Any idea what the rates are for the corona virus?
In reality, though, people who are going to die don't die at the moment of infection confirmation and people who are going to live do lag in the log because it takes time to confirm if someone has recovered and virus-free.
Some will suggest to simply compare the deaths to the confirmed case from a week? ago but this assumes that the patients are admitted at the same stage of their infection and all cases at the time are accounted for(deaths are probably much better tracked than the infection and the publicity has a huge impact on the reporting). It would be a guesstimate at best.
I would say, let's stick to official numbers since the calculation requires each patients timeline. Surely an educated guess can be constructed by modelling the patient prognosis and virus behaviour but that also requires much more data than what the public has.
This is why epidemiologists (ref: https://pdfs.semanticscholar.org/ebf2/48c9fc0a1a23d1778b9408... or 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/PIIS0140-6... 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/e71bd2e7a0824ca69f87bb... or in english: 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) suggest it could be as low as 9%.
Citation needed. I am not aware of data supporting this (or the reverse.)
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.
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?
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.
Any numbers we've seen so far seem very tame to me, compared to the pictures out of Wuhan.
If you don't want to read subtitles for 26 minutes here's all the subtitles copy-pasted from the video: https://pastebin.com/6hJ4h4rm
(You can hit the "..." above the red subscribe button and select "open transcript", but it shows up in a tiny window).
I suppose the WHO saying they're very impressed with how China is handling the situation is because they felt the pressure to save China's face.
Yes the WHO are playing politics when they focus on the good things China is doing and ignore the bad. But personally I think they are closer to the truth than those who present an entirely negative version of events. China's response has been 70% good :)
Not really, they jailed the experts who told them that they needed to act quickly, sat on it for a month, and finally did something about it when it was already out of hand.
If you don't mind me asking, where did you see that info?
I watched the CDC press conference today and saw nothing but fear written on their faces. And that is with far more advanced notice than the Chinese had.
Reading through it made it clear that:
1 - Wuhan's health care system is overwhelmed
2 - There's not enough transportation, test kits, masks, and hospital beds, or volunteers
3 - Many sick people are not even bothering to go to the hospital
4 - There's poor communication and rumors flying around
5 - People are frightened, panicking, and suspecting the worst
This tells me that:
A - there are likely way more people infected than there are confirmed cases, but possibly more deaths too of those who never made it in to hospitals
B - Many wouldn't have died had they had more adequate health care, better transportation and more test kits
So, for the rest of us who are sitting on our hands now, glued to social media or the television waiting to see how this will unfold, our time would be much more productively spent planning for when the outbreak hits our local area.
Volunteer. Get connected with volunteer organizations. Donate. See what you can do to ensure there's adequate transportation, communication and resources when the outbreak hits your area.
One thing I'm really curious about that I haven't heard covered yet is if people who get sick and recover become immune. If so, they should feel safe in volunteering to come in contact with the sick and help them directly after they've recovered themselves.
Cooperation, preparation, organization, and mutual aid are crucial.
The reporter, Chen Qiushi, describes his observations in Wuhan, a city of more than 10 million.
His preamble:
"My name has been flagged in China."
"If the content contains 'Chenqiushi' or 'CQS', or my face, it will not be sent on Wechat. ... if you [share on wechat], your wechat account will be deleted, like mine.""
He describes visits he made to hospitals in Wuhan and the general state in the city.
It is well worth listening to / reading.
Some points that stuck with me:
People cannot get to hospital because there is a critical lack of transportation.
There is a critical lack of test kits, so residents do not believe they will be diagnosed, so they stay home.
The original (not translated) is here: https://www.youtube.com/watch?v=iXozpbomAns
(thanks Roritharr)
How far does the censoring actually go?
That said you aren't going to be blacklisted for a single comment on HN. That sounds like the kind of thing the US would do.
[1] http://www.ddl.ish-lyon.cnrs.fr/fulltext/pellegrino/Pellegri...
Source: https://www.who.int/csr/sars/press2003_04_01/en/ (search for "deaths")
On the flip side, the R0 (rate of transmission) and death rate might be a good clip lower than currently estimated. On the other hand, China walled off a city but part of their motivation might have been the flack they got for moving slowly with SARS.
I wouldn't even go that far. I've been using this as an excuse to figure out the D3 v5 API using the Johns Hopkins data. Most provinces outside of Hubei are not reporting deaths yet. It's possible nobody's died outside of Hubei, but that seems suspect to me. There is almost certainly strong federal and local pressure to under report deaths, but this sort of thing is much harder to hide in Hubei because it's the epicenter.
I don't believe for a moment that China would've attempted to quarantine 60 million people so quickly if the case fatality rate were only 2%. 2% is bad but SARS saw around 15% in many countries and things weren't locked down this tightly.
More to the point, Hubei is reporting 204 deaths and 5,806 confirmed cases which works out to about 3.5%. This is compared to 76 deaths and 1,423 confirmed three days ago (or 5%). If you'd like to look at death compared to known outcomes you're looking at about 64% of the outcomes being death (204 deaths, 116 recoveries). It's not clear which part of the equation is lagging more in Hubei.
presumably fatality is only one of many factors here. 15% of 100 infections is a different beast than 2% of 1M. And if it takes up to 14 days to see symptoms...
There were roughly 8,000 SARS infections and currently about 10,000 nCoV infections so the comparisons aren't quite as absurd.
