A big challenge in determining the effectiveness of policy interventions (i.e. social distancing) is that there are really several buckets that determine how bad the outbreak is in any given area and it's not clear policy interventions are the most important one in the short run.
The buckets are something like:
1) Policy interventions
2) Immutable location-based characteristics, e.g. geography, density, age structure of the population, "culture", weather
3) Luck. How much undetected community spread was there before March? Perhaps strains matter also.
1) Policy interventions
2) Immutable location-based characteristics, e.g. geography, density, age structure of the population, "culture", weather
3) Luck. How much undetected community spread was there before March? Perhaps strains matter also.
My guess is 3 > 2 and 2 > 1, especially given the narrow range of interventions available in the short run. (If every country could "do South Korea", it might be different, but they can't on short notice.)
That could lead to some wrong conclusions about what works, what doesn't.
That could lead to some wrong conclusions about what works, what doesn't.
