It explores two types of heterogeneity
- variation in susceptibility
- and variation in contact rate. medrxiv.org/content/10.110…
The reason that infection-acquired immunity is highly effective when these heterogeneities exist is that infection acts like a targeted vaccine.
I am dubious about the assumptions made about heterogeneity, and I think the techniques used to measure it will struggle to disentangle the effects from interventions or behavior change.
What I'm giving here is my first impression, on Saturday, while trying to spend time with my kids. So grains of salt are needed, and others should look closely.
Along with the low herd immunity thresholds, these models would predict low levels of infection, even in unmitigated epidemics.
This is inconsistent with such high levels of heterogeneity in population structure.
The model only predicts such high attack rates if we assume the heterogeneity is low.
If these places had reached their herd immunity thresholds AND had effective interventions in place the disease should have just melted away.
So what do I think went wrong?
Early in the epidemic, we saw exponential growth. Almost every model would predict this. At some point the epidemic deviates to a lower than exponential growth.
So it's only after the deviation from exponential that you can start to fit parameters.
If we assume it's due to heterogeneity, then early deviation means higher heterogeneity.
I think people changed behavior sooner. If I'm right, I think this would cause their model to overestimate heterogeneity.