There has not been a substantial second wave anywhere there was a strong first wave. This implies that herd immunity, as I’ve noted here, is likely playing a big role.
Iran had a big outbreak (much bigger than official numbers) and now has a clear second wave. Some of this is in different cities but I haven’t found a careful analysis.
Have you looked at the mobility data? Most (maybe all) of the places in Europe that had a strong first wave kept mobility low (esp. public transport and workplace) and have adopted strict social distancing in public spaces and some level of masking. I haven’t seen any good evidence that herd immunity is playing more role than we would expect (e.g. 15-30% reduction in R in worst hit places like NYC, Lombardy, London, Madrid).
I think there’s pretty good evidence that most adults are susceptible from the huge outbreaks in prisons, meat plants and hospitals with bad PPE.
2. Sweden didn’t come out of this as the hero, but things were nowhere near as bad as the critics predicted for it, and cases managed to peak and then steadily decline.
This seems wrong-headed. Sweden has been terrible compared to ALL its geographic neighbors (which are very similar culturally and started from the same position). They have a very high death rate and a poor rate of testing. They have suffered substantial economic damage despite not locking down. AFAIK, the hospital system “survived” the peak in part because they did not treat the most vulnerable. As well as low testing, they have very low mask use, and so they are poorly set up for the end of summer (when people will be inside much more). I also think Sweden is pretty different from the US. I’d expect compliance with testing, contact tracing and isolation to be high in Sweden, while it seems compliance in NYC is not high.
4. Household infection rate is shockingly low.
Why is it shocking? If R=2.5 with zero social distancing and tons of superspreader events, it’s just not that infectious. We also know there is variability in infectiousness across individuals (overdispersion). SARS-1 had a household secondary attack rate of 8%, H1N1 flu had rates that varied across studies but they are mostly lower than 38% (e.g. 15-20% is common).
Regarding children, this meta-analysis finds adults have a 1.4x higher risk of infection. Not a huge difference. Kids are much more likely to have mild symptoms or be asymptomatic.
1. I don’t think mobility data correlates well with risk taken—it’s easy to screw up and limit the wrong things (get stuck together indoors), or to limit the right things without changing mobility much (move outdoors). It’s indicative of trying to do anything at all, at least. I’ve talked extensively over many posts about why I think herd immunity is a bigger deal than people think, especially in On R0.
2. Sweden did badly, but it’s important to notice that it did far less badly than a naive model would expect it to do. Why did things end up getting contained when they did? Why wasn’t it much worse? Pointing out that Norway did better doesn’t change the need to answer that. This is not me saying Sweden is a model, it’s a control group and we need to understand its data.
4. It’s shocking because those people are having very intimate contact over extended periods of time in indoor situations, often sleeping together, touching, sharing food and cooking, over periods of days of infectiousness, etc etc. It’s certainly not the naive or public perception of such risks if precautions aren’t taken. And it then requires an explanation for why we can’t contain this thing with relatively light countermeasures.
On the children, the metastudy doesn’t seem like a methodology I’d think would produce good results on such matters. I’m open to evidence that difference is that small but it definitely seems like the vector is mostly harmless...
I’ve talked extensively over many posts about why I think herd immunity is a bigger deal than people think
I understood the argument as “there’ll be herd immunity faster in specific locations (e.g. subway riders or people under 20 in some neighborhood)”. The logic makes sense but I’d guess the effect is small, due to population mixing / small-world network effects. Young people are probably getting infected more but they are still far from HI everywhere and they are probably well mixed. I haven’t seen any positive empirical evidence for your view over my take (big first wave --> people take precautions more seriously and have slower reopening + 20-30% drop in R due to fewer susceptible).
There’s Google/Apple style mobility (which actually records amount of time spent in work/home/retail/public transit) and questionnaires that ask for “number of contacts per day”. People have used both to model cases/deaths and they are both pretty useful. Somepapers (China) and UK. The point is that we know you can predict spread using these proxies for contact. So you can actually see if the amount of predicted contact is lower in NYC, London, Madrid and Lombardy vs. places that didn’t have a big first wave (e.g. LA, Miami, Phoenix). And the predicted contact was lower in the former places. (But I haven’t done a careful study).
2. Sweden did badly, but it’s important to notice that it did far less badly than a naive model would expect it to do. Why did things end up getting contained when they did? Why wasn’t it much worse?
Public transit use was down 55% in Sweden at peak and is still at −7%. Norway was down 65%. Swedes stopped going to the cinema and other high-risk venues were way down. Without a formal lockdown, there was a huge change of behavior in Sweden. I’d guess Swedes were aware that all the countries around them had tighter restrictions and much lower death tolls. So they acted to reduce risk. (People in the UK also reduced risk more than was required by government.) So I don’t see any mystery in Sweden. The real mysteries: Vietnam, Thailand, Cambodia, Laos and Indonesia. And I’m surprised how well the SF Bay has done.
