If you have a mild cough or a bit of a cold, you might not think anything of it beyond staying home from work, but that could be COVID-19 (and we might _never_ know that it was).
There was a recent (Feb 17) study here with mortality crosstabs (see ‘results’): http://weekly.chinacdc.cn/en/article/id/e53946e2-c6c4-41e9-9...
Case fatality rate (N_deaths/N_confirmed_cases):
[0-9]: NA
[10-39]: 0.2%
[40-49]: 0.4%
[50-59]: 1.3%
[60-69]: 3.6%
[70-79]: 8.0%
[>=80]: 14.8%
Case fatality by date of onset:
[<Dec 31] 14.4% (n=105)
[Jan 1-10] 15.6% (n=653)
[Jan 11-20] 5.7% (n=5417)
[Jan 21-31] 1.9% (n=26468)
[>Feb 1] 0.8% (n=12030)
That does make the overall fatality rate look quite a bit worse than the naive calculation.
This calculates Death Rate = (number of deaths / number of cases) which seems like how you're saying not to, but does split by age.
https://www.worldometers.info/coronavirus/coronavirus-age-se...
If you look at the Diamond Princess, where seemingly everybody was exposed to the virus, the actual death rate was about 0.4%, which is within error bars of the flu.
Given how it can take weeks to die after being infected, I doubt they will be the last deaths.
I’d say though you’re fear mongering posting a comment like this, why ? Maybe you don’t realise ?
If you're just stating that without posing a counter argument then I think you have failed to understand what I am saying. And that is precisely why I posted.
1. The methodology being used to arrive at the 2-3% figure is unambiguously vulnerable to bias. It may be the case that other biases (under-reporting mild cases) cancels out the effect, or maybe not.
2. The same methodology when applied to SARS was provably biased, and an alternative seemingly equally valid estimator was accurate for SARS and gives a much higher estimate for the mortality rate of coronavirus.
If, in fact, we are off by mortality estimates by a factor of 4 it needs to be more widely known because the appropriate economic trade-off in handling is different at the two mortality levels. (In particular, if the mortality rate is much higher for working age people then economically disruptive countermeasures are more justified.)
I'm doubtful that any comments on hacker news are likely to result in public panic. I think for the most part the audience here is capable of reasoning about these things and making prudent decisions.
Ok it’s fine to speculate, but you’re throwing up some big figures in what’s already a panicked situation and pretty much everything you’re saying is based purely on speculation and anecdotal evidence.
I just find it odd health organisations have already done studies, published numbers yet people all cover the internet (on HN of all places) seem to feel like they want to exaggerate the issue, refute the science and don’t trust the existing numbers. Why ?
I spoken with a professional epidemiologist and they also agreed.
If CDC were saying that they considered this case and concluded that d/c is a more reliable estimator, I'd be happy to hear it. Instead, it appears d/c -- which is a good estimator for viruses in steady state-- is being used because it's just the default and the only research I can find which has actually evaluated this question found that d/c underestimates in a rapidly spreading infection.
I don't think this is true, considering China has built new hospitals just for patients who are tested positive but have light symptoms [0].
China also sent 12500 testing kits to Japan [1].
[0]: https://www.zhihu.com/question/369522812
[1]: https://mainichi.jp/english/articles/20200226/p2a/00m/0na/00...
Disclaimer: I'm from China.
Both 2% and 7% will end up being massively overstated fear-mongering in a “pandemic” that never really actually qualified as such, and will kill less than 1/100th the number of people who die from Flu this year.
But everyone loves a good disaster story.
The 2% figure comes directly from dividing deaths by identified cases. Because it takes a while to kill and new cases are growing exponentially this figure is very likely an underestimate. (not certainly an underestimate because non-severe cases are less likely to get counted)
Instead, you can gauge mortality by looking at deaths/(deaths+recoveries). With this method you get a number around 7%. This can produce an overestimate, either because recovery takes a long time or because non-severe cases don't get counted.
This question was also asked about SARS and it turns out that for SARS deaths/cases was a massive underestimate until the rate of the rate of new infections decreased. For SARS d/(d+r) was a much more accurate estimation at all times.
https://blog.zorinaq.com/case-fatality-ratio-ncov/
2% and 7% are both pretty bad, but they have distinctive public policy implications. I hope we're not making bad decisions simply because people handle exponential processes poorly.
Has anyone seen death and recovery by age? I think it would be interesting to estimate mortality by age using the d/(d+r) method, and perhaps contemplate what effect that might have on the composition of the US senate. :-/