If the IFR is indeed .003% (the upper end of your range), then assuming the worst case scenario that 100% of the population of the UK gets infected eventually, only .003%*66.4 million = approx 2000 people will die total.
Would you consider the theory falsified if the death toll in the UK surpasses 2000?
No. My ambition here was a bit simpler. I have presented a rough qualitative argument here that infection is already widespread and only a toy model. There are some issues with this and I haven’t done formal modelling. For instance, this would be what would be called the “crude IFR” I think , but the time lag adjusted IFR (~30 days from infection to death) might increase the death toll.
Currently, also every death in Italy where coronavirus is detected is recorded as a C19 death.
FWIW, if UK death toll will surpass 10,000, then this wouldn’t fit very well with this hypothesis here.
FWIW, if UK death toll will surpass 10,000, then this wouldn’t fit very well with this hypothesis here.
If this update works then I feel like just looking at how the numbers in Italy came together would change your mind about the low-IFR hypothesis.
Alternatively, if the Covid-19 deaths in NY state go above 3,333 in the first week of April, that seems like it would also falsify the hypothesis. (NY state has fewer than one third the population of the UK.) Unfortunately I think this is >80% to happen.
Alternatively, if the Covid-19 deaths in NY state go above 3,333 in the first week of April, that seems like it would also falsify the hypothesis. (NY state has fewer than one third the population of the UK.) Unfortunately I think this is >80% to happen.
On April 4, the death toll in NY state surpassed 3,333. As of April 10, there are 7,844 deaths.
The death rate data coming in seems to be converging on a 0.5% to 0.7% death per infection rate. Multiple sources have estimated that weeks ago based on age-normalizing the Diamond Princess, and on testing evacuees from Wuhan.
Two serology surveys have now happened in Europe. One was in a hard-hit town in Germany, and one was in a hard-hit town in Italy at the epicenter of its outbreak. In both places, they got approximately a 15% seropositive rate. In Germany, we only have information on deaths with positive test rates and it comes to 0.35%. In Italy, total excess deaths over this time last year are about 2.5x the confirmed positive deaths and account for 0.1% of the population, giving an infection fatality rate of 0.7%. It is easy to imagine that some deaths did not get positive tests in Germany which along with a less-old population could make up for the difference.
From this, I estimate that at least 10% and possibly up to 20% of New York City has been infected, given the delay between infections and deaths. (100*8000 = 800,000, out of about 8 million)
One point of criticism is that the renowned German experts who were asked to comment on the study say they are skeptical about the antibody tests. They argue that to their knowledge, the only antibody tests widely in use in Germany at the time of the study can’t distinguish between SARS-CoV-2 and other coronaviruses responsible for a third of common colds. Because we are 1 month past the peak of cold season, they argue that the 15% could be largely picking up on false positives for SARS-CoV-2.
Given a 0.3% current acute infection rate and some epidemiological modeling they estimate 1% of their total population has been infected, with a death rate of 0.77%.
Yup. 0.77% is also what I keep stumbling upon when I look into various data points about the IFR! It’s my best guess about where Iceland’s IFR will end up, and very close to my best guess for proper age adjustment for the Diamond Princess.
Hardly an unbiased sample, but of 200+ pregnant women coming into a hospital to give birth that were blanket-tested, 15.3% tested positive.
Of this set of positive tests, only 12% of them were symptomatic on admission, and a further 10% developed symptoms over the course of their 2-day-long stays bringing it to a total of 22% symptomatic upon discharge or transfer. Presumably already-symptomatic women were more likely to be in the hospital already.
Doing a little armchair epidemiology. Let’s assume that half of the deaths of currently infected people have happened, due to the lockdown extending the doubling time from three days to more than a week. We get:
~8000 deaths * 2 / (15.3% of 8 million) = 1.3% infection to mortality rate.
If we assume that there were more symptomatic women who didn’t show up to normal birthing due to going to the hospital for COVID symptoms, we get a lower death rate. If 20% of the total population is infected, we get a 1% mortality rate. Could go lower if the doubling time has slowed less than my assumption, or if people who have recovered constitute a large enough actual segment of the population. Probably can’t account for more than a factor of two though, given known recovery times.
Compare this to what I wrote 21 hours ago, based on serology data from Italy and Germany:
‘From this, I estimate that at least 10% and possibly up to 20% of New York City has been infected, given the delay between infections and deaths. (100*8000 = 800,000, out of about 8 million) ’
I think what ignoranceprior was originally asking was, given all the information you know, what is your best estimate of the infection fatality rate? Best estimate in this case implies adjusting for ways that some research can be wrong, and taking into account the rebuttals you’ve read here.
If the IFR is indeed .003% (the upper end of your range), then assuming the worst case scenario that 100% of the population of the UK gets infected eventually, only .003%*66.4 million = approx 2000 people will die total.
Would you consider the theory falsified if the death toll in the UK surpasses 2000?
