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by tynpeddler 1374 days ago
What is often missed is that chimeric viruses are easy to detect. The viral genome will show clear evidence of manipulation from random base insertions and clear homology with all the ancestral viruses. Hiding the signs of manipulation would either require vast amounts of time and resources (the expense and man power would make it very difficult to hide) or straight up science fiction technology. The chimeric origin hypothesis is not a plausible explanation for the origin of sars-cov2, which means the nature link is not relevant.

The other lab leak hypothesis is that a specimen collected and cultured by scientists, infected a lab employee and this patient zero then transmitted the virus to others. This is a plausible option, and it is being researched. However it is less plausible than wild transmission based on a simple numbers game. What is more likely, a breakout infection cause by a dozen scientists specifically trained and equipped against this possibility, or a transmission to one of the millions of other people who routinely interact with these bat populations? Both are possible, but one is much more likely. Before covid19, WIV had published research indicating that novel coronaviruses routinely jump from bats to humans in that part of the world. Most of these viruses aren't don't last in human hosts, but it's clear that it was only a matter time before something nasty got through. After all, it's already happened once before.

The real nail in the coffin is that research[0] has shown that there were at least two, independent transmissions of sars-cov2 to humans. For this to happen as part of a lab leak it would require WIV to have found and cultivated 2 different strains of sars-cov2, and then each of those strains would have to escape the lab.

[0] https://www.science.org/doi/10.1126/science.abp8715

1 comments

That's a much better counter argument to the lab-origin. The

>The chimeric origin hypothesis is not a plausible explanation for the origin of sars-cov2, which means the nature link is not relevant.

seems to be incorrect. By a simple search: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7744920/

Now the two distinct genomic lineages seem to indeed present a challenge to lab-leak hypothesis. It's explained in the original study[0] that the second lineage B came from A by intra-host evolution. Due to the molecular clock of the virus the single-introduction origin of the pandemic from a lineage A can be ruled out.

[0]: https://www.science.org/doi/10.1126/science.abp8337

Have you looked at Pekar's full model, as described mostly in the supplementary materials? A typical molecular clock approach wouldn't give anywhere near the accuracy necessary to exclude evolution of lineage B (just two SNPs away) in humans. Pekar instead builds layer upon layer of complexity, with dozens of reasonable but somewhat arbitrary judgment calls, in the same general direction as econometrics. From the shape of the resulting modeled phylogenetic tree, he purports to exclude a single introduction into humans.

I'm not aware of any case where any similar model has been shown to have predictive power, and there's inherently no way to validate this one against any physical data. So I believe this result has been grossly oversold, per my comments and links at

https://news.ycombinator.com/item?id=32740568

> A typical molecular clock approach wouldn't give anywhere near the accuracy necessary to exclude evolution of lineage B (just two SNPs away) in humans

You're ignoring other data which is counter to the idea of B evolving from A in humans. Pekar's models are not the only evidence.

- Early cases were predominantly B - A shows less generic divergence than B, this is what Pekar is talking about with regards to the discontinuity in the early clock.

When we first started discussing this - I spoke up because I was annoyed by you trashing peer-reviewed papers when it was obvious you weren't even attempting to grok the phylogenetics involved. Still annoyed.

It's been genuinely interesting watching the scientific debate to root the SC2 tree over the past few years because of the involved paradoxes.

"Just a few SNPs" is just such a silly argument when stacked against peer-reviewed phylogenies in high-impact publications.

Have you looked at Pekar's full numerical stack yourself, as described in their supplemental materials? If yes, then why are you confident that their choice of the Barabasi-Albert algorithm to generate a fixed infection network correctly models the earliest spread of SARS-CoV-2 in humans? In particular, why choose to study robustness against doubling time (which seems intuitively like it wouldn't affect the shape of the tree much), but not robustness against that connectivity (which seems intuitively like it would)?

The rest of their arguments depend fundamentally on the polytomy thing, because nothing else excludes an earlier (even September) first introduction into humans. With an earlier introduction and thus more extensive unsampled spread, it's much harder to insist that A and B would be first sampled in the same order in which they evolved in humans, or make any similar early claims with confidence.

You are correct that I hadn't fully understood their polytomy argument before you brought it up, and I appreciate you bringing it to my attention. I still don't think it's very good, though. I later found Erik van Nimwegen's criticisms, which roughly followed my own; so I don't think I'm taking a fringe position here. Indeed, I've never seen anyone citing or defending Pekar engage in any way with the numerical complexity of that model. It seems like anyone who's looked inside the box becomes a critic, thus my hope that you'll do so.

High-impact publications have shown unfortunate willingness to publish low-quality work that would exclude research-related origin of SARS-CoV-2. For example, I assume you followed Nature's publication, editor's note, and ultimate extensive correction of their pangolin paper, and that you agree pangolins aren't the proximal host. This makes me less inclined to trust in their reviewers here, and more inclined to trust my own judgment (or that of the two Twitter threads I've linked elsewhere).

> In particular, why choose to study robustness against doubling time (which seems intuitively like it wouldn't affect the shape of the tree much)

As I understand it, the doubling times observed in the simulations were primarily the result of the ascertainment and transmission rate parameters.

Care to elaborate why you think the robustness of the model with respect to transmission rate should be assumed? I don't share your intuition here, and note that the authors observe, "that sensitivity analyses with longer doubling times increase the support for multiple introductions."

You really fault them for robustness analysis here?

To be clear I don't fault them for studying robustness against doubling time; I fault them for not studying robustness against connectivity of the infection network, since that seems like it would be more important than any of the parameters that they did study. My intuition is that when spread is highly deterministic (e.g. if R0 = 2 and each patient infects exactly two others), it's easy to make inferences about past spread from the present. For example, in that case it really would be near-impossible for a later lineage to outcompete an earlier one.

