Why are you skeptical about social distancing? It’s working in Hong Kong… When thousands are dying each day, there would be a lot of political will for drastic measures, right?
I think you’re right about social distancing working, and if you live in a country that has the capacity to mount an effective response, I’d probably put p(treatment) = 0.7 or so. Remember we won’t see any effect from what Italy has just done for at least a week because of incubation, and if it doesn’t work they’ll just keep escalating the isolation and quarantine, and we know that a high enough response works (China, South Korea).
Also, I think there’s a better than even chance that p(young + no preexisting conditions) is much lower than either individually—since the absolute numbers of young people in a lot of those studies were low.
Also also, and maybe the OP took this into account, the corrections for delay to death and underreporting skew the death rates even more strongly towards older patients.
I wouldn’t discount the possibility of a saving throw in the case of the virus approaching its natural attack rate—massive mobilization to provide at least basic medical care (oxygen) on a huge scale. The UK government has floated ideas that sound a lot like that (field hospitals outside cities), and there has already been a colossal expansion in the production of protective gear in China. So I would put p(Treatment | infection) at 0.2 or so if you live in the UK or somewhere similar.
Finally, and possibly for the above reasons, Rob Wiblin estimated a probability of the same 1/10th as high as the OP, here and again here.
I think Rob Wiblin is confused about the death rate with overwhelmed hospitals—link. He thinks it’s 1.6%, but I think it’s really 5-15%.
I really don’t think P(treatment) should be an input to your analysis at all; it should be an intermediate result, if it’s even worth mentioning at all. P(treatment) lumps together wildly different things. For example, compare P(treatment | 1% of the population is infected) vs P(treatment | 50% of the population is infected). The former requires 50x more treatment capacity. I’m not saying here that P(treatment | 50% of the population is infected) is definitely <5% or anything like that; I’m saying, at the meta-level, that the value of P(treatment | 50% of the population is infected) is an intuitively-understandable quantity whose value is worth debating directly, whereas P(treatment) is not.
Likewise, I think P(treatment | infection) lumps together very different scenarios, some where almost nobody gets infected but you personally get unlucky, and others where almost everyone gets infected.
Assuming that he read your comment and the comments of people on his FB saying similar things, I think Rob is confident that aggressive testing and social distancing measures will arrest the spread (as they already have in at least 3 countries!), along with expansion of capability (already happening w.r.t. masks!), will ensure that we get sort-of-adequate access to healthcare, even if things are somewhat overwhelmed, like in Wuhan, so doubling or 5x-ing their mortality rate is a better guide to what is likely to happen, rather than guesstimating based on no treatment.
But I also think it’s possible that the US (where I live) would be worse-off (in terms of hospital overwhelmed-ness) than the heart of Wuhan. The logic is: Hubei is <5% of the population of China, and the central government could draw on the resources of the other >95% of the country to marshal a response. And the other 95% was unencumbered by the extreme social distancing that Hubei was undergoing.
By contrast, as far as I know, there could be exponentially-growing community transmission in every city in the USA right now. (After all, we know about the Seattle outbreak because there happened to be the Seattle flu study checking random people in Seattle, not because we were checking random people in every city and only found community transmission in Seattle. If I understand correctly.) If there’s a crisis everywhere at once, then obviously marshaling a response is harder, not least because the people trying to marshal the response are hampered by the social distancing measures.
Not to mention various other differences between the US government and Chinese government and South Korean government etc. :)
I think you’re right about social distancing working, and if you live in a country that has the capacity to mount an effective response, I’d probably put p(treatment) = 0.7 or so. Remember we won’t see any effect from what Italy has just done for at least a week because of incubation, and if it doesn’t work they’ll just keep escalating the isolation and quarantine, and we know that a high enough response works (China, South Korea).
Also, I think there’s a better than even chance that p(young + no preexisting conditions) is much lower than either individually—since the absolute numbers of young people in a lot of those studies were low.
Also also, and maybe the OP took this into account, the corrections for delay to death and underreporting skew the death rates even more strongly towards older patients.
I wouldn’t discount the possibility of a saving throw in the case of the virus approaching its natural attack rate—massive mobilization to provide at least basic medical care (oxygen) on a huge scale. The UK government has floated ideas that sound a lot like that (field hospitals outside cities), and there has already been a colossal expansion in the production of protective gear in China. So I would put p(Treatment | infection) at 0.2 or so if you live in the UK or somewhere similar.
Finally, and possibly for the above reasons, Rob Wiblin estimated a probability of the same 1/10th as high as the OP, here and again here.
I think Rob Wiblin is confused about the death rate with overwhelmed hospitals—link. He thinks it’s 1.6%, but I think it’s really 5-15%.
I really don’t think P(treatment) should be an input to your analysis at all; it should be an intermediate result, if it’s even worth mentioning at all. P(treatment) lumps together wildly different things. For example, compare P(treatment | 1% of the population is infected) vs P(treatment | 50% of the population is infected). The former requires 50x more treatment capacity. I’m not saying here that P(treatment | 50% of the population is infected) is definitely <5% or anything like that; I’m saying, at the meta-level, that the value of P(treatment | 50% of the population is infected) is an intuitively-understandable quantity whose value is worth debating directly, whereas P(treatment) is not.
Likewise, I think P(treatment | infection) lumps together very different scenarios, some where almost nobody gets infected but you personally get unlucky, and others where almost everyone gets infected.
Assuming that he read your comment and the comments of people on his FB saying similar things, I think Rob is confident that aggressive testing and social distancing measures will arrest the spread (as they already have in at least 3 countries!), along with expansion of capability (already happening w.r.t. masks!), will ensure that we get sort-of-adequate access to healthcare, even if things are somewhat overwhelmed, like in Wuhan, so doubling or 5x-ing their mortality rate is a better guide to what is likely to happen, rather than guesstimating based on no treatment.
Well, that’s entirely possible.
But I also think it’s possible that the US (where I live) would be worse-off (in terms of hospital overwhelmed-ness) than the heart of Wuhan. The logic is: Hubei is <5% of the population of China, and the central government could draw on the resources of the other >95% of the country to marshal a response. And the other 95% was unencumbered by the extreme social distancing that Hubei was undergoing.
By contrast, as far as I know, there could be exponentially-growing community transmission in every city in the USA right now. (After all, we know about the Seattle outbreak because there happened to be the Seattle flu study checking random people in Seattle, not because we were checking random people in every city and only found community transmission in Seattle. If I understand correctly.) If there’s a crisis everywhere at once, then obviously marshaling a response is harder, not least because the people trying to marshal the response are hampered by the social distancing measures.
Not to mention various other differences between the US government and Chinese government and South Korean government etc. :)