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Discussion - Estimating the CFR for 2019-nCoV

alert said:
WHO today says that there are 82 confirmed cases outside of China, with no fatalities and only one severe case. Even if you assume the severe case has a 50/50 chance of dying (which is probably high), 0.5 deaths in 82 cases is about a 0.6% CFR.

If instead, you back only Hubei out of the global count, you're left with about 3900 cases and 9 deaths so far (with 71 confirmed recoveries).

Also, Zhejiang province now has 537 cases without a death (but only 9 discharges).

Both of these facts suggest to me that this virus might be milder than previously thought.
Click to expand...

The raw death/case ratio for Hubei vs the rest of the world is continuing to diverge. I think the main argument against this being good news is that the point at which Hubei showed a dramatic upswing in case numbers was a week ago and with a 2 week incubation period we might yet see it happen elsewhere in a week or so. Thailand concerns me, as they have a relatively large number of cases and their government has said that they have no capacity to respond.
 
I'm assuming the reason that Hubei is running at 10x the fatality rate of the rest of the world is that they've missed the mildest 90% of their cases, so are using a wrong denominator.

It's a lot easier to get confirmed as an nCoV case with "travel from Wuhan" than it is in a city with tens of thousands of cases.
 
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. Then the CFR would be only ~0.3%
or 150000 deaths in USA with the assumptions above.
Twice as many as in the bad 2018 flu-season
 
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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%
 
https://www.scmp.com/news/china/art...eath-toll-china-rise-epicentre-hubei-province

As many as 75,815 people in Wuhan may have been infected with the new
coronavirus
, according to a study by University of Hong Kong scientists.

The research, published in The Lancet on Saturday, is based on the assumption that each infected person could have passed the virus on to 2.68 others. The estimated total was as of Tuesday, it said.

Meanwhile, the number of new confirmed cases and deaths from the coronavirus in mainland China have hit record daily levels.

Authorities in Hubei province, the epicentre of the outbreak, reported 45 new deaths and 1,347 new confirmed cases on Saturday – both daily highs. Of the newly reported deaths, 33 were in Wuhan, the provincial capital, according to the Hubei Health Commission.
....snip
 
Data from http://www.nhc.gov.cn/xcs/yqtb/list_gzbd.shtml

Difference calculated from Discharged minus Deaths.

Still a noisy graph, but the trend suggests that the discharged number is accelerating faster than the fatality number.

nCoV.webp
 
One aspect of this outbreak that is puzzling is the apparent abruptness of the illness.
We have seen multiple videos of people who have simply collapsed while going about their normal business.
Yet it seems unlikely that anyone so sick as to be near collapse would bother to get up, get dressed and go out.
Is this a phenomenon that is common to other types of SARS like illnesses?
 
gsgs said:
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%
Click to expand...

I think this may have to do with onset of clinical symptoms. If Hubei started, people have been ill for a longer time. I think the first reported fatalities were around 10 days after onset of symptoms. Does that make sense ?
 
If that is an explanation fatality rates in other provinces will start to go up in a few days and intetnationally in a week to two weeks
 
Deriving the CFR by comparing deaths to hospital discharges

Ronan thanks for the graph. We have to be careful in interpreting these numbers.

First these two groups, dead people and survivors (the discharged patients), have nothing in common statistically so charting them together or plotting the difference is not really meaningful.

We need to compare the number of deaths with the number of people who are actually infected to obtain a reasonable estimate of the CFR. As JJackson has pointed out elsewhere in the forum, we can not even guess how many people are actually infected. For the purposes of the 2019-nCoV infections we can assume that the pretty much the entire world population is susceptible to infection. Even in a na?ve population (where no one has immunity), there will always be a few people who do not get infected.

Among the remaining members of the population, some may be infected and asymptomatic and not be counted. Others may be sick with mild symptoms and, if they are not tested, will probably not be counted. Compounding matters is that any given point in time, some people will be presymptomatic even if they are infected.

News media report that testing kits are not widely available. We can speculate that testing is only going to be carried out on very sick individuals presenting themselves for treatment. Presumably the daily increases in confirmed (tested) cases, reflects the increase in severe cases, not the actual number of new infections which could be much larger.

I assume that the discharged (recovered) cases refers only to very sick individuals who have recovered. What we need to know is how many of the confirmed cases are under treatment to understand the relationship of severity to deaths verses recoveries. I don’t think that the health officials are including mild or asymptomatic cases in the discharged or recovered count.

The CFR equation is simple. The numerator is the number of deaths, the denominator is the number of all infected people not just the severely ill ones. The paragraphs above relate to estimating the denominator. But we also need to be skeptical of the numerator, the number deaths.

