This week I wrapped up COVID-19 related policy work. Just to quickly pin it, here's a reference thread of my writing about various pandemic topics.
Epidemic forecasts are important, but often fail to translate to on-the-ground decision making. We list a handful of high-priority questions, from basic epidemiology to healthcare data science, that policymakers have been asking us to help them answer.

thelancet.com/journals/langl…
The wildlife trade is implicated in a tiny fraction of emerging disease outbreaks worldwide (and has no concrete link to SARS-CoV-2). Centering wildlife trade regulation as "pandemic preparedness" undermines the work of global health experts.

thelancet.com/journals/lanpl…
The PREDICT program invested $200m in cataloging viral diversity in wildlife. Those data have helped us understand where SARS-CoV-2 came from, but to make the most of them, we need a shift to open global data sharing that supports applied risk assessment.

thelancet.com/journals/lance…
Ecological tools that identify spurious correlations between weather and COVID-19 transmission will help policymakers act in bad faith to advance ideas like "Transmission will end in the summer" or "Africa is protected from the pandemic," costing lives.

nature.com/articles/s4155…
COVID-19 is already crashing into climate change; from bushfires to hurricanes, natural disasters will spread emergency response thin, prevent social distancing, and expose the need for a longer-term pandemic preparedness strategy for climate adaptation.

nature.com/articles/s4155…
And finally, the @viralemergence collaborative study on betacoronaviruses, in which we find two-thirds of horsheshoe bat reservoirs of SARS-like viruses might still not be known, and generate a list of sampling priorities for bat virology and immunology.

biorxiv.org/content/10.110…
Our Washington Post piece added to this thread:

A couple new things for this thread. First, another comment on COVID SDMs, this time getting more into the weeds of how bad these models are doing, and why that's alarming:

sciencedirect.com/science/articl…
Our big piece on COVID-19, seasonality, and climate: why did "experts" get it wrong about summer, or about the tropics being safe? (They didn't: people jumped in with guesswork but the wrong epidemiological knowledge.)

nature.com/articles/s4146…

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More from @wormmaps

17 Nov
So post-workshop, the World Meteorological Organization's Task Team on COVID-19 and Climatic, Meteorological, and Environmental Factors has published some guidance on how to do the science. It's nice, but missing the words "talk to an epidemiologist"

nature.com/articles/s4146…
It's tough. I appreciate what they've done here, and they very clearly nod to our piece on how climate-but-not-epidemiology experts got things wrong. But I also still think, 10 months in, the magic words are "talk to an epidemiologist about your understanding of the system."
This is particularly salient given that they actively encourage scientists to do public facing communication that "...includes informing media outlets or policy makers of dissenting views and encouraging the presence of multiple voices in coverage of their work."
Read 5 tweets
8 Nov
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…
Read 7 tweets
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

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