I’m sorry but this simply isn’t possible. The Diamond Princess cruise ship data alone proves it.
The Diamond Princess had a total of 3,711 people on board. By the end of its odyssey, a total of 712 of them tested positive, about a fifth. This population was observed in great detail, and puts severe limits on the fraction of people who have various outcomes. 10 people on this ship have died, and ~45 more were in critical condition at some point. If we take 712 as the true number of infections, we get a 1.4% death rate and 7.7% winding up critical or dead. The population was skewed elderly though which worsens the numbers somewhat, but that can’t change much more than a factor of two or three at the outside I think compared to a regular population. Thus an expected regular population’s death rate would be 0.5% to 1%.
20% of these people never had symptoms. Other data from other sources in China and Korea suggests the true number of asymptomatics could be above 30%, and Iceland is suggesting 50% but a lot of those people have not had followups so it could decrease. It is possible that more people on the cruise ship were infected but never tested positive, but it’s probably not huge compared to the positive tests.
The most extreme we could go is assuming that 100% of the ship was infected and four fifths of them were missed. This did not happen. But it’s an absolute upper bound. Then we get a 1.4% critical condition number and about a 0.3% death rate. Hospitalization would be higher. The parameters needed to have more than one or two percent of the British population have been exposed to the virus by now given reported deaths and hospitalizations require parameters for the fraction of people vulnerable to severe disease to be much lower than any plausible numbers here. Even with this extremely optimistic interpretation, you would’ve expected more than a full heavy flu season’s deaths squeezed into the last 2 months.
There IS a morbid case for it being relatively widespread in the North of Italy. The total excess mortality noted in several northern Italian cities is ~3x the official COVID death figures, indicating that a lot of people are dying without test results and without being noted down. That indicates ~30,000 total deaths in Italy. If we assume a 1% death rate for a population less skewed than a cruise ship, and a delay from infection to death this would indicate significantly upwards of three million Italians infected in the Northern provinces, which could be well over 10% of the badly affected provinces.
Median age on DM is 62 (basically, 50 per cent above 62). Most of the deaths were in people above 70.
In 2017, about 16 percent of the American population was 65 years old or over.
So, any DM mortality should be divided on 3 to get US mortality, given medical care will be available. If it will not be available, almost all critical care patients will die.
45 passengers of DM who were critical is 1.2 per cent of all 3700 DM passengers (I take all passengers’ number, not only infected ones, as it gives some estimation of the attack rate, that is the proportion of infected to those who escape infection, either via natural immunity or self-isolation. In US there will be many people, who will escape infection, via strong immunity, isolation, luck or very short asymptomatic illness—so short that it can’t be find via PCR).
Divided on 3, it gives 0.4 per cent of US population will die, or around 1.3 million people.
By the end of its odyssey, a total of 712 of them tested positive, about a fifth.
Perhaps other on the ship had already cleared the virus and were asymptomatic. PCR only works for a week. Also there might have been false negatives. I disagree that the age and comorbidity structure can only lead to skewed results by a factor of two or three, because this assumes that there are few asymptomatic infections (I’m arguing here that the age tables are wrong).
In my post, I’ve argued why the data out of China might be wrong.
Iceland’s data might be wrong because it is based on PCR not serology, which means that many people might have already cleared the infection, and it is also not random.
The DP data is commonly misunderstood. Influenza and COVID-19 (probably) both have a strongly age dependent IFR curve. The “COVID-19 is similar to influenza” model predicts IFR in the 1% range for a retiree age distribution like on DP but 0.1% range on the US age distribution. To a first approximation almost all the deaths are in the 65+ age groups, which are a small fraction of US population but about 50% of DP—it was a geriatric cruise.
So the DP is fairly strong evidence for influenza like mortality. I have an analysis here with more details, and this post by Nic Lewis has a more detailed analysis which considers a few more factors.
The “COVID-19 is similar to influenza” model predicts IFR in the 1% range for a retiree age distribution like on DP but 0.1% range on the US age distribution.