4. It’s shocking because those people are having very intimate contact over extended periods of time
Agree it goes against the naive model. But if you take seriously that 20% of people do 80% of infecting (or maybe a bit less than that), then it’s likely that a decent proportion are essentially not infectious. Also note that many household members are younger children, who are harder to infect.
Iran had a big outbreak (much bigger than official numbers) and now has a clear second wave. Some of this is in different cities but I haven’t found a careful analysis.
Have you looked at the mobility data? Most (maybe all) of the places in Europe that had a strong first wave kept mobility low (esp. public transport and workplace) and have adopted strict social distancing in public spaces and some level of masking. I haven’t seen any good evidence that herd immunity is playing more role than we would expect (e.g. 15-30% reduction in R in worst hit places like NYC, Lombardy, London, Madrid).
I think there’s pretty good evidence that most adults are susceptible from the huge outbreaks in prisons, meat plants and hospitals with bad PPE.
This seems wrong-headed. Sweden has been terrible compared to ALL its geographic neighbors (which are very similar culturally and started from the same position). They have a very high death rate and a poor rate of testing. They have suffered substantial economic damage despite not locking down. AFAIK, the hospital system “survived” the peak in part because they did not treat the most vulnerable. As well as low testing, they have very low mask use, and so they are poorly set up for the end of summer (when people will be inside much more). I also think Sweden is pretty different from the US. I’d expect compliance with testing, contact tracing and isolation to be high in Sweden, while it seems compliance in NYC is not high.
Why is it shocking? If R=2.5 with zero social distancing and tons of superspreader events, it’s just not that infectious. We also know there is variability in infectiousness across individuals (overdispersion). SARS-1 had a household secondary attack rate of 8%, H1N1 flu had rates that varied across studies but they are mostly lower than 38% (e.g. 15-20% is common).
Regarding children, this meta-analysis finds adults have a 1.4x higher risk of infection. Not a huge difference. Kids are much more likely to have mild symptoms or be asymptomatic.
1. I don’t think mobility data correlates well with risk taken—it’s easy to screw up and limit the wrong things (get stuck together indoors), or to limit the right things without changing mobility much (move outdoors). It’s indicative of trying to do anything at all, at least. I’ve talked extensively over many posts about why I think herd immunity is a bigger deal than people think, especially in On R0.
2. Sweden did badly, but it’s important to notice that it did far less badly than a naive model would expect it to do. Why did things end up getting contained when they did? Why wasn’t it much worse? Pointing out that Norway did better doesn’t change the need to answer that. This is not me saying Sweden is a model, it’s a control group and we need to understand its data.
4. It’s shocking because those people are having very intimate contact over extended periods of time in indoor situations, often sleeping together, touching, sharing food and cooking, over periods of days of infectiousness, etc etc. It’s certainly not the naive or public perception of such risks if precautions aren’t taken. And it then requires an explanation for why we can’t contain this thing with relatively light countermeasures.
On the children, the metastudy doesn’t seem like a methodology I’d think would produce good results on such matters. I’m open to evidence that difference is that small but it definitely seems like the vector is mostly harmless...
I understood the argument as “there’ll be herd immunity faster in specific locations (e.g. subway riders or people under 20 in some neighborhood)”. The logic makes sense but I’d guess the effect is small, due to population mixing / small-world network effects. Young people are probably getting infected more but they are still far from HI everywhere and they are probably well mixed. I haven’t seen any positive empirical evidence for your view over my take (big first wave --> people take precautions more seriously and have slower reopening + 20-30% drop in R due to fewer susceptible).
There’s Google/Apple style mobility (which actually records amount of time spent in work/home/retail/public transit) and questionnaires that ask for “number of contacts per day”. People have used both to model cases/deaths and they are both pretty useful. Some papers (China) and UK. The point is that we know you can predict spread using these proxies for contact. So you can actually see if the amount of predicted contact is lower in NYC, London, Madrid and Lombardy vs. places that didn’t have a big first wave (e.g. LA, Miami, Phoenix). And the predicted contact was lower in the former places. (But I haven’t done a careful study).
Public transit use was down 55% in Sweden at peak and is still at −7%. Norway was down 65%. Swedes stopped going to the cinema and other high-risk venues were way down. Without a formal lockdown, there was a huge change of behavior in Sweden. I’d guess Swedes were aware that all the countries around them had tighter restrictions and much lower death tolls. So they acted to reduce risk. (People in the UK also reduced risk more than was required by government.) So I don’t see any mystery in Sweden. The real mysteries: Vietnam, Thailand, Cambodia, Laos and Indonesia. And I’m surprised how well the SF Bay has done.
Agree it goes against the naive model. But if you take seriously that 20% of people do 80% of infecting (or maybe a bit less than that), then it’s likely that a decent proportion are essentially not infectious. Also note that many household members are younger children, who are harder to infect.
This was mostly critical comment. But I’m happy that you’re writing these updates and strongly upvoted the post!