No. My ambition here was a bit simpler. I have presented a rough qualitative argument here that infection is already widespread and only a toy model. There are some issues with this and I haven’t done formal modelling. For instance, this would be what would be called the “crude IFR” I think , but the time lag adjusted IFR (~30 days from infection to death) might increase the death toll.
Currently, also every death in Italy where coronavirus is detected is recorded as a C19 death.
FWIW, if UK death toll will surpass 10,000, then this wouldn’t fit very well with this hypothesis here.
The UK death toll currently stands at 10,612 according to:
https://www.worldometers.info/coronavirus/country/uk/
Boy there was a lot of desperate motivated cogniton around a few weeks ago...
@Hauke Hillebrandt
If this update works then I feel like just looking at how the numbers in Italy came together would change your mind about the low-IFR hypothesis.
Alternatively, if the Covid-19 deaths in NY state go above 3,333 in the first week of April, that seems like it would also falsify the hypothesis. (NY state has fewer than one third the population of the UK.) Unfortunately I think this is >80% to happen.
On April 4, the death toll in NY state surpassed 3,333. As of April 10, there are 7,844 deaths.
The death rate data coming in seems to be converging on a 0.5% to 0.7% death per infection rate. Multiple sources have estimated that weeks ago based on age-normalizing the Diamond Princess, and on testing evacuees from Wuhan.
Two serology surveys have now happened in Europe. One was in a hard-hit town in Germany, and one was in a hard-hit town in Italy at the epicenter of its outbreak. In both places, they got approximately a 15% seropositive rate. In Germany, we only have information on deaths with positive test rates and it comes to 0.35%. In Italy, total excess deaths over this time last year are about 2.5x the confirmed positive deaths and account for 0.1% of the population, giving an infection fatality rate of 0.7%. It is easy to imagine that some deaths did not get positive tests in Germany which along with a less-old population could make up for the difference.
From this, I estimate that at least 10% and possibly up to 20% of New York City has been infected, given the delay between infections and deaths. (100*8000 = 800,000, out of about 8 million)
It’s worth noting that the German serology study (it was in the town Gangelt) has been criticized for being poorly presented: https://www.sueddeutsche.de/wissen/heinsberg-studie-herdenimmunitaet-kritik-1.4873480?fbclid=IwAR1mpGCPj21bffeXBe1fGJVeEWc7UlO2DkEP9-XrSCi4sJeh2-Ri_Cahwrw
One point of criticism is that the renowned German experts who were asked to comment on the study say they are skeptical about the antibody tests. They argue that to their knowledge, the only antibody tests widely in use in Germany at the time of the study can’t distinguish between SARS-CoV-2 and other coronaviruses responsible for a third of common colds. Because we are 1 month past the peak of cold season, they argue that the 15% could be largely picking up on false positives for SARS-CoV-2.
Some non-serology blanket RNA tests coming out of Austria.
https://www.theguardian.com/world/2020/apr/10/less-than-1-of-austria-infected-with-coronavirus-new-study-shows
Given a 0.3% current acute infection rate and some epidemiological modeling they estimate 1% of their total population has been infected, with a death rate of 0.77%.
Everything seems to be converging...
Yup. 0.77% is also what I keep stumbling upon when I look into various data points about the IFR! It’s my best guess about where Iceland’s IFR will end up, and very close to my best guess for proper age adjustment for the Diamond Princess.
New, amazing data from New York, as of April 13. https://www.nejm.org/doi/full/10.1056/NEJMc2009316
Hardly an unbiased sample, but of 200+ pregnant women coming into a hospital to give birth that were blanket-tested, 15.3% tested positive.
Of this set of positive tests, only 12% of them were symptomatic on admission, and a further 10% developed symptoms over the course of their 2-day-long stays bringing it to a total of 22% symptomatic upon discharge or transfer. Presumably already-symptomatic women were more likely to be in the hospital already.
Doing a little armchair epidemiology. Let’s assume that half of the deaths of currently infected people have happened, due to the lockdown extending the doubling time from three days to more than a week. We get:
~8000 deaths * 2 / (15.3% of 8 million) = 1.3% infection to mortality rate.
If we assume that there were more symptomatic women who didn’t show up to normal birthing due to going to the hospital for COVID symptoms, we get a lower death rate. If 20% of the total population is infected, we get a 1% mortality rate. Could go lower if the doubling time has slowed less than my assumption, or if people who have recovered constitute a large enough actual segment of the population. Probably can’t account for more than a factor of two though, given known recovery times.
Compare this to what I wrote 21 hours ago, based on serology data from Italy and Germany:
‘From this, I estimate that at least 10% and possibly up to 20% of New York City has been infected, given the delay between infections and deaths. (100*8000 = 800,000, out of about 8 million) ’
I think what ignoranceprior was originally asking was, given all the information you know, what is your best estimate of the infection fatality rate? Best estimate in this case implies adjusting for ways that some research can be wrong, and taking into account the rebuttals you’ve read here.
This is indeed what I meant. Also I was thinking about once-the-dust-settles IFR, not “crude IFR”.