This site provides a good collection of data from all 50 states with the ability to visualize change over time and to do so comparing different states side by side. In talking about strategies of how to address this bug, we need exactly this: comparisons of how different strategies have fared. As I look at these numbers (it's a LOT of data, so nothing detailed, but from a "first run-through" sort of perspective), the broad patterns look quite similar in character in all states. This suggests that the bug is spreading and making people sick in fairly similar ways without regard to the different mitigation efforts in different states. In other words, there is not obvious evidence here to show that "more" effort against the bug has led to better sustained outcomes. If there are differences, they are at the margins. The timing of when different states do better relative to other states in any given snapshot of time of this epidemic seems at first glance random.

If someone sees a clear pattern that goes against what I have just said, I'd be interested to hear it. If what I say here is true, it is basically the statement of a negative result. It would suggest not that one particular strategy (greater or lesser interference in people's daily lives) yields a sustained benefit (or the inverse, a sustained harm), but that the strategies we have employed provide no better results than random chance.

These numbers do not catch - very important to note - ancillary effects. In other words, these are measures of direct disease expression. Effects on people that are not directly disease-related (e.g. unemployment, social depression, social disintegration, other non-covid medical issues delayed because of covid regulation, etc) do not show up here. If I am correct and we are looking at a negative result in difference in disease expression directly with the various Covid strategies, then the only effects we will see will be in this secondary set, and these effects are already abundantly clear.