But we know the spread of SARS-CoV-2 is actually stochastic, with most lineages dying out but a few exploding due to super-spreader events. In that case it's much harder to judge whether a clade is big because it had more generations to grow, or just big because of a few (un)lucky founder effects. In Pekar's epi simulation, that stochasticity is modeled by their connectivity network. I expect that a more overdispersed network (i.e. greater variance in the number of edges at each vertex, keeping the same average) would make non-modal outcomes--like the real pandemic's phylogeny, if it arose from a single introduction--more likely.

Yes, I've reviewed the supplemental materials.

> because nothing else excludes an earlier (even September) first introduction into humans. With an earlier introduction and thus more extensive unsampled spread, it's much harder to insist that A and B would be first sampled in the same order in which they evolved in humans

The tMRCA clearly excludes an earlier introduction. Because the tMRCA is based on genetic diversity, you cannot calculate a tMRCA based on all the known samples, get a date, and then say "oh, geez- well, there was also wide cryptic spread before that." It just doesn't make sense. Pekar addresses this point directly.

A race between the first A and the first B is a strawman. Rather, it's the predominance of lineage B over A in the early pandemic which is interesting. It would be unexpected for lineage B to dominate if A came first. Much of the modeling is to get a handle on how unlikely that situation would be. It shouldn't be surprising that the models don't support it as being likely. (But, that's not the only evidence.)

If you're willing to actually think about and engage on the phylogeny - stop with the "just a few SNPs" nonsense, and ask yourself what you really think the early origins looked like. If it really was a single introduction - Was lineage A ancestral? Was B ancestral? A C/C ancestor? A T/T ancestor? All these have interesting problems being supported by the data.

Finally, after reading some of your earlier comments, I'm realizing that you're conflating several techniques from Pekar's paper, eg:

> Have you looked at Pekar's full model, as set out mostly in the supplementary materials? This isn't any standard molecular clock approach. It's a byzantine stack of plausible but somewhat arbitrary assumptions, ending in a simulated phylogenetic tree.

His epi simulations are separate from the tree-building, with the possible exception of rooting, which he was using the output of the models to inform. Otherwise, the epi modeling which everyone is hand wringing over is really separate and doesn't end "in a simulated phylogenetic tree."

There /are/ novel methods used in the tree building (eg, non-reversibility of base substitutions), but that's a whole separate technique.

> Essentially Pekar's argument is a "two introductions of the gaps"--that if their model of a single introduction doesn't conform to reality, then it must have been two introductions.

BS. Again - understanding the paradoxes and debate involved in rooting the tree is basically required to understand the importance of this paper. The existing data is confounding and didn't conform to a logical understanding of viral evolution. A separate introduction elegantly explains the existing evidence.

If their modeling isn't strong enough evidence for you, fine. But that's different than throwing everything out because you don't understand how "just a couple SNPs" can still provide sufficient resolution to make phylogenetic inferences possible. If you think that "just a couple SNPs" /don't/ provide enough for experts in the field to inform their phylogenies, at least get to that argument directly instead of throwing ignorant shade at an unrelated portion of the paper.

Thanks for the links to those other threads. Nod's was interesting, but AFAICT, way off-base, starting around "Needless to say, early winter in Wuhan is not the Mardi Gras."

Here's Pekar's earlier thread which I recently reread and found helpful for understanding the significance of the phylogeny (#20 is where he gets into how lineage A breaks the clock):

https://twitter.com/jepekar/status/1499840335349911553

and Worobey re-emphasizing that we're not just talking about a few SNPs, it's the shape of the tree which matters:

https://twitter.com/michaelworobey/status/157050467474223923...

I think you're talking about their model in "Inferring the MRCA of SARS-CoV-2", and I'm talking about their model in "Separate introductions of lineages A and B"? So you're saying they don't use the epi simulations to root and build the phylogenetic tree of real sampled genomes, which is true. I'm saying they do use the epi simulations to build a phylogenetic tree for each simulated pandemic, whose shape (polytomy structure) they then compare against the real tree:

> We simulated SARS-CoV-2–like epidemics (22, 23) with a doubling time of 3.47 days [95% highest density interval (HDI) across simulations, 1.35 to 5.44] (24–26) to account for the rapid spread of SARS-CoV-2 before it was identified as the etiological agent of COVID-19 (figs. S21 and S22, tables S3 and S4, and supplementary text). We then simulated coalescent processes and viral genome evolution across these epidemics to determine how frequently we recapitulated the observed SARS-CoV-2 phylogeny.

Coverage of this paper in the popular press usually said something like "study finds that SARS-CoV-2 arose from two introductions into humans", so I thought the latter was the more important result and started there. Like in your second link, Worobey says:

> [...] We then go on the explain, point by point, that it is not a two-mutation difference that is unexpected. It is a two mutation difference between two large clades like lineage A and lineage B, each displaying a MASSIVE polytomy at their root. This is something that [sic] DO NOT see in ~99.5% of simulations. That is the crux of the paper. Not the idea that two mutations can't happen in a single transmission event.

Are those "simulations" not the SIR-type epi simulations (followed by simulation of the mutations and sampling, then construction of the tree)? I believe his 99.5% is 100% minus the 0.5% from Figure 2C.

Their former model is of course independent of their SIR stuff, and indeed purports to independently establish tMRCA in humans too recent for significant cryptic spread. It carries a different set of plausible but arbitrary assumptions though, again about the stochasticity/overdispersion and sampling rate of early spread, just less directly.