How can scientists address questions that have been painted as conspiracy theories? And without amplifying or legitimizing misinformation related to these questions.
As a scientist who has been washed out to sea on a contentious covid topic, I find it safest to talk to science journalists for news articles - professionals with some extent of scientific training, who know what to ask scientists, how to probe their reasoning and evidence.
Looking at the infographic, I think covid origins is a challenging topic for non-scientifically trained journalists.
Your trusted sources and the scientific consensus may not be very good at conveying the gaps in knowledge/logic because this is still an evolving area of inquiry.
When you're not sure about how all the evidence will stack up in the future, I believe that many tend to play it safe and stick to what other top scientists have said publicly already. Scientists are people too.
• • •
Missing some Tweet in this thread? You can try to
force a refresh
Based on the emails unearthed by @USRightToKnow EcoHealth was already circulating this letter by Feb 6. The virus had only been announced on Jan 20 to transmit from human to human; its genome released on Jan 12 was barely characterized at least publicly. thelancet.com/journals/lance…
If you've been going around rallying other scientists to condemn lab origins as a conspiracy theory since the beginning of the pandemic, how can you possibly “systematically examine every theory” “not be bound by preconceived ideas” “with an open mind” telegraph.co.uk/global-health/…
On the covid data sharing debate, I believe that the context of a raging pandemic killing millions of people should be considered 1st. If a scientist finds that there is rapid virus adaptation in minks, must they seek permission or wait for the data providers to publish first?
I know that some scientists on both sides of this issue think that the same data sharing protocol applies to pandemic data as it does to non-pandemic data. But I don't think so.
Pandemic data should be shared in real time, analyzed in real time, publish/preprinted in real time.
In non-pandemic times, it makes sense to let the data provider take precedence; no urgency.
But in pandemic times, if you can do the analysis differently, faster, or better, shouldn't it be released ASAP? Especially if data is already shared only months after sample collection?
Pandemic rages. Meanwhile scientists are fighting about what open data sharing means and whether you can publish analysis using someone's data if part of their dataset has not yet been published.
Scientists often keep data private so that they can publish in high impact journals and avoid others beating them in the publication race.
If you share data pre-publication, others are likely to swoop in and you lose your advantage.
In the pandemic, we've seen scientists really step up their data sharing generosity. It's the only way global databases @GISAID, public resources @nextstrain@covidcg can provide big picture, powerful analyses of SARS2. So many analyses have been run on unpublished sequences.
“if a similar phenomenon of host adaptation had occurred upon its jump into humans, those human-specific mutations would likely have reached fixation.. before the first SARS-CoV-2 genomes were generated.” 🙏🏻 @LucyvanDorp @BallouxFrancois biorxiv.org/content/10.110…
"The secondary host jump from humans into minks offers a glimpse into the window of early viral host adaptation of SARS-CoV-2 to a new host that has likely been missed at the start of the COVID-19 pandemic... and point to rapid adaptation of SARS-CoV-2 to a new host." 💯🔥
"pandemic is understood to have been caused by a unique host jump into humans from a single yet-undescribed zoonotic source in the latter half of 2019"
How does this fit with: "human-specific mutations would likely have reached fixation.. before the first SARS-CoV-2 genomes" 🤔
It looks like the universe will not let me have a day off.
@Nature just released an Addendum on the WIV's first paper about COVID, explaining what's up with RaTG13, the bat coronavirus most closely related to SARS-CoV-2. nature.com/articles/s4158…
tldr from the Mojiang mine, 293 CoVs found, 9 were SARS CoVs, 1 was RaTG13 first published in 2016 (not cited in their original 2020 @Nature paper). The other 8 SARS CoVs? We have no insight to their sequences!
Why are we hearing about this in mid-Nov 2020 when their paper was released in January, saying that they first found a match in the RdRp between RaTG13 and SARS-CoV-2 and then full genome sequenced RaTG13 to find a 96.2% genome identity match?