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Alina Chan Profile picture
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6 Jan, 5 tweets, 3 min read
The balance of evidence for a natural vs lab #OriginOfCovid is different from that of Omicron.

In the case of Omicron, many known plausible natural sources of the novel variant.

In the case of the original SARS-CoV-2, only postulated natural sources, no direct evidence found.
The case for a wet market #OriginOfCovid remains dimly lit. Lack of access to data describing what potential intermediate hosts were even sold at Huanan market in late 2019. Lack of access to early case data and exposures to potential sources of the virus.
Sorry to disappoint some natural origin diehards, but not all people who think a lab #OriginOfCovid is plausible are going to think Omicron likely came from a lab.

You have to evaluate the evidence and circumstances specific to each emergence.
As I told @statedclearly I'm actually very skeptical when someone tells me they've found evidence of a lab #OriginOfCovid and I've gotten into nastier disagreements with folks on the lab origin side than with folks on the natural origin side.
@StatedClearly It's just that the disagreements with the natural origin folks are much more public and reported by journalists because these tend to involve highly cited publications, as well as widely touted misinformation regarding links between Covid-19 & the sale of wildlife in Wuhan.

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Alina Chan Profile picture
4 Jan
I'm aware of the @newrepublic review of our book VIRAL: The Search for the Origin of Covid-19. I don't have much to say about it because it isn't a review of VIRAL. It was an opinion on #OriginOfCovid dressed up as a book review.

See article by @thackerpd
disinformationchronicle.substack.com/p/get-the-hell…
In order to formulate a response in defense of the book, there must be facts-based criticisms of the book's content, which do not exist in the @newrepublic review.

So how should I respond to a negative review that goes after the same old strawmen not represented in the book?
@newrepublic One scientific scenario I can compare this to is when you get a peer reviewer who clearly has a vendetta against a particular hypothesis. Instead of critiquing the data in the paper, goes after old arguments by other scientists, recommending rejection of the manuscript at hand.
Read 4 tweets
Alina Chan Profile picture
30 Dec 21
Would also be useful to color the states to indicate average age of population and BMI @nytimes

Also, deaths are counted since Apr 2021 but vaccination rate is as of Dec 2021, so would be useful to shift timeframe a few months later since some states were slower to vaccinate.
@nytimes To be clear, the Covid-19 vaccines approved in the US have protective effect against severe outcomes (although still awaiting Omicron data).

As a low risk category person, I was only fully vaccinated by June 2021 (2 shots Moderna + 2 weeks after 2nd shot).
Overlaying average age and BMI (e.g., age = size of dot; BMI = color of dot), and shifting the date range later to when most people got their vaccines, would help to show the effects of the vaccines vs other factors that contribute to Covid-19 deaths.
Read 4 tweets
Alina Chan Profile picture
30 Dec 21
One common #OriginOfCovid misunderstanding is that early Covid-19 cases were linked to market stalls selling wildlife.

There's actually no data to support the claim, and the data provided by the China-@WHO joint study, whether you trust it or not, contradicts the claim.
@WHO Although some cite the China-WHO joint study report in support of the claim above, the report actually contradicts their interpretation:

Page 45: "no clear clustering with one specific part of the market was apparent as cases were widely distributed"
who.int/publications/i…
It's also important to note that even though "most cases were associated with the western side of the market", we're talking about a market the size of more than 9 NFL football fields combined.

You're saying most cases were in 4.5 football fields.
Read 18 tweets
Alina Chan Profile picture
29 Dec 21
What we know from recent papers + data deposited into NCBI by the Wuhan Institute of Virology / EcoHealth Alliance just before the pandemic is that by 2016 they were actively sampling bat viruses in Yunnan and North Laos, where the closest relatives to SARS-CoV-2 have been found.
There are 2 things we don't know.

1. What other viruses and locations were sampled between 2016-start of pandemic. Their collaborators across 7 SE Asia countries, including Laos, wouldn't tell @theintercept @fastlerner

theintercept.com/2021/12/28/cov…
Although much of this work was funded by US sources such as USAID (PREDICT) and NIH/NIAID.

EcoHealth even told NIH in 2016 that they were going to transfer pathogen samples from the wildlife trade directly from 7 SE Asia countries to Wuhan.
Read 20 tweets
Alina Chan Profile picture
28 Dec 21
I'd like to see this problem of inequitable credit and technology sharing solved.

If updated vaccines/therapeutics/diagnostics are developed, these should be sent first to places that reported the new variant(s) used in the update.

There should be a new credit sharing system.
In a pandemic when novel SARS-CoV-2 sequences can rapidly translate into updated vaccines, diagnostics & therapeutics, why don't prominent journals guarantee a "Resource" paper for the researchers who are the first to share the sequence of a new variant of interest/concern?
This way, data sharing is highly incentivized and accelerated.

Both the sequence contributors and the journal are rewarded due to hundreds or thousands of citations of the Resource paper.
Read 4 tweets
Alina Chan Profile picture
28 Dec 21
Another key piece on risks of lab-based outbreaks by @fastlerner @theintercept

"it is not at all clear that tracking down virus-infected wildlife in remote locations, to which the U.S. devotes.. substantial [$].. helped us prepare for our current crisis"
theintercept.com/2021/12/28/cov…
"Virtually every part of the work of outbreak prediction can result in an accidental infection. Even with the best of intentions, scientists can serve as vectors for the viruses they hunt — and as a result their work may put everyone else’s lives on the line along with their own"
Dennis Carroll, who designed and led Predict:
“It’s fool’s gold to think that you’re going to predict which is the next virus. But you can begin forecasting where that emergence is most likely to occur... I probably never should have named Predict ‘Predict’”
Read 12 tweets

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