost two thousand miles away. During the debate, both Saar and Peter calculated the odds of a natural pandemic arising in Wuhan by dividing the population of Wuhan by the total urban population of East Asia (Saar) or South China (Peter). Saar got 1.5%, Peter got 3% (he later said this could be as high as 10% because it was a central hub in the wildlife trade). This isn’t an Official Position and I don’t think anyone else shares it, but during the debate Peter pointed out a few times that there are plenty of disease-ridden bats in Hubei (the province Wuhan is in), and that it’s not impossible that a bat virus currently known only in Laos could be active in Hubei. Still, this is the minority viewpoint and most scientists just think it involved something about the wildlife trade. 3: Other Points That Came Up 3.1: Apology to Peter re: extreme odds quiet_NaN wrote: Hot take: Peter clearly failed to convince anyone. The lab leak odds, in log10 (i.e. orders of magnitude are): Peter -20.7 Saar 2.7 Eric -3.1 Will -2.5 Scott -1.2 Daniel -1.4 One of these numbers is clearly an outlier. Scott mentions it and calls it "trolling", I would argue that it is debating in bad faith. 2e-21 is a ratio which is just silly. For one thing, the gain of function at WiV pathway is not the only pathway towards a lab leak. The WIV could also have released a naturally occurring coronavirus at the wet market. At 2e-21 odds, we would probably have to consider the possibility that the WIV built a time machine and went back in time to infect the wet market. I might have screwed up here - or at least I should have emphasized the “trolling” part. Peter complained about my presentation of his extreme-odds slide, saying: This is basically accurate. During the debate, Saar gave lots of different numbers. I don’t want to say exactly what the different numbers meant, because in earlier drafts of my post, Saar said I misunderstood them. My impression were that some of his numbers were conservative, others were central, others were extreme, others were adjusted-for-out-of-model-error, others were not-adjusted, etc. In an early draft of the post, I gave higher numbers for Saar. Saar asked me to replace them with the numbers I ended up using. I decided to agree, because I wanted to represent Saar fairly with the numbers he most centrally believed, but also because these were closest to the numbers on his Rootclaim site so it wasn’t like he was making them up just to fool me. Peter didn’t argue quite as hard, and also he didn’t have anything like the Rootclaim site, so I just took his first set of numbers. Trying to piece things together, I think a reasonable summary would be: During the debate, Saar mentioned 700-million-to-one odds in favor of lab leak, not because he thought this was plausible, but just as a discussion of where the situation would end up if you didn’t adjust for human fallibility.
Inline links: Dai et al, Pang et al., 2020, Beijing Daily, 2020b, seafood distribution warehouses, on docks, a seafood processing work area, Infectious Diseases Emerging From Chinese Wet Markets, a paper on an emerging bird flu, Chinese Markets May Be Breeding Ground For Deadly Viruses, Wet Markets, A Continuing Source Of SARS And Influenza, this study from SARS1, this thread, https://substackcdn.com/image/fetch/$s_!dcI7!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fc5aabd26-d70b-4f35-97cb-96d351bb52fd_552x920.png, https://substackcdn.com/image/fetch/$s_!UQ14!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F2411167c-1405-4fde-914b-6388ee498523_935x851.jpeg, a Vox article, wrote, wrote, https://twitter.com/tgof137/status/1773797640607850745
…and deciding whether you think the assumptions behind a specific statistical test are likely to debunk the idea that cases are centered around the wet market. 11. Wuhan used as a control for a 2015 serological study on SARS-related bat coronaviruses due to its urban location. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6178078/ I don’t know why this point is supposed to matter. If you mean that Wuhan isn’t directly exposed to bats, nobody ever said it was. The zoonotic theory is that wildlife carted in from other areas of China started the pandemic in the wet market. 12. Superspreader events also seen at wet markets in Beijing and Singapore (Xinfadi and Jurong). This was discussed very extensively in the debates, both in section 1 and section 3. Wet markets weren’t “superspreader locations” - in fact, the disease spread no more quickly there than anywhere else. They were the first place in those cities that the pandemic started, due to contaminated animal products. If anything, this supports zoonosis. See also my discussion with Saar on this point below. 13. WIV refuse to share their records with NIH who terminated subaward in 2022. Wider suspension over biosafety concerns. https://www.bloomberg.com/news/articles/2023-07-18/us-suspends-wuhan-institute-funds-over-covid-stonewalling Although WIV has not been especially forthcoming, some of their databases were leaked in various ways and showed that they did not have any viruses capable of transforming into COVID. 14. PLA involvement at WIV and MERS research prior to SARS-COV-2. MERS features several similarities with SARS-CoV-2. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7022351/ I can’t even tell what conspiracy theory you’re trying to propose with this one; if you spell it out I can try to explain why it might be false. 15. SARS1 leaked several times and SARS-COV-2 has leaked from a BSL-3 lab in Taiwan. Agreed that SARS leaked several times. It also spilled over from animals several times. During the debate, a lab leak rate of once per lab per 500 years was proposed (everyone agreed to steelman this by 10x for WIV numbers); I would be interested to know whether anything about the study of SARS challenges that number. 16. Unpublished infectious clone identified from Wuhan contradicting arguments such reverse genetics systems would be published. https://www.biorxiv.org/content/10.1101/2023.02.12.528210v1.full I asked some scientists about this paper and here’s what they told me. Wuhan University sequenced some rice. In the middle of the sequence, there’s an unexpected sequence from a common coronavirus, HKU4. The most likely explanation is that someone else in Wuhan was working on the coronavirus and there was cross-contamination. Plausibly this is Wuhan Institute of Virology, who is known to work with coronaviruses. This is cool detective work, but it’s not clear what it’s supposed to prove. I think some lab leakers are using it to prove that WIV can do reverse genetics, but they admitted this already in a published paper so that’s not too helpful. I think others are using it to prove WIV had “secret viruses” in their catalogue, but the rice virus wasn’t secret, it was HKU4, which is common and which WIV has already published papers about. 1.6: DrJayChou’s 7 Arguments Once again, I cannot stress enough how much better a take you might have on this debate if you watch it. “The first known case predates the market outbreak by a month” - this is not the consensus position. I cannot say for sure what Dr. Chou means by this, but I suspect he’s referring to one of the many claims to this effect that Peter effectively debunked during the debate (Connor Reed, Mr. Chen, the 92 cases, Brazil, etc).
Inline links: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6178078/, https://www.bloomberg.com/news/articles/2023-07-18/us-suspends-wuhan-institute-funds-over-covid-stonewalling, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7022351/, https://www.biorxiv.org/content/10.1101/2023.02.12.528210v1.full, a published paper, has already published papers about, https://substackcdn.com/image/fetch/$s_!yA9U!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F467dd304-190a-4437-8920-d498c433dffb_1600x960.jpeg