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#Post#: 36--------------------------------------------------
estimating the cfr
By: gsgs Date: February 1, 2020, 1:40 am
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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]
==========================================
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
-------------------------------------------------------
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
#Post#: 59--------------------------------------------------
Re: estimating the cfr
By: epsilon Date: February 6, 2020, 5:43 am
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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.
#Post#: 66--------------------------------------------------
Re: estimating the cfr
By: epsilon Date: February 7, 2020, 6:50 am
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Building upon the idea to only use the cases outside china (as a
the most unbiased sample we have at this time),
[attachimg=3]
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:
[attachimg=2]
Luckily I found that this work has already been done by a Swiss
research group who put their code and figures on github:
HTML 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%
[attachimg=1]
HTML 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)
#Post#: 71--------------------------------------------------
Re: estimating the cfr
By: gsgs Date: February 8, 2020, 1:30 am
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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
--------------------------------
yes, I should have considered that time lag. I thought it were
just a few days
#Post#: 72--------------------------------------------------
UPDATE: Althaus CFR estimate now at 1.7%
By: epsilon Date: February 8, 2020, 6:20 am
---------------------------------------------------------
UPDATE: case fatality ratio of 2019-nCoV at
1.7%
(95% confidence interval: 0.1%-7.5%)
HTML https://github.com/calthaus/ncov-cfr
#Post#: 73--------------------------------------------------
Re: estimating the cfr
By: epsilon Date: February 8, 2020, 6:29 am
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@gsgs:
[quote]
take cases outside Wuhan or outside Hubei , that gives much more
cases
and still relatively few deaths.
[/quote]
Yes. And whats even more interesting: Much more "discharged"
cases too.
I did a very rough calculation CFR = fatal / (fatal +
discharged) for all non-hubei provinces and it was only about
1%.
This seems roughly consistent with the Christian Althaus
estimate (that I posted recently and that I have much confidence
in his model and method) which is based only on non-china cases
and is now at CFR=1.7%
This reminds me more and more of the situation with the 2009
H1N1 pandemic where the CFR was initially estimated 10% then 1%
and in the end it was like less than 0.1%, i.e. really "just the
flu".
The other lesson from 2009 H1N1, however, was that it could NOT
be contained. The global attack rate was 50%. We were lucky that
the CFR turned out so benign. Hopefully it will be similar this
time.
However, there is a freightening scenario with the new Virus
even if the final CFR would "only" be something like 0.5% and a
50% global attack rate which would still be a devastating
pandemic with millions of deaths.
#Post#: 76--------------------------------------------------
Re: estimating the cfr
By: gsgs Date: February 8, 2020, 8:57 pm
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thanks for the cfr-updates.
Yes, 1.7% is still pretty bad .
however the case numbers are going down !
#Post#: 86--------------------------------------------------
Re: estimating the cfr
By: gsgs Date: February 10, 2020, 6:12 am
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10 February 2020 - Imperial College London‌
Report 4: Severity of 2019-novel coronavirus (nCoV)
(Download Report 4)‌
HTML https://www.imperial.ac.uk/media/imperial-college/medicine/sph/ide/gida-fellowships/Imperial-College-2019-nCoV-severity-10-02-2020.pdf
this assumes a time-lag of 22.2 days from "confirmed" to "death"
and it assumes that all cases are confirmed ;
CFR=deaths/(confirmed cases)
My data starts Jan.25, before that there were 572 confirmed
cases in Wuhan,
157 in Hubei ex Wuhan, 558 in China ex Hubei.
Currently there are ~70 daily deaths in Wuhan, 18 in Hubei ex
Wuhan, 7 in China ex Hubei.
If those cases pre-Jan.25 were all attributed to Jan.18 , then
with the 22-day-lag
I get CFR=12.2 in Wuhan, CFR=11.5 in Hubei ex Wuhan, 1.3% in
China ex Hubei.
Obviously many cases were unconfirmed, especially in Wuhan.
There were those 5M people
leaving the city at that time.It is likely that severe cases had
a greater probability
of being confirmed.
You would expect deaths climbing sharply after 10-20 days
already - even if 22 were the average.
I do not see this. Deaths in Hubei ex Wuhan (where I'd assume
not much underreporting)
were 2,6,12,12,12,13,15,16,16,18,5,14,18,18
And we clearly have no exponential increase in confirmed cases
as they assume
--------------------------------------------
I'm unsure, that all doesn't make so much sense to me.
The CFR might be changing. The CFR might be different in Wuhan.
The 22-day-lag might be too long.
(CFR=deaths per all infections).
------------------------------------------------------
and then we have "severe cases" . These counts were up quite a
lot since Feb.03,
but now they somehow have redefined "severe":
daily reported new severe cases in Hunan Jan.26-Feb.09 :
109,400,189,89,106,200,268,139,442,377,564,918,119 3,52,258
daily reported new severe cases in China ex Hunan ,
Jan.26-Feb.09 :
28,115,74,42,51,68,47,47,50,54,96,44,87,135,38 (212)
#Post#: 89--------------------------------------------------
Re: estimating the cfr
By: epsilon Date: February 10, 2020, 7:52 am
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"Obviously many cases were unconfirmed, especially in Wuhan.
There were those 5M people
leaving the city at that time.It is likely that severe cases had
a greater probability
of being confirmed."
Th big question is: How prevalent was the virus already in the
general community when Wuhan Quarantaine begun ?
My gut feeling is at least 1% prevalence, maybe even 10%
obviously (and hopefully) this would imply many more mild cases
than assumed previously.
Most models based on exported cases put the pre-shutdown absolut
case numbers between 25k and 150k, corresponding to roughly
100k/10M = 1% prevalence.
So there is, unfortunately, still large uncertainty of one order
of magnitude (factor 10) about the actual pathogenity/severity
of this virus.
What we really need are seroprevalence studies for 2019nCoV
antibodies in every large community.
My hope is, that sero prevalence is very high already because
this means that the vast majority of cases are mild or
asymptomatic cases.
But until we have the data, this may be just wishful thinking.
#Post#: 95--------------------------------------------------
Re: estimating the cfr
By: gsgs Date: February 11, 2020, 12:26 am
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you could compare the Wuhan deathrate with the deathrate outside
Wuhan
to get ~ 2-3 times more real cases in Wuhan
assuming no covered up deaths in Wuhan, assuming same real
deathrates in and out Wuhan
~20 daily deaths in Wuhan, when it was quarantined. That's about
the amount
in Hubei ex Wuhan now - 14 days later
so with that speed there had been ~400 cases in Wuhan ~Jan.10
redouble every 3-4 days to get 6400 cases on Jan24 , 100000 now
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