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Estimating clinical severity of COVID-19 from the transmission dynamics in Wuhan, China

Joseph T. Wu, Kathy Leung, Mary Bushman

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Nishant Kishore, Rene Niehus, Pablo M. de Salazar, Benjamin J. Cowling, Marc Lipsitch, Gabriel M. Leung

2020 · Nature Medicine

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Original HN comments, with labels from simple text rules. A label describes the whole comment and may miss context or irony. Read the discussion to make up your own mind. About the labels

7 selected excerpts · 7 total mentions

random314
Neutral mention · rule
Yes, the IFR has been consistently estimated at 0.4 to 0.7 since February 2020. 0.5% of 8B world population works out to 160M excess deaths. This calculation assumes availability of medical facilities at 100% with no dead doctors or nurses. I don't think our public facilities can handle so many excess dead bodies unless we let some float down the river. https://www.google.com/search?q=india+covid+19+floating+bodi... March 2020 - IFR estimate in China 0.6%, CFR in China estimated as 1.2% https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7118348/ "Adjusting for delay from confirmation to death, we estimated case and infection fatality ratios (CFR, IFR) for coronavirus disease…
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(COVID-19) on the Diamond Princess ship as 2.6% (95% confidence interval (CI): 0.89–6.7) and 1.3% (95% CI: 0.38–3.6), respectively. Comparing deaths on board with expected deaths based on naive CFR estimates from China, we estimated CFR and IFR in China to be 1.2% (95% CI: 0.3–2.7) and 0.6% (95% CI: 0.2–1.3), respectively." March 2020 - Symptomatic case fatality risk 1.4% https://www.nature.com/articles/s41591-020-0822-7 "Using public and published information, we estimate that the overall symptomatic case fatality risk (the probability of dying after developing symptoms) of COVID-19 in Wuhan was 1.4% (0.9–2.1%), which is substantially lower than both the corresponding crude or naïve confirmed case fatality risk"
zucker42
Neutral mention · rule
The princess cruise ship study also gave an IFR (for China) of 0.5%, and an early epidemiological modeling study put the symptomatic CFR at 1.4% which would imply 0.7% IFR assuming it's 50% symptomatic. https://www.nature.com/articles/s41591-020-0822-7 https://www.medrxiv.org/content/10.1101/2020.03.05.20031773v... 0.5% to 1% has been the most plausible for at least a month, and this NYC study seems to exactly line up with that.
nodamage
Neutral mention · rule
A few thoughts: 1) Extrapolating from the infection rates of very specific groups (for example, evacuees) to the entire population without taking into account transmission dynamics and the time between infection and detection does not make very much sense. The authors naively multiply the infection rate among evacuees by the population of Wuhan to conclude that Wuhan must have had 178,000 infections at the end of January. By comparison, epidemiological models have estimated there were around ~20,000 infections at that time [1][2][3]. What conclusion should we draw here? If you use sloppy, back of the napkin math to over-inflate the infection count by 10x then you can…
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correspondingly deflate the mortality rate? 2) Speculating about the mortality rate of Covid-19 based on several gigantic assumptions ("If our surmise of six million cases is accurate, that’s a mortality rate of 0.01%") seems borderline irresponsible. Numerous researchers have been modeling this virus and have generally arrived at numbers in the range of 0.5% to 1.6% [4][5][6][7][8][9]. The authors don't present any compelling reason why we should doubt those numbers. 3) Ultimately the mortality rate is not as important a number as the hospitalization rate. The authors would have you believe this virus is no worse than the flu, but this is not congruent with the number of reports coming out of places like Italy and New York saying they're about to run out of ICU beds, or China rushing to build temporary hospitals to house all of the patients that need critical care. What the mortality rate might be under ideal circumstances where every patient receives adequate medical care might be significantly different compared to a scenario where you've run out of ICU beds and have to start rationing ventilators. [1] https://www.mdpi.com/2077-0383/9/2/419/htm [2] https://www.medrxiv.org/content/10.1101/2020.01.23.20018549v... [3] https://www.mdpi.com/2077-0383/9/2/523/htm [4] https://www.imperial.ac.uk/media/imperial-college/medicine/s... [5] https://institutefordiseasemodeling.github.io/nCoV-public/an... [6] https://cmmid.github.io/topics/covid19/severity/diamond_crui... [7] https://www.medrxiv.org/content/10.1101/2020.03.04.20031104v... [8] https://www.medrxiv.org/content/10.1101/2020.03.09.20033357v... [9] https://www.nature.com/articles/s41591-020-0822-7