FWIW I tried to do an age adjustment for the Diamond Princess myself and what I got was that the 1.4% IFR for the cruise demographics translates into a 0.3% IFR for US demographics (factoring out gender adjustments). I think you could argue that because women were underrepresented on the cruise ship, the adjustment should be greater, so 0.25% is plausible. That said, this doesn’t yet factor in that the people who are medically worst off probably don’t book cruises, so my best-estimate adjustment is maybe 0.4% with a lot of uncertainty. I agree that the people who use the Diamond Princess as evidence for an IFR around 0.9% or higher seem to be making a mistake. At the same time, I do think the Diamond Princess is at least weak to moderate evidence against the 0.125% figure Ioannidis arrived at, or the 0.1% figure that I’ve seen discussed elsewhere.
I don’t really know how this compares to flu mortality, but I found myself somewhat skeptical about the claim I quoted above. You seem to get a 10x update for your age adjustment, whereas my update was only about 5.7x (before factoring in harder-to-quantify assumptions that IMO reduce the factor a bit more even).
(I made a huge mess of my calculations and I don’t recommend clicking on the following link, but just so people see that I’m not just making this up, here’s some evidence that I did something with numbers. Could also be that I neglected some considerations. For factoring in how much overrepresentation of age bracket 70-79 changes things, I based the adjustment off of previous estimates on how strongly Covid19′s IFR is age skewed. I’d imagine that this adjustment was uncontroversial because whether you subscribe to the low IFR theory or not, probably there’s no reason to question whether the proportionalities of the attack rate are correctly reported?)
For a really rough analysis, the overall IFR on the DP was probably about 1% (10 deaths / 1000 infections) after adjusting slightly for false negatives / missed tests.
All those deaths are 70+ age with an in IFR in that group ~2%. About 10% of the US population is in the 70+ bracket, so the projected IFR is ~0.2%. However about half the deaths were in the 80+ age bracket, and if you do a more fine grained binning it’s probably more like 0.15%, but it’s not a high precision estimate.
I’m sorry but this simply isn’t possible. The Diamond Princess cruise ship data alone proves it.
The Diamond Princess had a total of 3,711 people on board. By the end of its odyssey, a total of 712 of them tested positive, about a fifth. This population was observed in great detail, and puts severe limits on the fraction of people who have various outcomes. 10 people on this ship have died, and ~45 more were in critical condition at some point. If we take 712 as the true number of infections, we get a 1.4% death rate and 7.7% winding up critical or dead. The population was skewed elderly though which worsens the numbers somewhat, but that can’t change much more than a factor of two or three at the outside I think compared to a regular population. Thus an expected regular population’s death rate would be 0.5% to 1%.
20% of these people never had symptoms. Other data from other sources in China and Korea suggests the true number of asymptomatics could be above 30%, and Iceland is suggesting 50% but a lot of those people have not had followups so it could decrease. It is possible that more people on the cruise ship were infected but never tested positive, but it’s probably not huge compared to the positive tests.
The most extreme we could go is assuming that 100% of the ship was infected and four fifths of them were missed. This did not happen. But it’s an absolute upper bound. Then we get a 1.4% critical condition number and about a 0.3% death rate. Hospitalization would be higher. The parameters needed to have more than one or two percent of the British population have been exposed to the virus by now given reported deaths and hospitalizations require parameters for the fraction of people vulnerable to severe disease to be much lower than any plausible numbers here. Even with this extremely optimistic interpretation, you would’ve expected more than a full heavy flu season’s deaths squeezed into the last 2 months.
I am compelled to point to a twitter thread from Professor Bergstrom ( https://twitter.com/CT_Bergstrom/status/1242611599405277184 )
There IS a morbid case for it being relatively widespread in the North of Italy. The total excess mortality noted in several northern Italian cities is ~3x the official COVID death figures, indicating that a lot of people are dying without test results and without being noted down. That indicates ~30,000 total deaths in Italy. If we assume a 1% death rate for a population less skewed than a cruise ship, and a delay from infection to death this would indicate significantly upwards of three million Italians infected in the Northern provinces, which could be well over 10% of the badly affected provinces.
Median age on DM is 62 (basically, 50 per cent above 62). Most of the deaths were in people above 70.
In 2017, about 16 percent of the American population was 65 years old or over.
So, any DM mortality should be divided on 3 to get US mortality, given medical care will be available. If it will not be available, almost all critical care patients will die.