First, given China’s track record, we have no reason to believe that the number of deaths is real. There are unsupported reports that there are many more deaths that are now being covered up by the Chinese. Second, deaths directly attributable to the coronavirus may be underreported. Because of comorbidities, some deaths may be assigned to a different cause than the coronavirus.

At this early stage of the 2019-nCoV outbreak, we are just guessing at what the final CFR might be.
 
Laidback Al said:
Deriving the CFR by comparing deaths to hospital discharges

Ronan thanks for the graph. We have to be careful in interpreting these numbers.

First these two groups, dead people and survivors (the discharged patients), have nothing in common statistically so charting them together or plotting the difference is not really meaningful.
Click to expand...

It depends on what you are looking for. Many people I have been interacting with are worried that the ratio of deaths to recovered is quite high (about 48% at time of writing). I have seen posts that in order to be declared cured, the patient must be symptom & virus free for two weeks. I suspect that this would mean that the number of cured is a lagging indicator in that for patients admitted on the same day, they could pass and be added to the dead total at any time, but if they survive, will not be added to the survived total for several weeks. Comparing the trends in the two numbers suggests that the survival numbers are now increasing faster than the fatality numbers. To me, that provides support to the idea that the current Fatality: Cured ratio of confirmed is way too high and will end up being much lower.

So I now have a lower and upper boundary for my cfr calculations.

Lower = current # of deaths/ suspected number of cases = 259/200,000 = 0.13% (within the range of flu)
Upper = current # of deaths/ resolved cases = 259/534 = 48%

I'm certain that the lower number will increase a bit as we get more data and now I'm equally certain that the upper number will decrease as we get more data each day. I know that this is a massive range and really not at all useful, but it will tighten up over time.
 
Ronan Kelly said:
It depends on what you are looking for. Many people I have been interacting with are worried that the ratio of deaths to recovered is quite high (about 48% at time of writing). I have seen posts that in order to be declared cured, the patient must be symptom & virus free for two weeks. I suspect that this would mean that the number of cured is a lagging indicator in that for patients admitted on the same day, they could pass and be added to the dead total at any time, but if they survive, will not be added to the survived total for several weeks. Comparing the trends in the two numbers suggests that the survival numbers are now increasing faster than the fatality numbers. To me, that provides support to the idea that the current Fatality: Cured ratio of confirmed is way too high and will end up being much lower.

So I now have a lower and upper boundary for my cfr calculations.

Lower = current # of deaths/ suspected number of cases = 259/200,000 = 0.13% (within the range of flu)
Upper = current # of deaths/ resolved cases = 259/534 = 48%
Click to expand...

Yes, it common for a patient to be declared cured once tests determine that they are free of the virus for a certain period of time. As noted in NawtyBits post there may be a possibility of reinfection. More time will have to pass before we can assess the incubation period and the recovery period for sick individuals. The range you provided is sufficiently large to encompass the eventual CFR for 2019 nCoV. I hope with more information we can narrow that range.
 
Another paper looking at early transmission rates.

https://www.nejm.org/doi/full/10.1056/NEJMoa2001316 [h=2]RESULTS[/h]
Among the first 425 patients with confirmed NCIP, the median age was 59 years and 56% were male. The majority of cases (55%) with onset before January 1, 2020, were linked to the Huanan Seafood Wholesale Market, as compared with 8.6% of the subsequent cases. The mean incubation period was 5.2 days (95% confidence interval [CI], 4.1 to 7.0), with the 95th percentile of the distribution at 12.5 days. In its early stages, the epidemic doubled in size every 7.4 days. With a mean serial interval of 7.5 days (95% CI, 5.3 to 19), the basic reproductive number was estimated to be 2.2 (95% CI, 1.4 to 3.9).
 
in cases with available age , the mean age of Wuhan cases is 43.0 (271) , and the mean age of
all cases is 43.3 (343) , no big difference.
In the total statistics the first seafood-market cases should play no role, meanwhile. So many cases meanwhile.
I see no reason why the CFR should be higher in Wuhan
 
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Wuhan and China should comment on this. (The likely many unreported cases from Wuhan )
As well as WHO,ECDC,...
It's their task. That we have to hear from it on the internet forums and modeling studies
and Hong Kong experts is not increasing their credibility and trust
 
Obviously the numbers from China are suspect.
However, there is now a substantial number of patients hospitalized outside of China which should allow a determination of the cfr for optimally treated cases within the next couple of weeks.
However, the cfr will be entirely different when the hospital resources are overstretched and support is minimal.

So we must hope that the current efforts to isolate the potential patients to halt the spread of the disease are successful. If we see the same exponential growth in cases here and in Europe as we have seen in China, the cfr will be brutal and apply to a massive number of instances.
 
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