lbeltrame

Phylogenetic analysis showed that in most countries there were multiple seeding events before the infections were discovered. In short, it wasn't just one sick person.

As a scientist, some of their public statements have been weird to say the least, in particular the very controversial, poorly-worded and then retracted tweet on immunity.

And then, pausing SOLIDARITY on the HCQ arm because of the flawed Lancet study (granted, they weren't the only ones to fall for it).

This does not excuse people (in particular well-educated people) from not using their brains.

I'd go further, and say that actually a lot regarding this disease is still heavily polarized, without any room for more nuanced positions.

I read it. No hard data presented save for a couple of findings. Key aspect of the message: following the precautionary principle. I can expect governments to act on that, but not scientists.

I'd have expected an appeal to study more on that instead. The precautionary principle is absolutely not scientific.

> 1) Seroprevalance of antibodies in just 5% of the population in one of the hardest hit European countries

I think this is only partly relevant. SARS-CoV-2 did not spread like a molecule in a solution. Since the spread is not uniform, seroprevalence in the individual regions is far more important, and IIRC the regional data were up to 3x the national amount in some specific regions.

Does anyone have a copy of the letter or a link to it? I'd like to see the data supporting the claim.

> What I saw on Twitter is many GOP/Trump militants making dubious claims about HCQ effectiveness and branding everyone who disagree victims of TDS..

I also saw the opposite, people saying "we knew all along", before some solid evidence was out (RECOVERY, and the UMN study: the latter however has limits due to lack of PCR-confirmed viral tests). Or they believed the flawed Lancet paper unconditionally (count me among them, it was a mistake).

The whole matter was politicized too heavily and the first victim was science, as far as I can see.

I say "some" and not "the" evidence because there are still some large studies going on, like COPCOV.

The studies were done on cells (taking a sample from the surface after minutes or hours and trying to infect them - if they die, there is infectious virus there), but cells in culture don't have an immune system, nor they have physical barriers like nose and mouth.

At this point animal studies are necessary to determine whether there is significant infection through items or not. Given the spread of the virus in the world, I think it is unlikely at this point, though (it would've been noticed if significant).

I've looked up some papers on the maximum incubation period (by no means a comprehensive search):

- https://pubmed.ncbi.nlm.nih.gov/32594928/ (14 days in 99.5)

- https://academic.oup.com/ije/article/doi/10.1093/ije/dyaa106... (this one says 95% within 14 days)

- https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7302302/ (preprint, says median is 5.35 days, and says the data support the 14 day intervention policy but gives no data about why so)

Most of the studies are with "old" outbreaks so likely more data is needed. Yet the median is still around 2-6 days.

> Playing it safe with the incubation time

That is, applying the precautionary principle. Not very scientific, but understandable (although I don't agree with it). Personally, now that we're well into the epidemic, I'd expect a little more rigor, though.

> with an incubation time of two weeks

Can we stop perpetuating this myth? 14 days is when 99.5% of the people show symptoms. The median, which is far more important, is between 2 to 4 days.

If that were the case it would be hilarious. Nello Musumeci, Sardinia's governor, just last month wanted Sardinia to be COVID-19 free and did not want anyone from any other Italian region without quarantining or constant surveillance.

FTR, My country's government is completely inconsistent. After voting yes to reopen EU's borders to select countries without quarantine, it immediately made an order forbidding tourists from extra EU areas and forcing quarantine upon everyone entering.

Getting properly done studies is hard. In particular the statistics are even harder and easier to mess up (the retracted Lancet paper had also statistical problems).

> I would see acceptance into a top-tier journal - or even a reputable journal - as a very, very strong signal.

Not anymore, I'd say. Both The New England Journal of Medicine and Lancet were fooled by the Surgisphere scandal, and they didn't even notice the statistical errors, let alone the fabrication of the data.

Lancet took years to remove the Wakefield paper on autism and vaccines, and still has other papers with questionable statistics up.

