This means that from the time someone is infected until they die, a month and a half can have gone through.
By the time you take new isolation measures, you have to wait roughly two weeks to see if daily infection rates start to vary. But the lethality at this point, assuming no change in healthcare system overload, can be more or less statically predicted for weeks after the fact.
Those are called "lagging indicators"; the main thing you try to prevent are deaths, which you can lower by reducing the overload on the healthcare systems, which you can lower by controlling infection rates and keeping them low.
Due to the duration of the disease's evolution, you get to see if your policies really worked more than a month and a half after enacting them, which is extremely slow for a disease that propagates at exponential rates. So people look for proxies like infection rates that are still lagging, but far less so.
Do note that the one good metric you want in the end is going to be "excess deaths", which counts the impact of not just the diseases, but of all other side issues that the disease may have caused. This can usually take months up to years to properly account and analyze.
Thanks!
Sorry to hijack, your actual question is interesting too. I guess that would mean all the increased infection metrics are entirely from increases in testing and we're actually seeing that infection rates have always been way higher and the virus is way way less deadly than previously thought? Or maybe it has mutated and become less deadly?
I'm not sure what to make of the meaning of such a short gap, and of course people may now be testing earlier than they did in the early hot spots, so I'm not sure if this has any predictive value.