Like others I doubt the infection and fatailty rates because of South Korea and Diamond princess (if the author knew about how much this result conflicts with those datasets then its up to them to argue why the new paper is better).
R0=5 isn't completely unbelieveable. If the doubling time without containment measures is 2 days and the infective period is 12 days (i.e. 5 days incubation period and a week afterwards) then R0=5. Unfortunately based on the rather unbelievable infection and fatality rates I don't think this paper really adds any evidence for this - it suggests the model is fatally flawed.
True, but Diamond Princess is full of oldies, and, despite South Korea massive testing, there might be selection bias - I guess people would only get tested if they had some symptom or contact with other infected persons (perhaps you're referring a more specific study?). Notice that, if the science study claiming 86% of the cases in Wuhan were undocumented were right, this would already imply a fatality rate of about 0.6%, below South Korea estimates.
Yet, I agree the fatality rate is surprisingly low, and it's just a statistical model.
Diamond princess is important because they did 100% testing so it gives us an idea of asymptomatic : symptomatic ratio. The result was roughly 1:1, nothing like 50:1 or whatever this paper suggests. The science study with 6:1 is at least plausible if you account for symptomatics who weren't identified.
If South Korea hadn't managed to test the majority of their cases then it is unlikely that they would have managed to reduce their infection rate so dramatically - their quarantine measures aren't massively strict although I think the population are self-enforcing good practice pretty well. I doubt that Wuhan death rates could be below South Korean rates due to the acknowledged overcrowding in Wuhan. Again, 0.6% is kind of plausible, the model here (0.1%) isn't.
New editorial about the asymptomatic rate in Nature - the author of the preprint above are featured in this as well. They say asymptomatic and mild case rate might be up to 50% of all infections and that these people are infectious.
And another preprint saying there were +700k cases in China on 13th of March:
"Since severe cases, which more likely lead to fatal outcomes, are detected at a higher percentage than mild cases, the reported death rates are likely inflated in most countries. Such under-estimation can be attributed to under-sampling of infection cases and results in systematic death rate estimation biases. The method proposed here utilizes a benchmark country (South Korea) and its reported death rates in combination with population demographics to correct the reported CO...
And yet another preprint estimating the R0 to be 26.5:
Quotes from paper:
"The size of the COVID-19 reproduction number documented in the literature is relatively small. Our estimates indicate that R0= 26.5, in the case that the asymptomatic sub-population is accounted for. In this scenario, the peek of symptomatic infections is reached in 36 days with approximately 9.5% of the entire population showing symptoms, as shown in Figure 3."
I think they estimate about 1 million severe cases in the US alone if left unchecked at the peak.
"It is unlike...
Another preprint suggesting that half or more of the UK population is already infected:
FT coverage:
https://www.ft.com/content/5ff6469a-6dd8-11ea-89df-41bea055720b
study:
https://www.dropbox.com/s/oxmu2rwsnhi9j9c/Draft-COVID-19-Model%20%2813%29.pdf?dl=0
tl;dr: Someone wrote buggy R code and rushed a preprint out the door without proofreading or sanity checking the numbers.
The main claim of the paper is this:
The total number of estimated laboratory–confirmed cases (i.e. cumulative cases) is 18913 (95% CrI: 16444–19705) while the actual numbers of reported laboratory–confirmed cases during our study period is 19559 as of February 11th, 2020. Moreover, we inferred the total number of COVID-19 infections (Figure S1). Our results indicate that the total number of infections (i.e. cumulative infections) is 1905526 (95%CrI: 1350283– 2655936)
So, they conclude that less than 1% of cases were detected. They claim 95% confidence that no more than 1.5% of cases were detected. They combine this with the (unstated) assumption that 100% of deaths were detected and reported, and that therefore the IFR is two orders of magnitude lower than is commonly believed. This is an extraordinary claim, which the paper doesn't even really acknowledge; they just sort of throw numbers out and fail to mention that their numbers are wildly different from everyone else's. Their input data is
the daily series of laboratory–confirmed COVID-19 cases and deaths in Wuhan City and epidemiological data of Japanese evacuees from Wuhan City on board government–chartered flights
This is not a dataset which is capable of supporting such a conclusion. On top of that, the paper has other major signals of low quality. The paper is riddled with typos. And there's this bit:
Serial interval estimates of COVID-19 were derived from previous studies of nCov, indicating that it follows a gamma distribution with the mean and SD at 7.5 and 3.4 days, respectively, based on [14]
In this post I collected estimates of COVID-19's serial interval. 7.5 days was the chronologically first published estimate, was the highest estimate, and was an outlier with small sample size. Strangely, reference [14] does not point to the paper which estimated 7.5 days; that's reference 21, whereas reference 14 points to this paper which makes no mention of the serial interval at all.
I was particularly bemused by quoting cumulative infections to 7 significant figures where the 95% confidence interval spanned a factor of 2. This did not fill me with confidence...
This suggests that South Korea missed about 90% of infections despite their extensive testing, which many have argued is responsible for their success at containment. This is so implausible that I'm hesitant to even look at the paper. But I bookmarked it and will report back if I find something interesting!
