@R_H_Ebright I leave room for the possibility that these scientists and journalists are just repeating the same honest/human mistakes rather than a conspiracy to deceive the public.
@R_H_Ebright I honestly think they just didn't know. It looks like their paper was based on a major error on their part, not an intention to deceive.
@R_H_Ebright Sometimes when there are too many authors on a paper, the other authors assume someone else in the team has done due diligence to properly check key facts on which their group analysis is based on.
And it's terrible when this turns out to not be true.
@R_H_Ebright I think it would be appropriate for this group to rename their preprint:
Huanan market is epicenter of early Covid-19 cases in Wuhan due to ascertainment bias.
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#OriginOfCovid reporting in early 2022 is a repeat of what happened in early 2020.
Some scientists, including some from 2020 #ProximalOrigin, put out a paper claiming certainty of a natural origin.
Reporters, incl some from 2020, rush out headlines amplifying this claim. /20
I get that people’s bandwidths are stretched right now with the pandemic and the war in Ukraine.
But weren’t any lessons learnt from 2020 about responsible COVID-19 reporting?
Fool me once, shame on you. Fool me twice…
After reading the preprints, I quickly identified major scientific issues or misunderstandings undermining the main claims of the highly reported Worobey et al. preprint.
I will address the 11 key claims of this preprint listed in their discussion.
Dec 2019 to mid-Jan 2020: Chinese CDC, Hubei CDC, Wuhan CDC specifically looked for potential Covid-19 cases with links to Huanan Market or living in the vicinity of the market.
Feb 2022: Western scientists say, "Wow so many of the early cases were centered around the market!"
China-WHO report annexes (p125) described the early search for cases:
"screening.. targeting people with pneumonia.. and exposure history with Huanan market.. surveillance at several hospitals (close to Huanan market), Huanan market and the neighbourhood" who.int/publications/i…
Jan 2020, the 2019-nCoV Outbreak Joint Field Epidemiology Investigation Team reported that, in late Dec 2019, Wuhan CDC did "a retrospective search for pneumonia patients potentially linked to the market.. found additional patients linked to the market" ncbi.nlm.nih.gov/labs/pmc/artic…
My main takeaway from this report by @theintercept@MaraHvistendahl is there is a Year 6 report potentially describing more work done at the Wuhan Institute of Virology - that the NIH received from EcoHealth in June 2021 but has not shared with reporters. theintercept.com/2022/03/03/wuh…
@theintercept@MaraHvistendahl Article quotes @FilippaLentzos co-director of King’s College London’s Centre for Science and Security Studies: “By only communicating through litigation requests, it comes across as though [NIH]’re covering something up.”
Note that Peter Daszak, president of the EcoHealth Alliance told @theintercept “Even though we didn’t have access to the [NIH] funding, we still had to file reports on it. So we then filed the Year 6 and 7 reports.”
Even without receiving funding, the work went on for 2+ years.
Video is up for a recent (Feb 28, 2022) National Science Advisory Board for Biosecurity (NSABB) public review of US government policies on dual use research of concern (DURC) and research with enhanced potential pandemic pathogens (ePPP/P3CO). videocast.nih.gov/watch=44823
Having listened to this, I'm worried that some of the experts on the call are more concerned that the US might lose its competitive edge internationally than that some of this research might kill millions whether by accidental or deliberate release.
There's good acknowledgement of the difficulty of balancing security vs research advances, challenges of knowing what is happening in labs even in the US, & the value of engaging non-scientist stakeholders (I think this is very important; non-scientist views should have weight).
To facilitate discussion, here it is, the text in their preprint that says they can't verify the data, don't have key data, but believe their analysis is robust.