What I consider a strong signal is good data with clear conclusions and well-outlined limitations (these are often as important as the results themselves). Peer review can help with that, but it's not a magic bullet. In that sense top tier journals can be "dangerous" because sometimes they focus on good storytelling instead of presenting the data correctly.

Peer review, while extremely useful in bringing out some, or many warts of a work, is not a substitute for quality control, which depends only on the authors.

> Don't expect that you, the average HN reader, knows better than reviewers with relevant backgrounds.

After what happened with the Surgisphere paper, where the first problem was the statistics (caught by post-publication comments) and only later there was the problem of fake data, the mere presence of a secret review does not mean the work is up to anything.

P.S: yes, I work in the fields of biology and pharmacology and have written and reviewed a number of papers myself.

Only the translation teams use SVN (and perhaps some very old websites, but I think most if not all of them have been moved to git). All the code lives on git, instead.

Montagnier's "proof" is a questionable paper (that has not his name on it, though) that does "decomposing" on the RNA of the viruses with a mathematical transformation that has no biological sense, and by using "patterns" and "waves" "deduces" that there must be something from HIV.

I've read it. It's embarassing on how bad it is written, and the mental gymnastics it uses to "explain" things.

I've tried it years ago, and I couldn't even get it to bootstrap one node. It was, at least at the time, an insanely complex and fragile system.

Has anyone some recent real-world experience in MAAS?

> Declining severity is good, but it's not that important.

It is IMO, because the mere fact of being infected is a necessary, but not sufficient condition to cause problems. What matters is being infected and needing hospitalization (which as far as I can see not clear cut and heavily dependent on the place of spread).

Lack of antibodies in the bloodstream does not equate to lack of immunity.

- There could be antibodies at the mucosal level (IgA)

- There could be cellular responses (T cells) that aren't detected

- There could be immunological memory at play after antibodies aren't detectable anymore

A critique of the work, a little heavy-handed:

https://statmodeling.stat.columbia.edu/2020/06/17/some-forec... (this specific comment)

Note that this study only looks at the asymptomatic rate: it does not attempt to determine how infectious are asymptomatic people.

While this paper[1] doesn't attempt to provide exact dates, the phylogenetic data suggest that there were multiple seeding "events" in each country before outbreaks were actually noticeable.

[1] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7199730/

> First, it was discovered in late December, probably jumping to humans in November

The most recent phylogenetic analysis on 7000+ viral sequences from isolates points at the end of October as a possible date.

I didn't want to downplay the fact that it can be bad. What I meant to say is that this is a respiratory disease virus, and a lot of the stuff it is supposed to cause (according to the press) is actually due to that, not because it is novel.

Even the reported brain infections (neural invasion) aren't a unique feature of this virus, but are recorded as happening with other coronaviruses (the most common ones, not SARS or MERS).

> only to face weeks or months of recovery.

FTR, this also happens with other respiratory diseases. You can also take quite a bit of time (months) to fully recover from "regular" pneumonia.

I argue that in Lombardia (where I live) the virus found niches of vulnerable populations (nursing care homes, hospitals like Alzano Lombardo which weren't closed after infections were found) and then proceeded to cut them down.

Thanks for the links. I'll read the Shenzhen paper as soon as I get the time, but as far as I can remember, there are newer studies that aren't as clear cut at that one.

It would be interesting to see whether there was an uptick in infections in places, like Austria, that have reopened schools.

To me, the evidence on the school closures being effective is totally lacking, given the impact of the virus on the younger population. In fact, most evidence of an effect or lack thereof in general is inconsistent, or lacking.

Governments are acting on the basis of the precautionary principle, not science.

The efficacy of the influenza vaccine has a lot to do with the influenza virus genome, which is fairly different than coronaviruses, and due to that mutates far quicker.

Notice that this is for common coronaviruses, and doesn't mention SARS or MERS much: IIRC, the former elicited an IgG response years after exposure in an experiment. As far as I can tell, this preprint does not cite that work.