(Disclaimer: I don't know what I'm talking about, pointers to real literature would be more useful than this, every sentence deserves to be aggressively hedged/caveated, etc.)

Increasing test capacity: I've seen some people suggest that the second wave is just an artifact of increased testing in these states. If that were the case, then there would be no rise in covid cases to be explained. But then I would expect the fraction of tests that returned positive to be decreasing, and we aren't seeing that. This one seems like wishful thinking to me.

I don't think the increase in testing capacity fully explains the "second wave," but I think it does totally change the quantitative picture.

Intuitively I expect that (rate of change in positive test %) is better than (rate of change in confirmed cases) as a way of approximating (rate of change in actual cases). It also doesn't seem great, especially over multiple weeks, but I'll use it here until someone convinces me this is dumb.

Johns Hopkins aggregates testing numbers here. Picking CA as a second-wave state, it hit its minimum positive test rate of .04 on May 24. That rate rose by 20% by June 21, to 0.048 (and has kept going up).

If there was a 7 day lag, we'd expect to see a 20% increase in deaths by from May 31 to June 28. Eyeballing the google deaths data things look basically flat. So I guess that means a drop of ~20% in fatality rate over that month.

Trying again, let's take Georgia. Minimum of .058 on June 10, up 50% to .091 by June 21. Google seems to have deaths roughly constant or maybe decreasing from June 17 to June 28, which is a ballpark ~30% drop in fatality rate to offset the ~50% increase in infections.

One problem with these numbers is that I think the test numbers are for day the test occurred, but the death numbers are for the day they are reported. Would probably be better to use numbers for the day the death actually occurred, though I think that probably requires going at least a few days further back in time (which is going to make it harder to interpret cases like Georgia that hit the minimum only 3 weeks ago).

Delayed initial testing: When things were first taking off in first wave states, our testing capacity was way behind where it needed to be. Perhaps this heavily suppressed the initial "confirmed" numbers for the first wave, and so we should expect to see second wave deaths rise in the next few weeks?

It seems like the average time lag between showing symptoms and dying from COVID is something like 18 days (here, data from China but if anything I expect longer lags here). So if we were testing people earlier it seems like we could easily have more like a 2 week lag than a 1 week lag. That could mostly explain Georgia and California.

Overall I can't really tell what's going on, my sense is that your story in the post is basically right (and demographic changes sound likely) but that the mystery to be explained is *much* less than a 5x change in fatality rate. I feel like the constant death rate in the face of exploding cases is suspicious but best guess is that it's a coincidence, death rates will end up rising and IFR will end up modestly lower than the initial wave.

I would love to see a version of the analysis in the OP controlling for big increases in testing, and getting a more careful handle on lags between testing and death. Hopefully someone has already done that and it's just a matter of someone here finding the cite.

Another possibility (not sure how likely): maybe treatment capacity and protocols have improved?

One possibility seems to be that the virus could be evolving towards lower mortality rates, possibly in conjunction with other mentioned environmental causes (higher ratio of young people being out and about, Vitamin D). I don't know of any direct evidence for this, but it might be what we'd expect from theory (e.g. SA Frank 1994, PRSB). If, for example, a portion of severity of case is underpinned by genetics of the virus (and not just the host), and these people are more mobile (and have been for months), there could be selection for reduced virulence.

Another possibility is better disease survival due to increased vitamin D levels from sunshine (or due to some other physiological effect of sunlight).

The effect seems rather large for this to be the explanation, but it sure would be great if a bit of sunlight is all that's needed!

I don't understand how the second wave can't be explained by increase in testing. Before only people who were sick were allowed to be tested, who correlate more with hospital visits, which correlates more with deaths, so it more closely follows the death graph.

Now anyone can be tested and it's estimated that 40 to 80 percent of people are asymptomatic who will never even see a doctor.

Hence the infection rate skyrockets and the death rate remains the same.

So I don't follow the reasoning.

Additionally there's the possibility that death rates were inflated before by doctors labeling any death that test positive for covid, even if a car accident, a covid death. From a cynic's perspective there is also more financial renumeration from insurance the medicare for a corona labeled patient.