One last thread on the origins of #SARSCoV2 before the upcoming publication of the US intelligence report. First of all, there are two things that might be even more important than the origin itself: research ethics and scientific debate. 1/
Since the beginning, some scientists working in Chinese institutions haven't been fully transparent. The history of #RaTG13 and the issues with its sequencing data, the miners pneumonia, the missing database, the pangolin CoV data. Hiding info, playing with words. Bad science. 2/
The second thing that I didn't like was the suppression of an open dialogue between scientists, which lasted for several months. Now it's easier for scientists to freely talk about the different scenarios, but do you remember how difficult it was one year ago? 3/
Most scientists remained silent, or just cited the Proximal Origin paper without any critical evaluation of its content. Too busy with their work? Maybe. But I have a feeling that a lot of them were afraid to join a discussion that had become 100% political, because of #Trump. 4/
Back then, those who dared to talk about experiments or lab leaks were mocked and accused of promoting #conspiracy theories. It goes without saying that in that environment, skeptical scientists preferred to stay quiet. 5/
Even worse, we later discovered that the same scientists who were so sure about the natural origin of the virus had expressed before the very same doubts of the so-called "conspiracy theorists". Taking this into account, their patronizing attitude was even more irritating. 6/
The lack of #transparency from China and the lack of a proper debate among scientists are the two things that led me to tweet and write articles on this topic. Those practices were harming #science reputation, and I couldn't stay silent: I love science! 7/
Now everything is different, thanks to the presidency change and the famous Science letter. Scientists seem to be more open to other interpretations, they discuss (sometimes fiercely) and highlight the weaknesses in each other's arguments. Science at work, finally. 8/
I am sorry for the general public, who might feel a bit confused by the narrative shift and the revival of the lab leak hypothesis. But this is what happens when scientists make bold claims without enough evidence, and pretend there is a #consensus when there is none. 9/
A natural #spillover and a #LabLeak have always been plausible hypotheses. Both have circumstantial evidence on their side, both suffer inconsistencies or lack of data. Where did SARS2 come from? Nobody knows, but science is now in a better position to find it out. 10/
This thread will disappoint many of my lab leak followers and irritate someone in the other camp. But I don't care, this is what I think and always thought.
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THREAD - What happened at the Huanan #seafood market?
The @WHO report is quite clear on this point: #SARSCoV2 might have jumped from a wild animal sold in this market and maybe other markets in #Wuhan. But what do we know exactly? 1/15
After all this time, the Huanan seafood market still remains the main suspect for a simple reason: most of the early cases had visited at least one market in Wuhan city, and several of them visited the Huanan market. 2/15
According to the report, 10,000 people visited this place every day, making it a perfect setting for an #outbreak. One might argue: what about the cases without market exposure? Good question! 3/15
La prima permette a SARS-COV-2 di legarsi meglio al recettore ACE2, in altre parole i virus con questa mutazione riescono a entrare più facilmente nelle nostre cellule. 1/
Variante inglese 🇬🇧 (B.1.1.7), sudafricana 🇿🇦 (B.1.351) e brasiliana 🇧🇷 (P.1) hanno tutte quante la mutazione N501Y.
Probabilmente, è proprio per questo motivo che queste varianti tendono a essere più contagiose. 2/
La E484K, invece, aiuta il virus a sfuggire agli #anticorpi, pertanto potrebbe ridurre in parte l'efficacia dei #vaccini.
La #varianteinglese non ha questa mutazione (per ora), ma brasiliana e sudafricana sì. Per questo sono così temute! 3/
Question for bioinformaticians! Believe it or not, the first genome of bat virus #RaTG13 had some nucleotides that were supported by zero reads: in other words, the genome didn't match the sequences that were used to assemble it. How is it possible? 1/ #originsofSARSCoV2
Assemblers are computer programs, they do not "invent" nucleotides. So, what happened here? My explanation was that this genome was assembled using other reads, maybe in addition to the ones that were uploaded. 2/
In that case, I expected the authors to upload the missing reads.. Instead they did the opposite: they updated the genome, replacing the nucleotides supported by zero reads with the correct ones. So, the question is: how the heck did they assemble the genome the first time? 3/
Conspiracist, May 2020: "Look, these sequences in database are dated 2017/2018. So you didn't sequence RaTG13 this year, as you wrote in the paper!" 🔬
Average scientist, May 2020: 😴
Shi Zhengli, July 2020: "Yes, actually we got the sequence in 2018."
2/
Conspiracist, May 2020: "Have a look at these Chinese theses we found on the internet: RaTG13 was found in a #mineshaft were people died of #pneumonia!" 😱
Average scientist, May 2020: 😴
Shi Zhengli, June 2020: "Oh yes we found it there, but.. well, the cause was a fungus"
3/
Ora, è vero che a Wuhan facevano chimere a scopi di ricerca, ma questi due virus sono troppo diversi da SARS2 per essere i suoi antenati diretti. 2/
Il nuovo #coronavirus infatti ha una similarità dell'87% con questi due virus, troppo poco per essere il risultato di una loro ricombinazione (il virus più simile a SARS2 è #RaTG13). 3/
Il modello di @istsupsan che ha guidato le decisioni del governo sulla fase 2 è un modello SIR stocastico strutturato per età. Uno dei punti di partenza è questa tabella, che quantifica i contatti medi degli italiani in base a età e luogo del contatto. 1/
La suddivisione dei lavoratori in base al settore di attività (es. edilizia, manifattura) si basa su dati INAIL. Il modello fa molte assunzioni: ad esempio ipotizza che i contatti nel tempo libero passino dal 10% (dati Google) al 34% in caso di apertura di bar e ristoranti. 2/
Le simulazioni prevedono due modalità di trasmissione della malattia: uno immagina che siamo tutti ugualmente suscettibili all'infezione, l'altro ipotizza che gli anziani siano più suscettibili della fascia 15-64, che a sua volta è più suscettibile dei bambini. 3/