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Different regions have dramatically different population densities, and don't necessarily need shelter-in-place rules. In NYC, shelter-in-place is probably the only feasible way to reduce social interactions when case-count is exploding, but in Boise, where people mostly live in detached housing and drive cars and cases are measured in the hundreds, it might be sufficient to eliminate large gatherings and shut down restaurants. It's not just a matter of thresholds.

For all the various politicians are talking about "following the science", there's very little actual science backing up these measures. We're pretty much making it up as we go, and you would be hard-pressed to find "scientific" justifications for most of what we're currently doing.

> don't necessarily need shelter-in-place rules

Is there a cite for that? Because that's not the way the data looks.

Everywhere was growing with roughly the same exponent before lockdown. The numbers were bigger in NY because it grew longer pre-detection, but there's no reason to believe that everywhere else was any different. Really this disease's growth constant looks shockingly consistent almost everywhere in the world.

> It's unclear to me why we're making these policies at a federal level.

We... aren't. Literally every existing lockdown regime is being enforced at the state level or lower. For the Boise example you mention, the relevant regulation is a stay in place order from Gov. Little in late March.

Edit to show the point better: Go here (easily the best visualization site, FWIW), scroll to the bottom where you can see a log chart of per-capita infection rates normalized to a single "start time" metric, and compare the Idaho chart with the New York one.

https://91-divoc.com/pages/covid-visualization/

They are almost exactly the same chart, modulo a vertical offset and a kink in NY data in the second week (which consensus says is the testing backlog finally catching up).

If Idaho's detached housing and automobile dependence was reducing its rate of infection spread, it should be visible in the slope of this line. And it clearly isn't.

Multiple states don't have shelter-in-place rules, but still remain very different from NY. (They still have some rules, of course; I agree it seems silly to claim that it was safe to do nothing.)

Those states are in for a surprise like Florida was - they may get lucky and just have a very low rate of spread into their state - but if they have a lot of community transmission the disease will spread very quickly and the lack of a reasonable response will be obviously stupid in retrospect once again.

Shelter-in-place is a good general rule - we can roll it back when we've got infrastructure to vaccinate people.

Florida isn't doing great, but it's not doing as bad as New York either.

I'm not sure what you're referring to about vaccination. As California's roadmap lays out, we'll need to roll back shelter-in-place long before vaccines are available and find less costly ways to mitigate the virus.

"Everywhere was growing with roughly the same exponent before lockdown."

No, they weren't. You're just asserting that this is true. There's effectively no way to know what the doubling rate was in a place like Boise before the national lockdown, because the numbers were in the low single digits:

https://covid-19.direct/metro/Boise?tab=glance

But even ignoring that...the site you're linking to shows a wide range of slopes on the per-state graph. You just think they look the same, because the log Y-axis compresses dramatic differences in scale, particularly near the origin. New York, NJ, Michigan and Louisiana are well above the diagonal line, while states like Wyoming, Montana, Vermont, Maine etc. are all well below it.

One of the things we urgently need to figure out is how to prevent bad data visualization from leading to bad conclusions. Statistical malpractice isn't just a meme phrase anymore.

Idaho on 20 March was at 23 confirmed cases (above the "low single digits" metric you picked, but you can pick other points too and get the same result). On 31 March it hit 515.

That's a doubling period of less than three days. It was spreading every bit as fast as New York was. It looks like exactly the same chart with a different constant factor. Yet you insist that these identical results are somehow due to different underlying behavior? Why? Where's the research showing that?

Because the pretty obvious hypothesis is that the disease was spreading the same way because it's the same disease and doesn't care about whether you live in Boise.

All right, here's a different example. Loving County, TX, is roughly 50 or 100 people. It has roughly the area of Los Angeles County. "Don't leave your house" is a bit more ridiculous when the next humans are 20 miles away. Sure, maybe don't go visit them... but stay at home? Why?

OK. That seems like sort of a strawman, but fine. I'm OK with very rural areas having a "Stay home, OR at least 20 miles from the nearest people" rule. Is Loving Texas really chafing under the existing shelter order? I mean, surely that's the way it's being enforced currently, no?

Out there? I doubt it's being enforced at all. How would you?

Edit to show the point better: Go here (easily the best visualization site, FWIW), scroll to the bottom where you can see a log chart of per-capita infection rates normalized to a single "start time" metric, and compare the Idaho chart with the New York one.

Number of cases is largely a proxy for how many tests are being done (https://fivethirtyeight.com/features/coronavirus-case-counts...). Looking at deaths is more accurate, and that shows Idaho (and all other states) well below New York.

But growing with the same exponent! The point was that Idaho doesn't need special mitigation rules, because unmitigated Idaho is somewhere around 2 weeks "behind" New York. Even here people seem not to get that point. The outbreaks are smaller outside the international cities because they were later, not because they're inherently better controlled.

They are not growing with the same exponent. You keep repeating this, even though the evidence you cite clearly shows that it's not true.

I literally gave you numbers elsewhere in this thread. Argue there and cite your own, please. You seem to be the one arguing without evidence.

I used the graph you gave me. You aren't reading it correctly.

Jay Inslee and the Seattle Flu Study. Without the flu study going against medical guidelines (along with the guidance of the CDC to adhere to those guidelines) and testing some of their samples for COVID-19 (which isn't what they were collected for), Washington's timeline would have been pushed much further back.

Don't forget Newsom, who issued the first state-wide shelter in place order. That has been invaluable in keeping California safe(r).

> except in trivial stuff like dates?

Dates are not trivial when people's very livelihoods are at stake.

You know what I meant. You can write the same plan for different regions with parameters. There's no inherent regional interest that requires every county government in the US staff its own disease control department.