Earlier quoted context omitted.
Once you commit to some success metric, you're going to be stuck with it even it proves to be a bad metric. Let's say we all agree the "2 weeks with decreasing number of deaths" is a good target. Then we go back to work, and we discover that going back triggers a rapid spread and kills a bunch of people and starts to overwhelm hospitals. Now we need a new metric. This is a novel scientific problem. Caution and study…
People's lives are always at stake. That's how public policy works. Like 100% of the time. Try painting lines on the highway or administering a school lunch program without putting people's lives at stake. The only thing novel here is completely abandoning the concept of public policy goals. There's nothing scientific about setting your public policy without any metrics at all. This is kind of the opposite of a scien…
At the same time, to your point, I would like to see clear explanations of "these are the aspects of the disease we are trying to understand (virality, mortality, etc)," these are the constraints on our healthcare system, these are the economic effects, here are the tradeoffs we're trying to make. All of that stuff is good, but it's a complex problem and assuming that we know enough at this point to set a clear numerical goal seems wrong to me. Describing general parameters for our data gathering and decision-making is good, though, and I agree that I'd like to see more of it.