4 ms·
«assume that when a case is confirmed the death or cured status is also determined at that moment» This is why epidemiologists (ref: https://pdfs.semanticschol
by mrb 7y ago
«assume that when a case is confirmed the death or cured status is also determined at that moment»
This is why epidemiologists (ref: https://pdfs.semanticscholar.org/ebf2/48c9fc0a1a23d1778b94083319aa995e34f4.pdf https://pdfs.semanticscholar.org/ebf2/48c9fc0a1a23d1778b9408... or https://news.ycombinator.com/item?id=22195827 https://news.ycombinator.com/item?id=22195827 for my comment on the paper) prefer instead this formula which only counts patients for which the eventual outcome is already known:
deaths / (deaths + recoveries)
With this formula, there is no need to guess the "patient timeline". If you do the math right now for the largest case study known to date (published yesterday: https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(20)30211-7/fulltext https://www.thelancet.com/journals/lancet/article/PIIS0140-6... covering 99 patients, 11 dead, 31 recovered) you get:
11 / (11 + 31) = 26% case fatality rate
If you do the math on ALL data from mainland China (170 deads, 124 recovered as of 2020-01-29 http://www.nhc.gov.cn/xcs/yqtb/202001/e71bd2e7a0824ca69f87bbf1bef2a3c9.shtml http://www.nhc.gov.cn/xcs/yqtb/202001/e71bd2e7a0824ca69f87bb... or in english: https://en.wikipedia.org/wiki/Timeline_of_the_2019%E2%80%9320_Wuhan_coronavirus_outbreak https://en.wikipedia.org/wiki/Timeline_of_the_2019%E2%80%932...), you get:
170 / (170 + 124) = 58% case fatality rate
This formula gives a pretty good estimate of the eventual observed CFR according to the paper I referenced above. Of course, there are caveats, for one deaths or recoveries may not be properly tracked: there could be many patients with mild cases that are not even detected/confirmed and end up recovering on their own.
PS: I am not stating the lower bound CFR is 26%! Another method I applied (described in twitter thread https://twitter.com/zorinaq/status/1222427708723879936 https://twitter.com/zorinaq/status/1222427708723879936) suggest it could be as low as 9%.
- mrtksn 7y agoWhat exactly a margin of %9 to %56 tells us anyway?
- deleted 7y ago[deleted]
- akiselev 7y agoNothing conclusive but if a new disease emerges has a mortality rate even approaching 9% and a basic reproduction number (R0) of 1 or greater, it's a significant cause for concern. Combined with the incubation period, asymptomatic transmission, and the population density in which the outbreaks occurred, in this case it's enough to declare a global public health emergency.
- BoiledCabbage 7y agoThe problem is that the method that you use and the paper referenced (https://pdfs.semanticscholar.org/ebf2/48c9fc0a1a23d1778b94083319aa995e34f4.pdf https://pdfs.semanticscholar.org/ebf2/48c9fc0a1a23d1778b9408...) only applies the calculation on data 3 weeks, 4 weeks and 5 weeks after the epidemic has peaked. Of course you can get valid data once things have peaked and are slowing down. The issue is trying to get valid data while still in the exponential growth portion. And it seems like this method would have all the same flaws as other methods on rapidly changing data (if not worse due to the lag between recovery and deaths.). I'm not an epidemiologist, but I believe I see flaws in your application of the methods from the paper. [1] At the bottom page 481 it clearly say the virus peaked on March 27th. The first date they use data for the e2 calculation is April 6th. Two full weeks past the peak.
- aqme28 7y agoPatient timelines still matter. It takes longer to recover than it does to die, so it would make sense to compare current recoveries with the number of deaths from several days ago. But without knowing the patient timeline, I couldn't tell you how many.
- dumbfoundded 7y agoThis is a great point and we should also normalize it to similar flu's in the region. Quality of treatment will vary greatly.
- mrb 7y ago«It takes longer to recover than it does to die» Citation needed. I am not aware of data supporting this (or the reverse.)
- Double_a_92 7y ago> deaths / (deaths + recoveries) How does that produce a meaningful number? If you got 1000s of infected people, and 1 dies... The formula would be 1 / (1 + 0) = 100%. What does that mean?
- acqq 7y agoYou simply have to have the known numbers of confirmed dead and recovered patients. The way you used it "1 / (1 + 0) = 100%" means just "the knowledge used in the formula is that one patient died, zero recovered." In that case, yes, the fatality rate is "everybody dies." But using the sample of 1 is of course not meaningful for any statistics, not only for that formula.
- tremon 7y agoIt means that nobody has succesfully recovered following a confirmed infection, which is exactly what your data suggests.