nCoV - discussion > nCoV - discussion
estimating the cfr
gsgs:
currently we have 2.2% = deaths/confirmed cases.
That would make ~1mllion deaths in USA within 1 year (when the vaccine may become available)
Assuming the spread is as in 2009
------------------------------------------------------------------
On February 12, 2010, the CDC released updated estimate figures for swine flu,
reporting that, in total, 57 million Americans had been sickened, 257,000 had been
hospitalised and 11,690 people had died (including 1,180 children) due to swine flu
from April through to mid-January.[128]
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but ...
I should really add here, that they have apparently many cases which are unconfirmed,
but less likely deaths that are unnoticed.
There were estimates about 100000 cases already.
These would probably still have developed immunity.
Then the CFR would be only ~0.3%
or 150000 deaths in USA with the assumptions above.
Twice as many as in the bad 2017/2018 flu-season
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also :
164 cases outside China with 0 deaths ; cfr=0
7153 cases in Hubei with 249 deaths , cfr=3.5%
3992 cases outside Hubei with 9 deaths ; cfr=0.2%
this supports the assumption that there are many nonconfirmed cases in Hubei
epsilon:
Unfortunately it is still too early for a reliable CFR estimate.
There are three major biases.
First the unknown number of actual infections vs. reported numbers of confirmed cases. There are estimates of an ascertain rate of about 0.1 in the literature (i.e. actual cases = ten times reported cases).
So this bias leads to a 10 times over-estimation of the true CFR.
Second: The time lag issue between symptom onset and death. For SARS/MERS like illnesses (with the typical clinical picture of worsening pneumonia only after 10 days, then progressing to ARDS and ICU/ventilator support as is also typically reported for nCoV ) it is well established in the literature that average time from symptom onset to death with SARS is about three weeks (and even longer for the younger age groups).
So we must not relate the number of deaths to the current number of cases but to the number of cases three weeks ago. Given the high case doubling rate of about 3-5 days, there were 10-100 times less cases three weeks ago.
So this second bias leads to 10 to 100 times under estimation of the CFR.
Third there is the aspect of reliability of information from authoritarian state officials when it comes to such important and sensitive figures like death rates from a new epidemic. This is not to say that there is "large scale" intentional desinformation. All in all we should trust China to not completely misrepresent the big picture (in its own interest) but it would not be surprising if the numbers are indeed somewhat "tuned" towards being less panic/fear inducing for the general public.
Altogether there are so many sensitive parameters, assumptions and biases that it seems almost impossible to infer the true CFR at this time.
I have extensively researched the topic in the past weeks but still I can neither rule out a best-case scenario with <0.1% Flu-like CFR nor can I rule out a worst case scenario with 15% SARS-Like CFR.
We should get a better picture by end of February when the first 100-or-so closely observed "exported" cases outside china will have passed the 3-4 weeks mark after their symptom onset.
Then we will have a reasonably unbiased sample of the final outcome of 100 closely monitored patients.
epsilon:
Building upon the idea to only use the cases outside china (as a the most unbiased sample we have at this time),
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I thought about writing a little simulation program for calculating the probabilities (confidential intervals) of CFR given the known number of deaths among them (n=2 so far) and the distribution of time-to-death which has been described as Weibull-like distribution in the literature so far:
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Luckily I found that this work has already been done by a Swiss research group who put their code and figures on github:
https://github.com/calthaus/ncov-cfr
They even regularly update their estimates based on new fatal cases outside china.
The most recent estimate is CFR = 2% (rightmost bar in the diagram)
Confidence: 5% probability that CFR is below 0.1% or above 8.8%
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https://github.com/calthaus/ncov-cfr/blob/master/figures/ncov_cfr.png
(Ironically: 2% is about the same number as given by the very naive and biased approach of the mass media to simply divide currently reported deaths by total cases)
Remaining biases are:
- Not counting for very mild/asymptomatic cases which would lead to CFR over-estimation.
- avg. time to death could be higher (for SARS it was over 3 weeks) which would lead to CFR under-estimation
Still, this is the first CFR estimate that I am reasonably confident in to be not too far off at least on the high side of the confidence interval. (regarding the low side I still hope that CFR will be lower in the end due to increasingly more very mild/asymptomatic infections)
gsgs:
take cases outside Wuhan or outside Hubei , that gives much more cases
and still relatively few deaths.
deaths in Hubei outside Wuhan started to climb on Jan29, since then ~12 deaths per day
=1% of cases.
deaths in Wuhan started ~Jan 25
deaths outside Hubei may be starting now slowly, 3,4,5 the last days
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yes, I should have considered that time lag. I thought it were just a few days
epsilon:
UPDATE: case fatality ratio of 2019-nCoV at
1.7%
(95% confidence interval: 0.1%-7.5%)
https://github.com/calthaus/ncov-cfr
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