As she said, we will only know once the thing is over.
Assuming the average time from symptom onset and diagnosis to death is 7 days, we're looking at at 20% death rate (830 confirmed infected 1 week ago). Even a 5 day lag between symptom onset to death is a ~9% death rate (1,975 confirmed infected 5 days ago).
This is exactly how the fatality rate of SARS played out.
Do you have evidence of that in this case?
Viruses vary widely on how many are asymptomatic. My understanding is that having people be infectious and asymptomatic only happens with diseases that are well-adapted to their hosts. Which this one, having recently crossed a species barrier, isn't. (Its fatality rate is also high for the same reason.)
However that is a general understanding and I don't have data to base it on on this case. Do you?
If they in fact can't transmit, then this is OK. If they can or, even worse, have a long latency period and will show symptoms in 2 weeks, that is very, very scary.
Our best tool for diseases like this is contact tracing. And asymptomatic carriers make that very hard.
(Useless trivia, the first documented asymptomatic carrier who was infectious was a short order cook named Mary Mallon. She is better known as Typhoid Mary.)
When she was first identified, she cooked for a number of families. The outbreak that got her put away for life was due to working as a cook at Sloane Hospital for Women.
I cannot immediately find record of her being a short order cook specifically. However that is my recollection from https://www.amazon.com/Betrayal-Trust-Collapse-Global-Public...
- how many infected but not confirmed. They could be asymptotic or mild enough not to seek medical treatment. This would increase the denominator.
- time between infection to first symptom to death. Therefore we don’t know which way the remaining confirmed cases will go. Probably increase the numerator over time but don’t know by how much.
- unclear how accurate the reported numbers are.
We don't know how many people are infected. We only have numbers of confirmed cases and those numbers are heavily skewed because 1) people don't know they are sick 2) stay at home or 3) are not diagnosed properly. Those diagnosed in China are probably severe cases with a multiple not being diagnosed. Also, it is unclear how good the reporting is.
We don't know how many of those who are infected will die and how many will recover. We only know of deaths of confirmed patients in the hospital. Of roughly 10000 confirmed cases 200 are dead, 200 are recovered and 9600 are yet to be determined. From that you could deduce 2% or 50%, less than 2% or more than 50% or anything else. Right now we don't have good data. Also we don't know how long it takes to die or to recover and on most patients we will probably lose track.
Since the infection takes about 2 weeks, we have to wait a few weeks until the smoke starts clearing.
100%
Streets are deserted. The few that go out all wear a mask. Restaurants, museums, cafes, bars have been demanded shut across the country, ostensibly until the end of the weekend but I can see this being extended. The first working day after the Chinese New Year was supposed to be February 3rd, but the city I'm in have extended this to February 9th - offices have been told not to open. Shops are open, there is food, and new fresh vegetables, fruits, meats are being stocked.
Long answer: wait a week or two.
Disclosure: no I'm not an epidemiologist. But for a reference to a paper by actual epidemiologists see https://pdfs.semanticscholar.org/ebf2/48c9fc0a1a23d1778b9408... section Simple Estimators, specifically this formula:
e₂(s)=D(s)/{D(s)+R(s)} which is: deaths / (deaths + recoveries)
The paper concludes: "The second simple estimate based on the ratio of deaths of those for whom the outcome is known, e₂, is reasonable at most points in the epidemic" ie. produces a good estimate of the eventual observed case fatality rate (in fact in their example it slightly underestimates the actual case fatality rate)
still can't believe them.
I suppose one way to reduce uncertainty is to examine a cohort of patients and follow it meticulously. To do that, we can look at the 99-patient case study published in The Lancet yesterday: https://www.thelancet.com/journals/lancet/article/PIIS0140-6... 11 died, 31 were discharged, and 57 remain in the hospital. This suggests a CFR of 11/(11+31) = 26% The assumption epidemiologists make when they use this formula is that the 57 still in the hospital have the same chance of dying as those who already died in the hospital.
Another way of looking at probabilities, out of the 57 patients left in the hospital:
If 0 die (ie. all recover), the CFR is 11% (11 deads, 88 recovered)
If 15 die (26% of 57 still hospitalized), the CFR is 26% (11+15=26 deads, 73 recovered)
If 57 die, the CFR is 69% (11+57=68 deads, 31 recovered)
So the CFR bounds are 11-69% and if the trend on remaining patients continue it should be 26%.
Only 7% of hospitalized flu cases died in 2018-2019 (34 157 out of 490,561): https://www.cdc.gov/flu/about/burden/index.html The coronavirus would thus appear to be 4 times more deadly (26%.)
In other places that are better prepared and which have more resources the outcomes will likely be better, in worse prepared places with fewer resources the outcomes will likely be worse.
Let's keep that in mind before we extrapolate from Wuhan to the rest of the world.
I doubt this. WHile this may be true for a known disease, we have to ask, how much can the hospital do in this cases? It is a little bit like HIV in the beginning. Watch them die?
Interestingly, China is trying HIV medications on the infected.
For more info on ARDS and treatment in the context of the current pandemic, see this informative explanation: https://www.youtube.com/watch?v=okg7uq_HrhQ
This is a very straightforward application of survival analysis, and those still in the hospital are "censored" observations - we know their outcome takes place in the future, but we're not sure when.
There are methods for calculating things like CFR in the presence of censoring, which will change based on what type of model you're using.