Tl;dr: In the short run (a few weeks) seroprevalence, in the medium run (months) behavior. In the long-run likely behavior as well, but other factors like wealth and technological access might start to dominate in hard-to-predict ways.
Thanks for the question! When I made this AMA, I was worried that all the questions would be about covid. Since there’s only one, I might as well devote a bunch of time to it.
There are of course factors other than those three, unless you stretch “behavior” to be maximally inclusive. For example, having large family sizes in a small house means it’s a lot harder to control disease spread within the home (in-house physical distancing is basically impossible if 7 people live in the same room). Density (population-weighted) more generally probably means it’s harder to control disease spread. One large factor is state capacity, which I operationalize roughly as “to the extent your gov’t can be said to be a single entity, how much can it carry out the actions it wants to carry out.” Poverty and sanitation norms more generally likely matters a lot, though I haven’t seen enough data to be sure. Among high-income countries, I also will not be surprised if within-country inequality is a large factor, though I am unsure what the causal mechanism will be.
In the timescale you need to think about for prioritizing hospital resources and other emergency measures, aka “the short run” of say a few weeks, seroprevalence of the virus (how many people are infected and infectious) dominates by a very large margin. There’s so much we still don’t know about how the disease spreads, so I think (~90%) by far the most predictive factors for how many cases there will be in a few weeks are high-level questions like how many people are currently infected and what the current growth rate is, with a few important caveats like noting that confirmed infections definitely do NOT equal active infections.
In the medium run (2+ months), I think (~85%), at least if I was to choose between {current prevalence, behavior, seasonality}, this is almost entirely driven by behavior, both governmental actions (test and trace policies, school closures, shutting large events) and individual responses (compliance, general paranoia, voluntary social distancing, personal mask usage). This is especially clear to me when I compare the trajectories of countries in Latin America to ones in (especially East) Asia. In March and April, there was not a very large seasonality difference, and wealth levels were similar, and household sizes weren’t that different, and East Asia started with much higher seroprevalence, but through a combination of governmental interventions and individual behaviors, the end of April looked very different for Latin America countries and Asian ones.
Seasonality probably matters. I tried studying how much it matters and got pretty confused. My best guess is ~25% reduction in Rt (with high uncertainty), so maybe it matters a lot in relative terms compared to specific interventions (like I wouldn’t be surprised if it’s a bigger deal than a single intervention like going from 20% to 70% cloth mask coverage, or university closures, or 50% increase in handwashing, or banning public events larger than N people), but I’d be very surprised if it’s bigger than the set of all behaviors. In the short run seasonality will be a lot smaller than the orders of magnitude differences in current prevalence, and in the long run seasonality is significantly smaller than behavioral change.
One thing to note is that some of the effects of seasonality is likely mediated through behavior or the lack thereof. For example, schools opening in fall are plausibly a large part of disease spread for flu and thus maybe covid; this channel is irrelevant in places that have school closures anyway. Likewise, summer vs winter (in many countries) changes where and how people interact with each other. There’s also countervailing factors I don’t know enough about, like maybe hotter weather makes it less palatable to wear masks, or especially hot/cold weather interface poorly with existing ventilation setups.
For Covid-19 spread, what seems to be the relative importance of: 1) climate, 2) behaviour, and 3) seroprevalence?
Tl;dr: In the short run (a few weeks) seroprevalence, in the medium run (months) behavior. In the long-run likely behavior as well, but other factors like wealth and technological access might start to dominate in hard-to-predict ways.
Thanks for the question! When I made this AMA, I was worried that all the questions would be about covid. Since there’s only one, I might as well devote a bunch of time to it.
There are of course factors other than those three, unless you stretch “behavior” to be maximally inclusive. For example, having large family sizes in a small house means it’s a lot harder to control disease spread within the home (in-house physical distancing is basically impossible if 7 people live in the same room). Density (population-weighted) more generally probably means it’s harder to control disease spread. One large factor is state capacity, which I operationalize roughly as “to the extent your gov’t can be said to be a single entity, how much can it carry out the actions it wants to carry out.” Poverty and sanitation norms more generally likely matters a lot, though I haven’t seen enough data to be sure. Among high-income countries, I also will not be surprised if within-country inequality is a large factor, though I am unsure what the causal mechanism will be.
In the timescale you need to think about for prioritizing hospital resources and other emergency measures, aka “the short run” of say a few weeks, seroprevalence of the virus (how many people are infected and infectious) dominates by a very large margin. There’s so much we still don’t know about how the disease spreads, so I think (~90%) by far the most predictive factors for how many cases there will be in a few weeks are high-level questions like how many people are currently infected and what the current growth rate is, with a few important caveats like noting that confirmed infections definitely do NOT equal active infections.
In the medium run (2+ months), I think (~85%), at least if I was to choose between {current prevalence, behavior, seasonality}, this is almost entirely driven by behavior, both governmental actions (test and trace policies, school closures, shutting large events) and individual responses (compliance, general paranoia, voluntary social distancing, personal mask usage). This is especially clear to me when I compare the trajectories of countries in Latin America to ones in (especially East) Asia. In March and April, there was not a very large seasonality difference, and wealth levels were similar, and household sizes weren’t that different, and East Asia started with much higher seroprevalence, but through a combination of governmental interventions and individual behaviors, the end of April looked very different for Latin America countries and Asian ones.
Seasonality probably matters. I tried studying how much it matters and got pretty confused. My best guess is ~25% reduction in Rt (with high uncertainty), so maybe it matters a lot in relative terms compared to specific interventions (like I wouldn’t be surprised if it’s a bigger deal than a single intervention like going from 20% to 70% cloth mask coverage, or university closures, or 50% increase in handwashing, or banning public events larger than N people), but I’d be very surprised if it’s bigger than the set of all behaviors. In the short run seasonality will be a lot smaller than the orders of magnitude differences in current prevalence, and in the long run seasonality is significantly smaller than behavioral change.
One thing to note is that some of the effects of seasonality is likely mediated through behavior or the lack thereof. For example, schools opening in fall are plausibly a large part of disease spread for flu and thus maybe covid; this channel is irrelevant in places that have school closures anyway. Likewise, summer vs winter (in many countries) changes where and how people interact with each other. There’s also countervailing factors I don’t know enough about, like maybe hotter weather makes it less palatable to wear masks, or especially hot/cold weather interface poorly with existing ventilation setups.