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Josh Marshall makes the same point I do about how the fatality numbers in NY make the Santa Clara and LA studies implausible.
Much of the news coverage of the Stanford serology studies has focused on how many more infections they seem to show than the official lab confirmed numbers – ranging from 50 to 90 times the number in the LA County study. But these studies also speak directly to how lethal the disease is. They suggest that the actual death rate is just over .1%.
The problem with this estimate is that, as I explained here, the actual mortality data out of New York City seems to make that estimate all but impossible. As of two days ago, the COVID19 mortality rate in New York City for the entire population was between .11% and .16%, depending on whether you count only lab confirmed COVID19 fatalities or those diagnosed on the basis of symptoms alone. To put that differently, for something in the range of Bhattacharya’s IFR to be accurate, literally the entire population of New York City would have to have been infected already.
The numbers are straightforward: as of two days ago, there were 9,101 lab confirmed cases and 4,582 presumptive diagnosed cases for a total of 13,683 fatalities In New York City. The population of New York City is 8,398,748. That comes to either .11% or .16% depending on which death toll number is used.
I do not think anyone thinks 100% exposure is at all possible. Even if we assume what I think most experts would consider the highly unlikely possibility that 50% of New Yorkers have been infected with COVID19 that would mean a .33% IFR. To be generous, let’s say a third of the population of New York City had already been infected with COVID19 – very high but not inconceivable. That would mean a IFR of .49%.
Needless to say, I’m no epidemiologist and I’m no statistician. I can’t tell you what the actual infection fatality rate is. But the actual death toll from New York City appears to place a hard lower bound on the numbers that is significantly higher than what the Stanford group’s serology studies suggest.
The problem with this estimate is that, as I explained here, the actual mortality data out of New York City seems to make that estimate all but impossible. As of two days ago, the COVID19 mortality rate in New York City for the entire population was between .11% and .16%, depending on whether you count only lab confirmed COVID19 fatalities or those diagnosed on the basis of symptoms alone. To put that differently, for something in the range of Bhattacharya’s IFR to be accurate, literally the entire population of New York City would have to have been infected already.
The numbers are straightforward: as of two days ago, there were 9,101 lab confirmed cases and 4,582 presumptive diagnosed cases for a total of 13,683 fatalities In New York City. The population of New York City is 8,398,748. That comes to either .11% or .16% depending on which death toll number is used.
I do not think anyone thinks 100% exposure is at all possible. Even if we assume what I think most experts would consider the highly unlikely possibility that 50% of New Yorkers have been infected with COVID19 that would mean a .33% IFR. To be generous, let’s say a third of the population of New York City had already been infected with COVID19 – very high but not inconceivable. That would mean a IFR of .49%.
Needless to say, I’m no epidemiologist and I’m no statistician. I can’t tell you what the actual infection fatality rate is. But the actual death toll from New York City appears to place a hard lower bound on the numbers that is significantly higher than what the Stanford group’s serology studies suggest.
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