Florida governor Ron DeSantis today issued a 30-day stay-at-home order for the state. Florida’s approximately 21 million residents are instructed to remain at home unless they are pursuing “essential services or activities.”

It’s not clear what DeSantis accomplished by delaying this effort to mitigate the Wuhan coronavirus pandemic. Florida’s economy will now be hammered. The state might experience the worst of all worlds.

The bigger question, which John raised last night in a thoughtful and informative post, is the degree to which stay-at-home orders will save lives. John wrote: “Sheltering in place won’t prevent the COVID-19 virus from working its way through the population, it will just do so more slowly.” That view is widely shared by epidemiologists.

This doesn’t mean that sheltering place won’t save lives. It will. For one thing, as John noted, lives will be saved by “flattening” the infection curve because if the same same number of infections is spread out over time, hospitals will be better able to prevent the infected from dying. Why? Because there won’t be the kinds of acute shortages of equipment, such as ventilators, that we experience during extreme peaks of infection.

That’s not necessarily all. While the spread is delayed, we may find medicines that treat the infection effectively. Delaying the spread might also mean reducing the spread if it turns out that the virus doesn’t do well in warm weather. It’s even possible that, over time, the virus mutates or simply goes away.

So sheltering in place will save lives. But how many?

We don’t know. But I think it was reasonable for John to conclude that it won’t save nearly as many lives as some modelers and politicians would have us believe.

It seems implausible that in Britain, the ways in which staying at home reduces fatalities (as described above) can swing the number of deaths from around 500,000 to fewer than 20,000, as Dr. Neil Ferguson’s models indicate. And it seems absurd to suppose that staying at home in Minnesota will reduce the death total there from more than 70,000 (as the governor’s model apparently forecasts) to a little more than 1,000 (as a University of Washington model, IHME) predicts.

In absolute numbers, staying at home might well produce a substantial reduction in deaths without decreasing the total number of infections. But I doubt it will produce such a reduction in large multiples.

This raises the question of whether such orders are desirable, given their economic impact. More acutely, it raises the question of how long such orders should remain in place.

Yesterday, I learned from one of my daughters that Ralph Northam, the governor of Virginia (Mr. Black Face himself), has directed that citizens of the Commonwealth stay at home until June 10. Virginians would surely balk at an order of this duration if informed that complying won’t reduce the odds of them becoming infected, but will only delay the date of infection. This is particularly true given that a very high percentage of those infected won’t die from the virus even if hospitals are flooded.

But is it really the case that staying at home has no effect on the number of infections (absent a “hot weather” effect of which we are unsure)? Would all of the 77 people said to have become infected at a Biotech conference in Boston have been infected eventually, even absent the conference and even if they stayed at home for two and a half months? Would all of the hundreds of people in South Korea said to have been infected by “Patient 31” after she attended two church services have been infected eventually anyway?

I’m not sure about Boston, but I believe most of the people in South Korea who were infected thanks to Patient 31 would have avoided infection had she stayed at home.

Why? Because South Korea was still in containment mode. In other words, it was (or is said to have been) effectively testing, tracking, and isolating. As I understand it, when a country or area is in that mode, infections on a large scale can be avoided, as apparently happened in South Korea.

The infected are identified through tracking and testing. Isolated, they either die or get better and (we think) are no longer capable of transmitting the virus. The rest of the population mostly avoids infection (though the tracking/testing/isolation cycle must be continued).

The problem in the U.S. is that, at least until recently, we didn’t have nearly enough tests to do tracking/testing/isolation. (For a good explanation of why that was, go here.) Now, it’s too late, at least in much of the country. Thus, we’re in “mitigation” mode, which means flattening the infection curve but not reducing total infections.

However, it may be possible that, by staying at home, we can get back to containment mode. While we self isolate, the infected die or get better and can (we think) no longer transmit the virus. Thus, the infection rate is sharply reduced, as is the number of now-current infections.

To be sure, not all infections will be extinguished even after months of sheltering in place, and once the stay-at-home order is lifted, the infected will be able to start spreading the virus rapidly. However, the number of now-current infections might be low enough that we can restore our missed opportunity to contain the virus through testing, tracking, and isolating the reduced number of carriers. (This assumes, of course, that we have enough tests. We should, by then.)

In this way, the sheltering in place will enable us not just to flatten the infection curve, but also to reduce the number of infections.

The purpose of this post is not to defend or attack stay-at-home orders in general or any such order in particular (okay, I am attacking the Virginia governor’s order). The purpose is to try to advance my understanding, and perhaps that of others, of the virtues and limits of such orders from a public health perspective. As always, the economic effects of such orders must also be considered.

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