Good point about the tropics. I could be wrong about the seasonal directionality. I had an unstated assumption that even if direction of the effect was inverted the change wouldn’t be significant enough to account for the data. That was my real crux.
My reference point for religious rituals was Christmas in the United States. India’s biggest religious rituals take place outside. Even if India’s religious rituals were much bigger, they wouldn’t cause a takeoff as fast as we observed in Zvi’s graph.
That’s a informative variant graph. I’m updating my probabilities to 98% it’s one or more strains and 99% it’s one or more strains and/or a change to the measurement. I’m going to add another prediction: 95% confidence that India fails to get B1.617 under control before it burns through the population.
But experts say India is unlikely to meet its target of covering 250 million people by July, especially as cases continue to surge.
I had an unstated assumption that even if direction of the effect was inverted the change wouldn’t be significant enough to account for the data.
I agree.
or a change to the measurement
Given the apparent under reporting, I’d say no.
95% confidence that India fails to get B1.617 under control before it burns through the population.
It seems like people will panic and isolate. Don’t know how much that could or will change in India though.
According to OWD the reproduction rate is 1.5 . So non pharmacological interventions might make a difference, conversely abandoning non pharmacological interventions might have contributed to the current outbreak.
Seconded. The situation in India looks worse, but kind of comparable, to the rapid spikes in South Africa and the UK when new variants arose there. In both cases, the strong reaction induced by the threatening situation led to things stabilizing. It’s true that things might be worse for India, but 95% seems really quite high. Maybe you have a detailed model of why the situation is much different and worse in India now? If so, I’d be curious about the reasoning. (JTBC, I also think it’s likely that things will be completely bad, but I don’t immediately see why >60% for a worst-case scenario seems obviously warranted. There’s a chance that if I looked into this for 2h or heard some convincing arguments, I’d also update to >90% now. )
Good point about the tropics. I could be wrong about the seasonal directionality. I had an unstated assumption that even if direction of the effect was inverted the change wouldn’t be significant enough to account for the data. That was my real crux.
My reference point for religious rituals was Christmas in the United States. India’s biggest religious rituals take place outside. Even if India’s religious rituals were much bigger, they wouldn’t cause a takeoff as fast as we observed in Zvi’s graph.
That’s a informative variant graph. I’m updating my probabilities to 98% it’s one or more strains and 99% it’s one or more strains and/or a change to the measurement. I’m going to add another prediction: 95% confidence that India fails to get B1.617 under control before it burns through the population.
India is hosed. I wonder what happens when B1.617 hits other countries that haven’t vaccinated their populations yet?
I agree.
Given the apparent under reporting, I’d say no.
It seems like people will panic and isolate. Don’t know how much that could or will change in India though.
According to OWD the reproduction rate is 1.5 . So non pharmacological interventions might make a difference, conversely abandoning non pharmacological interventions might have contributed to the current outbreak.
Seconded. The situation in India looks worse, but kind of comparable, to the rapid spikes in South Africa and the UK when new variants arose there. In both cases, the strong reaction induced by the threatening situation led to things stabilizing. It’s true that things might be worse for India, but 95% seems really quite high. Maybe you have a detailed model of why the situation is much different and worse in India now? If so, I’d be curious about the reasoning. (JTBC, I also think it’s likely that things will be completely bad, but I don’t immediately see why >60% for a worst-case scenario seems obviously warranted. There’s a chance that if I looked into this for 2h or heard some convincing arguments, I’d also update to >90% now. )
My model of the Indian subcontinent is it’s a poor region of huge dense population centers administered by weak central governments.