You are still not quite grasping the reason for controlling for pop density. Policy makers ARE concerned about pop density, along with age distributions and comorbidities, some of the other factors controlled for in the study. They were controlled for because it is already known how those affect the impact of a pandemic and the researchers wanted to study decisions that could help everyone. Controlling for factors isn't ignoring them. It is factoring in their respective impact and seeing if the variables of interest are still impactful.

So, now we can see which rules and implementations would be irresponsible to apply across varying pop densities. If they analyzed a policy whose efficacy was highly contingent on pop density, the statistical confidence would drop significantly, and we would conclude that it is not a generally-applicable policy.

We know a policy aspect works across all pop densities because we controlled for it and found it to be statistically significant. It achieved exactly what you want. Does that make sense?

So don't call something stupid and irresponsible if you don't know what is going on. It's a very common method to isolate specific causes of variance in data so that proper analyses can be made. Maybe approaching it in good faith and inquiring about why it concerns you would yield a more productive conversation. Through colleagues I have over at that institution, I've heard about the peer-review responses of this paper. There were minor edits, but reviewing health economists would have pointed out a problem as glaring as "ignoring" a factor as important as population. Not controlling for population and having sweeping generalizations across pop densities would have prevented this paper from being published in the first place, because that would be poor science.