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.
For what it’s worth, I haven’t heard much mention of a 70% immunity threshold in the UK recently, but I suspect the public conversation is worse in the US. That being said, there is still explicit derision of the concept of herd immunity, based on declining antibody counts that don’t give strong evidence for anything, so Zvi’s point that a lot of people don’t want to hear about herd immunity still clearly applies—see e.g. this:
Prof Jonathan Heeney, a virologist at the University of Cambridge, said the findings had put “another nail in the coffin of the dangerous concept of herd immunity”.
With that as the background, I’d be interested to know your opinion on this UK government report. They go over a bunch of factors that might increase transmission and say that a ‘reasonable worst case’ scenario is R_t increasing to 1.7 in September and remaining constant, assuming effectively zero government action—total second wave deaths are about double the first, with a similar peak of currently infected individuals and the peak in January (meaning a lot of time to course-correct and reimpose measures). As far as I can tell that’s just a guesstimate modelling assumption, not motivated by any kind of complicated transmission model.
(Honestly, this is a fair bit better than I would have guessed for the worst case scenario—a far cry from the sorts of things we discussed here in March.)
They don’t say how plausible they think this scenario is or give explicit motivation for R_t=1.7, just model the consequences of that change.
Does this look like a paper that doesn’t account for a potentially lower immunity threshold, so is probably overestimating the damage of a winter wave? And what about seasonality—they claim that the degree of seasonality of Covid-19 is highly uncertain. Is this true? I’ve heard some sources say it’s probably not that seasonal and others say it definitely is. What’s your read of that question? A winter wave seems to be the most likely route to a damaging second wave in Europe and it would be good to know how plausible that is.
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.
For what it’s worth, I haven’t heard much mention of a 70% immunity threshold in the UK recently, but I suspect the public conversation is worse in the US. That being said, there is still explicit derision of the concept of herd immunity, based on declining antibody counts that don’t give strong evidence for anything, so Zvi’s point that a lot of people don’t want to hear about herd immunity still clearly applies—see e.g. this:
With that as the background, I’d be interested to know your opinion on this UK government report. They go over a bunch of factors that might increase transmission and say that a ‘reasonable worst case’ scenario is R_t increasing to 1.7 in September and remaining constant, assuming effectively zero government action—total second wave deaths are about double the first, with a similar peak of currently infected individuals and the peak in January (meaning a lot of time to course-correct and reimpose measures). As far as I can tell that’s just a guesstimate modelling assumption, not motivated by any kind of complicated transmission model.
(Honestly, this is a fair bit better than I would have guessed for the worst case scenario—a far cry from the sorts of things we discussed here in March.)
They don’t say how plausible they think this scenario is or give explicit motivation for R_t=1.7, just model the consequences of that change.
Does this look like a paper that doesn’t account for a potentially lower immunity threshold, so is probably overestimating the damage of a winter wave? And what about seasonality—they claim that the degree of seasonality of Covid-19 is highly uncertain. Is this true? I’ve heard some sources say it’s probably not that seasonal and others say it definitely is. What’s your read of that question? A winter wave seems to be the most likely route to a damaging second wave in Europe and it would be good to know how plausible that is.