See my other post here on the general phenomenon of denying that different people are different and behave differently and experience different outcomes in a way that is meaningful for what is likely to happen both to them and for everyone overall. I keep having to remind myself along with everyone else that this is not a straw man argument. It’s being used to argue for policies that have huge impacts on our lives.
I can’t comment on what doctors and random public health bureaucrats might have said, but as Owain Evans said earlier, the current state of modelling among the actual domain experts in modelling is nowhere near as bad as you suggest and it does take these effects into account.
I think that the heterogeneity you talk about is part of the reason that even the ‘worst case’ planning (at least in the UK) is suggesting partial herd immunity being reached with ~30% infected. This UK government report goes over a bunch of factors that might increase transmission and say that a ‘reasonable worst case’ scenario for herd immunity from a winter wave is R_t increasing to 1.7 in September and remaining constant, assuming effectively zero government action—total second wave deaths (and, approximately cases) are about double the first, which would mean a total infected of a bit less than 30% for herd immunity (A bit less than 10% infected so far + about double to come).
One of the most influential models is the “Imperial Model”, which certainly impacted UK policy and probably US and European policy too. Other countries did versions of the model. The lead researcher on the model literally became a household name in the UK. The Imperial Model is an agent-based model (not an SIR model). It has a very detailed representation of how exposure/contact differ among different age groups (work vs. school) and in regions with different population densities.
The lesson here may be that the public line about ‘there’s a fixed 70% herd immunity threshold’ is just that—a public line, and isn’t (and never was—if I remember rightly, the Imperial model from March estimated a herd immunity threshold of 40% without a lockdown) biasing the output of modelling. It could also be the case that doctors or generic public health people in the US are repeating the 70% line while epidemiologists and modellers with specific expertise (in the US and elsewhere) are being more methodical.
I searched herd immunity in the UK government report you referenced and found the following line
Serology studies suggest that ~5-10% of the UK population has been infected to date, with levels up to 15% in some areas, but infection levels of approximately 70% may be required to achieve herd immunity, bearing in mind that the degree to which immunity is conferred by past infection is still unknown (see section 3.1.2). (page 12)
That comment looks exaclty like the supposed strawman Zvi is putting up. Is there some reading between the lines explanation that contradicts their direct statement? And if there is, why would it matter more than their direct statement.
I generally do believe your point that modelers accept the broader evidence on immunity much more than public health officials and pundits.
It’s clearly the case that the public line about 70% herd immunity is still out there, but I think my broader point is served by that report. They have the obligatory ‘herd immunity is reached at 70% and there may be no immunity conferred’ caveat but then the actual model implies that in a worst case scenario 30% of the UK gets infected. You might speculate that they consulted the modellers for the model but not for the rest of it.
I can’t comment on what doctors and random public health bureaucrats might have said, but as Owain Evans said earlier, the current state of modelling among the actual domain experts in modelling is nowhere near as bad as you suggest and it does take these effects into account.
I think that the heterogeneity you talk about is part of the reason that even the ‘worst case’ planning (at least in the UK) is suggesting partial herd immunity being reached with ~30% infected. This UK government report goes over a bunch of factors that might increase transmission and say that a ‘reasonable worst case’ scenario for herd immunity from a winter wave is R_t increasing to 1.7 in September and remaining constant, assuming effectively zero government action—total second wave deaths (and, approximately cases) are about double the first, which would mean a total infected of a bit less than 30% for herd immunity (A bit less than 10% infected so far + about double to come).
The lesson here may be that the public line about ‘there’s a fixed 70% herd immunity threshold’ is just that—a public line, and isn’t (and never was—if I remember rightly, the Imperial model from March estimated a herd immunity threshold of 40% without a lockdown) biasing the output of modelling. It could also be the case that doctors or generic public health people in the US are repeating the 70% line while epidemiologists and modellers with specific expertise (in the US and elsewhere) are being more methodical.
I searched herd immunity in the UK government report you referenced and found the following line
That comment looks exaclty like the supposed strawman Zvi is putting up. Is there some reading between the lines explanation that contradicts their direct statement? And if there is, why would it matter more than their direct statement.
I generally do believe your point that modelers accept the broader evidence on immunity much more than public health officials and pundits.
It’s clearly the case that the public line about 70% herd immunity is still out there, but I think my broader point is served by that report. They have the obligatory ‘herd immunity is reached at 70% and there may be no immunity conferred’ caveat but then the actual model implies that in a worst case scenario 30% of the UK gets infected. You might speculate that they consulted the modellers for the model but not for the rest of it.