jMyles
Neutral mention · rule
To the degree that the WHO was wildly irresponsible - and I'm not I'm ready to apply the "wildly" part, it was publishing the terrifying 3.4% CFR when there was no basis for caluculating a denominator at that time. Even though they've been called out on that by one of the world's foremost experts in the area of research reliability [0], and even though every subsequent study [1] [2] [3] [4] has shown the CFR to be far lower, the extreme measures based on this being a once-in-a-century coronavirus are not only still in place, but being expanded as if that number is still reality. 0: https://www.reddit.com/r/PrepareInsteadOfPanic/comments/fl08... 1: https://www.cebm.net/global-covid-19-case-fatality-rates/ 2: https://www.nature.com/articles/s41591-020-0822-7 3: https://sci-hub.tw/https://doi.org/10.1136/bmj.m1113 4: https://www.sciencedirect.com/science/article/pii/S092485792...
spikels
Neutral mention · rule
Not data analysis, just weakly argued opinion. Author even accuses “Germany’s virologists” of “lying”. While this seems like pessimistic bias I think much of the confusion about mortality rates stems from the multiple definitions. Is the denominator infected, symptomatic or hospitalized? These three estimates - still very uncertain today - will vary drastically. Here’s some actual data analysis on this subject: https://www.nature.com/articles/s41591-020-0822-7
609venezia
Neutral mention · rule
I think Ioannidis included that very low number as an example of how ridiculous the statistics can look when using the Diamond Princess as a sample and factoring in the relevant sources of uncertainty. <<Projecting the Diamond Princess mortality rate onto the age structure of the U.S. population, the death rate among people infected with Covid-19 would be 0.125%. But since this estimate is based on extremely thin data — there were just seven deaths among the 700 infected passengers and crew — the real death rate could stretch from five times lower (0.025%) to five times higher (0.625%). It is also possible that some of the passengers who were infected might die later, and…
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that tourists may have different frequencies of chronic diseases — a risk factor for worse outcomes with SARS-CoV-2 infection — than the general population. Adding these extra sources of uncertainty, reasonable estimates for the case fatality ratio in the general U.S. population vary from 0.05% to 1%.>> Mainly I think he wants more testing, but people are cherry picking his argument to try to downplay the risk. His key point from the overall piece is something like "we need more testing, including randomly sampled data. Let's not give up on testing while we ratchet up the countermeasures." Evidence: Second graph- <<At a time when everyone needs better information, from disease modelers and governments to people quarantined or just social distancing, we lack reliable evidence on how many people have been infected with SARS-CoV-2 or who continue to become infected. Better information is needed to guide decisions and actions of monumental significance and to monitor their impact.>> in the middle- <<The most valuable piece of information for answering those questions would be to know the current prevalence of the infection in a random sample of a population and to repeat this exercise at regular time intervals to estimate the incidence of new infections. Sadly, that’s information we don’t have.>> concluding graph- <<If we decide to jump off the cliff, we need some data to inform us about the rationale of such an action and the chances of landing somewhere safe.>> --- Coming from a different angle, the latest estimate from Wuhan is 1.4% (.9-2.1) https://www.nature.com/articles/s41591-020-0822-7?mod=articl...
jacobolus
Neutral mention · rule
Keep in mind, the number you are talking about is known deaths / known cases. Neither of these is a final or accurate number: many of the current cases will progress to death, and many who have been (or are) infected have not been tested (e.g. because they were asymptomatic or had only minor symptoms). Here’s a more careful attempt to determine the numbers for Wuhan (published today) which results in numbers substantially lower (though still scary) than those suggested by the WHO previously https://www.nature.com/articles/s41591-020-0822-7

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