It's interesting though that with the swine flu pandemic, experts were initially alarmed about a somewhat high IFR, and later on it turned out that the vast majority of cases were extremely mild. The WHO got accused of "crying wolf" over swine flu even though it ended up infecting more than 11% of the planet, and killing more than a hundred thousand people according to this Wikipedia article. So it was really bad, but initially some experts feared it would be a lot worse.
Might something similar be going on with Covid-19? I'm pretty sure that the answer is no, but I thought it was interesting that there's a recent precedent for missing large numbers of milder cases.
I don't think it's the same with Covid-19 because:
Counterarguments to my view:
IFR for the rest of 2020:
Ground glass opacity is named after its visual appearance on a CT scan. Information I can find (and I'm not a doctor, don't trust me at face value!) suggests that it's generally reversible and doesn't indicate any more severity than the pneumonia it's detecting.
The obvious question to reconcile the Diamond Princess and Veneto is: do the tests have subclinical thresholds, and if so are they different? I don't know where to begin researching that, though. (And as a more general concern, I worry the entire line of questioning might be overfitting, maybe there's some random reason that has nothing to do with the general pandemic.)
You're right re the "ground glass", it's describing what the lung looks like on imaging and is very non-specific. (Many etiologies and a long list of differential diagnoses).
A good article re ground-glass opacification and what might have caused it.
As mentioned in a comment above, one of the (pretty highly credentialed) authors of this preprint has written two papers on the Diamond Princess, and so, excuse the appeal to authority, but any argument against this paper based on Diamond Princess doesn't seem likely to invalidate conclusions of this preprint .
Also this squares seemingly squares more with John Ioannidis take on Corona:
"no countries have reliable data on the prevalence of the virus in a representative random sample of the general population."
And that airborn-ish transmission is highly likely.
Also this seemingly squares more with John Ioannidis take on Corona:
Ioannidis makes this claim:
Projecting the Diamond Princess mortality rate onto the age structure of the U.S. population, the death rate among people infected with Covid-19 would be 0.125%.
I don't find a source for this. The adjustments I saw looked different. If he's right about those 0.125%, that would be an important update!
But it feels more plausible to me that the 0.125% thing went wrong somewhere because it just seems ruled out by South Korea, which unlike European countries has their outbreak contained. I can't see how South Korea could somehow have missed 700% of their reported cases even though they are conducting 10,000 tests daily, and have fewer than 10,000 confirmed cases.
UPDATE: I took a shot at doing the age adjustment myself here. The summary: I don't see how one can get anything below 0.3% and, adjusting for selection effects where the least healthy people probably avoid going on cruises, even going below 0.5% seems implausible to me. UPDATE2: I adjusted my estimates after finding more precise data. I still think 0.125% is too low, but I think something like 0.2% is perhaps already defensible. This suggests that the estimate was closer than I thought and I now consider the Diamond Princess not to be evidence in favor of IFR of 0.5% or higher (assuming no hospital overstrain).
As mentioned in a comment above, one of the (pretty highly credentialed) authors of this preprint has written two papers on the Diamond Princess, and so, excuse the appeal to authority, but any argument against this paper based on Diamond Princess doesn't seem likely to invalidate conclusions of this preprint .
Interesting, I wasn't aware of that! Makes me upshift that I was wrong, but also upshift that one author is responsible for several studies that I found dubious.
I looked through his list of publications and it seems he finished 2 papers on the prevalence of asymptomatic cases on the Diamond princess already (but not on fatality rates from there!). And the second one reports a point estimate that is outside the 95% confidence interval of the first paper, yet I don't see any addendum to the first paper. This seems kind of odd?
And that airborn-ish transmission is highly likely.
I don't have strong views on that. The only thing I feel confident about is that an IFR of below 0.5% seems extremely implausible.
The ~1% infection fatality rate on the Diamond Princess (where everyone was tested) is pretty solid evidence against this.
Not sure: the Diamond Princess is mentioned in this preprint and in fact one of the authors of this preprint wrote two papers on the Diamond Princess:
https://scholar.google.com/citations?hl=en&user=OW5PDVgAAAAJ&view_op=list_works&sortby=pubdate
So I think they thought about this,
They don't mention Diamond Princess IFR estimates in their paper, though. In fact, the study doesn't cite other studies on IFR estimates for SARS-CoV-2 at all. I don't get what's going when soemeone writes a paper with a conclusion that's 5-10x lower than all the other estimates before, but instead of including a discussion on why this might be the case or how it might fit with apparently contradictory data points (e.g., the cruise ship IFR or South Korea's IFR), they just move on to the next paper. Credentials or not, I find that process pretty dubious. I realize that there's an implicit hypothesis in the paper that "because transmission is stronger than we thought, others might have underestimated the number of mild or asymptomatic cases." Okay, but that hypothesis is contradicted by data points he must be aware of (as you say, he wrote papers on the cruise ship). Why is there no discussion on this?
What do people think of this preprint from March 13th?
It suggests:
The authors are very reputable (GScholar profile first author, senior author, also quoted in the NYT).
If this is true, might there be many more (asymptomatic) cases everywhere now than people think?
From paper:
"Recently more evidence suggests that a substantial fraction of the infected individuals with the novel coronavirus show little if any symptoms, which suggest the need to reassess the transmission potential of this emerging disease"