I think it's easy to assume more of this is riding on "access and cooperation" between China and the WHO / other countries than history would suggest is actually true (thread)
Take SARS-CoV as a counterfactual, where tracing back to wildlife trade was efficient and transparent. Civets are linked to SARS-CoV before the outbreak ends, and horseshoe bats are implicated as the reservoirs of SARS-like viruses by 2005. Access and cooperation at work! But...
The actual reservoir species isn't fully tracked down and published until 2017. That has less to do with early outbreak transparency, and more to do with the arduous nature of tracing viral origins in the wild:

nature.com/articles/d4158…
This kind of work is a huge pain, ESPECIALLY because coronaviruses seem to like using "bridge hosts" - a stepping stone between bats and humans, like civets for SARS-CoV or camels for MERS-CoV. That decouples "early outbreak" from "where it came from"

nature.com/articles/s4157…
Or, to put it another way: let's say it *was* pangolins in the wildlife trade - knowing that doesn't actually, necessarily, help us find SARS-CoV-2's ancestor in bats. It took 2002 to 2017 for SARS-Cov, and could take just as long this time - regardless of this investigation.
That's why our team at @viralemergence uses machine learning to help narrow the search, with a candidate list of species that should be sampled for SARS-CoV-2's closest relatives, plus 200 other bats that might host betacoronaviruses like SARS and MERS:

biorxiv.org/content/10.110…
But the bottom line is, if it takes a long time to figure out where SARS-CoV-2 came from, don't chalk it up to "China's fault" - it's just as much, if not more, about luck, optimization of basic science, and scientists' ability to resume normal fieldwork & research

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More from @wormmaps

28 May
A quick thread about the evidence base for this claim about Ebola, which is perhaps troubling (1/4)
The 2014 outbreak in West Africa, the largest to date, was traced back to human-bat contact without any link to wildlife trade. Many scientists find the evidence for this incomplete, but it's probably impossible to know now. (2/4)

sciencemag.org/news/2014/12/b…
Some (not all) outbreaks since 1976 were linked to human consumption of wildlife, especially wild primates or bats as a primary food source. This is not the big, international wildlife trade with a criminal underworld side that conservationists mean (3/4)

journals.plos.org/plospathogens/…
Read 4 tweets
6 May
New COVID-19 comment: Species distribution models are a great tool, but wrong for a respiratory virus. Here's an explainer of where ecologists went wrong, and why we have to stop right now, before people get killed.

New in Nature Ecology and Evolution:
nature.com/articles/s4155…
Thanks to @joechip90 @BlasBenito @richardjtelford @BobOHara and Nature Ecology & Evolution for working around the clock to get this out there (and to the journal for making it open access).
Bottom line:

Using SDMs for a system like COVID-19 is malpractice, deeply indicative of a lack of understanding about microbiology.

Pushing studies out anyway against the advice of public health experts, at great risk to the public, is careerist misconduct.

End of discussion.
Read 4 tweets
19 Apr
Let's say that after COVID-19, you wanted to discover every single animal virus that can make a person sick, from Aichi to Zika.

How many are there?
How long would it take?
A little thread for a quiet night.
When you walk into a party, you meet the most strangers early in the night; the longer you’re there, the fewer new people you’re likely to meet, and the more repeats you hit.

Ecologists usually measure diversity the same way, using what they call “rarefaction curves.”
Every year, about 2-4 new animal viruses that can infect humans – zoonotic viruses – are discovered. Even though we’re being hit by more virus outbreaks every year, we started hit a plateau in zoonotic virus discovery over the 20th century.
Read 21 tweets
2 Apr
Can I talk to the public as a modeler for a second?

I've been training for something like this for 10 years. I've been doing outreach, posting, publishing and now I'm asking you:

Don't listen to modelers right now. Don't try to understand the full range of good and bad science.
Normally, there's a bell curve of good and bad science - some really brilliant work, some really confused work - but it all sort of approximates the truth like a shotgun blast.

Right now, every single person with my training is doing this work. I can't even keep up with it.
What that means is that every now and then, there's going to be a paper that says something like "Africa won't be hit by COVID because it's too hot" or "10 million Americans were infected weeks ago and the disease isn't severe."

I promise it is, really, as bad as it seems.
Read 5 tweets
31 Mar
Today, the U.S. extended a program, defunded last year, to stop pandemics by studying wildlife viruses.

For today's very first issue of Lancet Microbe, I've written about USAID PREDICT, why it was important, and why it wasn't enough to stop COVID-19:

thelancet.com/journals/lanmi…
I want to add a few points of nuance that I wish had made it into this, starting with the fact that today, the program was extended for 6 months / $2.26 million budget, focused on
1. COVID-19 diagnostics, and
2. Tracing wildlife origins of SARS-CoV-2

ucdavis.edu/coronavirus/ne…
Even before this announcement, PREDICT-funded labs around the world (esp. Africa and Asia) have already been pivoted to COVID diagnostics.

I'm optimistic that the capacity building aim of PREDICT will pay off in this crisis.
Read 15 tweets

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