45 passengers of DM who were critical is 1.2 per cent of all 3700 DM passengers (I take all passengers’ number, not only infected ones, as it gives some estimation of the attack rate, that is the proportion of infected to those who escape infection, either via natural immunity or self-isolation. In US there will be many people, who will escape infection, via strong immunity, isolation, luck or very short asymptomatic illness—so short that it can’t be find via PCR).
Divided on 3, it gives 0.4 per cent of US population will die, or around 1.3 million people.
Cruise Ship passenger are a non random sample with perhaps higher co-morbidities.
The cruise ships analysed are non-random sample: “at least 25 other cruise ships have confirmed COVID-19 cases”
Being on a cruise ship might increase your risk because of dose response https://twitter.com/robinhanson/status/1242655704663691264
Onboard IFR. as 1.2% (0.38-2.7%) https://www.medrxiv.org/content/10.1101/2020.03.05.20031773v2
Ioannidis: “A whole country is not a ship.”
Perhaps other on the ship had already cleared the virus and were asymptomatic. PCR only works for a week. Also there might have been false negatives. I disagree that the age and comorbidity structure can only lead to skewed results by a factor of two or three, because this assumes that there are few asymptomatic infections (I’m arguing here that the age tables are wrong).
In my post, I’ve argued why the data out of China might be wrong.
Iceland’s data might be wrong because it is based on PCR not serology, which means that many people might have already cleared the infection, and it is also not random.
That’s the Grand Princess, not the Diamond Princess.
Cheers- corrected.
The DP data is commonly misunderstood. Influenza and COVID-19 (probably) both have a strongly age dependent IFR curve. The “COVID-19 is similar to influenza” model predicts IFR in the 1% range for a retiree age distribution like on DP but 0.1% range on the US age distribution. To a first approximation almost all the deaths are in the 65+ age groups, which are a small fraction of US population but about 50% of DP—it was a geriatric cruise.
So the DP is fairly strong evidence for influenza like mortality. I have an analysis here with more details, and this post by Nic Lewis has a more detailed analysis which considers a few more factors.
FWIW I tried to do an age adjustment for the Diamond Princess myself and what I got was that the 1.4% IFR for the cruise demographics translates into a 0.3% IFR for US demographics (factoring out gender adjustments). I think you could argue that because women were underrepresented on the cruise ship, the adjustment should be greater, so 0.25% is plausible. That said, this doesn’t yet factor in that the people who are medically worst off probably don’t book cruises, so my best-estimate adjustment is maybe 0.4% with a lot of uncertainty. I agree that the people who use the Diamond Princess as evidence for an IFR around 0.9% or higher seem to be making a mistake. At the same time, I do think the Diamond Princess is at least weak to moderate evidence against the 0.125% figure Ioannidis arrived at, or the 0.1% figure that I’ve seen discussed elsewhere.
I don’t really know how this compares to flu mortality, but I found myself somewhat skeptical about the claim I quoted above. You seem to get a 10x update for your age adjustment, whereas my update was only about 5.7x (before factoring in harder-to-quantify assumptions that IMO reduce the factor a bit more even).
(I made a huge mess of my calculations and I don’t recommend clicking on the following link, but just so people see that I’m not just making this up, here’s some evidence that I did something with numbers. Could also be that I neglected some considerations. For factoring in how much overrepresentation of age bracket 70-79 changes things, I based the adjustment off of previous estimates on how strongly Covid19′s IFR is age skewed. I’d imagine that this adjustment was uncontroversial because whether you subscribe to the low IFR theory or not, probably there’s no reason to question whether the proportionalities of the attack rate are correctly reported?)
For a really rough analysis, the overall IFR on the DP was probably about 1% (10 deaths / 1000 infections) after adjusting slightly for false negatives / missed tests.
All those deaths are 70+ age with an in IFR in that group ~2%. About 10% of the US population is in the 70+ bracket, so the projected IFR is ~0.2%. However about half the deaths were in the 80+ age bracket, and if you do a more fine grained binning it’s probably more like 0.15%, but it’s not a high precision estimate.
Very good analysis.
I also thought your recent blog was excellent and think you should make it a top level post:
https://entersingularity.wordpress.com/2020/03/23/covid-19-vs-influenza/