I'm assuming the peaks and valleys correspond to weeks, but why are deaths correlating so strongly with the day of the week?
The lack of consistent context and framing around the human malware has made most discussions of it pretty useless, but easy to skew in a particular direction for those wishing to make political hay out of a trend (on either side - very few have clean hands in this regard).
The positive rate for 2020 of all tests is 3%, but it really appears that whatever tests they're using are just wrong - California had daily flights from Wuhan.
The one logical conclusion from this thread is that if ships, hospitals and nursing homes have high rates of infection, and California homes don't, turn off your central AC and heating in NY, etc.
San Francisco: 47 Alameda: 116 Santa Clara: 152 San Mateo: 99 Contra Costa: 50 Marin: 18 Solano: 23
In other words, about ~500 deaths. If you had 60% of the population infected, you might expect 20x that figure.
Why would it matter that California had daily flights from Wuhan? It changes the math almost by nothing. Whenever an initial seeding occurs, domestic cases rapidly and overwhelmingly takeover in spread.
Wuhan has, as of early June testing, a SARS-CoV-2 seropositive rate of approximately ~3%. There were very few infected people coming on those daily flights in January, and by February domestic spread was many orders of magnitude larger than any seeding event.
California also shutdown earlier than other states, especially in the Bay Area, where essentially all major employers implemented work from policies 7-10 days before the official Shelter-in-Place notice.
California may have had an earlier seeding, but we know for sure it was spreading domestically by mid-January in several cities around the country.
https://i.imgur.com/zZ7UGVW.png
Deaths has a few problems. One is that once SARS-CoV-2 finds a nursing home, it's a lot of at-risk people in once place, so it gets hit hard. If deaths is the metric you care about, it's best to put a lot of effort into testing workers at care facilities and putting those facilities strict lockdowns. Once we learned this, we started "gaming" the metric a bit. The other problem is it's a lagging indicator.
Positive tests are problematic because early on, there was a shortage, presumed positive people weren't being tested because it wouldn't change anything, people without symptoms aren't being tested, etc. It's the flakier metric, for sure.
For how many tests are coming back negative, I wish we were doing random testing and random antibody testing. If we're not doing those, we're still being reactive.