Last week, when their “health weather” map debuted, I noted that it was nifty but that it’d be nice to be able to see at a glance on the map whether fevers are becoming more or less common. Kinsa added that feature (“Trends”) yesterday.

As you can see above, there’s a band of counties in Colorado and New Mexico that are showing a modest increase but otherwise the fever rate is declining practically everywhere coast to coast. Dark blue areas reflect the steepest decline. Check out L.A.:

Not only are they not (yet) seeing atypical rates of fever, they’re waaaaaay below where Kinsa’s historical data would project them to be in a normal year. What’s happening here, one would think, is that the social distancing being practiced by locals is sharply reducing the total number of seasonal infections caused by all “influenza-like illnesses.” COVID-19 isn’t the only bug out there; the flu is circulating, as are other well-known and milder forms of coronavirus. Because Kinsa can only measure fevers and not the underlying cause, it can’t say definitively that rates of infection by COVID-19 specifically are decreasing. It’s possible that that rate is still rising but is being offset (and then some) in their data by dramatically declining rates of infection by all other forms of “influenza-like illness.” The overall trend is downward but maybe not the particular trend for COVID-19, especially since it’s more contagious than flu. And that’s the one we care about.

But. Obviously it’s possible that social distancing is driving down the infection rate of COVID-19 too. That’s what these lockdowns are designed to do, after all. The self-isolation strategy is — probably — working, too late for New York but hopefully not too late for a lot of places. Even Florida, the most worrisome fever hot spot in last week’s Kinsa data, is beginning to cool off.

Seems like a good moment, then, to flush this promising collective effort down the toilet and start owning the libs again by hastily sending people back to work:

https://twitter.com/realDonaldTrump/status/1242905328209080331

“ASAP” is correct but I’m guessing his idea of when “ASAP” is and when Fauci’s idea of it is diverge starkly. Here’s a sneak preview of our country lifting isolation measures before local health departments are ready:

This dickhead who licked a toilet seat for the #CoronaVirusChallenge on Tik Tok has tested positive for COVID-19 and been suspended from twitter.

Darwin is working overtime for this year’s awards show pic.twitter.com/6V4k4RMm35

— KFC (@KFCBarstool) March 25, 2020

There’s another, more radical way to interpret the Kinsa data. What if it’s not social distancing that’s driving down fever rates? What if much of the country has already been infected by coronavirus and begun to recover, as the Oxford study I wrote about last night speculated? That study theorized that (a) coronavirus may be spreading at lightning speed, (b) half the population of Great Britain may already have it, and (c) the disease is actually exceedingly mild in almost everyone who’s infected, to the point that few people who’ve gotten it will ever even know they’ve had it. There are severe cases, of course, as American doctors and nurses are seeing firsthand now, but the severe cases might not be one-in-50 infections. They may be more like one-in-5,000 infections. There may be a crunch at hospitals now only because such a tremendously large number of people in NYC have been infected that even the tiny percentage of severe infections currently represents a big raw number.

A piece in the Wall Street Journal echoes that theory. We’re making BIG decisions as a country based on an assumption about how dangerous COVID-19 is to most of the population. If one in 50 or so need hospital treatment then we really are staring at a potentially apocalyptic load on our system and we need to do everything we can to start managing the spread for months to come. If only one in 5,000 need hospital treatment, then many millions of people may already have recovered and gained immunity, with no “second wave” on the way this fall. What we’ll experience over the next month or so may be the worst of it, with herd immunity shortly to follow.

Fear of Covid-19 is based on its high estimated case fatality rate—2% to 4% of people with confirmed Covid-19 have died, according to the World Health Organization and others. So if 100 million Americans ultimately get the disease, two million to four million could die. We believe that estimate is deeply flawed. The true fatality rate is the portion of those infected who die, not the deaths from identified positive cases…

[T]he northeastern Italian town of Vò, near the provincial capital of Padua. On March 6, all 3,300 people of Vò were tested, and 90 were positive, a prevalence of 2.7%. Applying that prevalence to the whole province (population 955,000), which had 198 reported cases, suggests there were actually 26,000 infections at that time. That’s more than 130-fold the number of actual reported cases. Since Italy’s case fatality rate of 8% is estimated using the confirmed cases, the real fatality rate could in fact be closer to 0.06%…

The epidemic started in China sometime in November or December. The first confirmed U.S. cases included a person who traveled from Wuhan on Jan. 15, and it is likely that the virus entered before that: Tens of thousands of people traveled from Wuhan to the U.S. in December. Existing evidence suggests that the virus is highly transmissible and that the number of infections doubles roughly every three days. An epidemic seed on Jan. 1 implies that by March 9 about six million people in the U.S. would have been infected. As of March 23, according to the Centers for Disease Control and Prevention, there were 499 Covid-19 deaths in the U.S. If our surmise of six million cases is accurate, that’s a mortality rate of 0.01%, assuming a two week lag between infection and death. This is one-tenth of the flu mortality rate of 0.1%. Such a low death rate would be cause for optimism.

That’s the same argument made in the Oxford study, and the same made by Stanford epidemiologist John Ioannidis in a widely read piece last week. We know the numerator in calculating the fatality rate from COVID-19; the momentous question is what the denominator is. What if the new coronavirus is extremely infectious, almost always mild (unless, perhaps, you get a high dose of it like front-line health-care workers do), but severe in some freak cases? There may be enough infected people out there, say the authors, that we should expect a death toll in the range of 20,000 to 40,000 people, which is serious business but in line with the death toll from the flu and orders of magnitude below the death toll of two million people predicted in some worst-case scenarios. The reason hospitals are being crushed by COVID-19 when they aren’t crushed every year by the flu is because we have few ways of slowing down transmission of COVID-19 like we do with the flu (vaccines, naturally gained immunity, and so on). An enormous number of people are sick with it at the same time. It’s just that only a very unlucky few actually end up feeling it.

That’s not to minimize what New York is dealing with now. It’s bad. But the falling fever rates on the Kinsa map could be partially explained by many more people than we realize having already contracted the disease and now reached the recovery stage.

Two questions, though:

1. If the virus spreads like lightning, why weren’t more people quarantined on cruise ships infected? Many were, but when Dr. Jeremy Faust offered his theory a few weeks ago that COVID-19 is less lethal than we think, even he noted how surprisingly low the rate of infection onboard the Diamond Princess cruise ship was (705 of 3,711 passengers). Given the close quarters and recirculated air, you would think they might all have been quickly infected, not just 20 percent or so. Only six infected people died, but that’s close to one percent, not the .01 percent rate about which the Journal piece speculates.

2. Why haven’t we seen any atypical rates of fever in L.A. yet, per the Kinsa data? A virus as contagious as the Oxford study imagines should have infected many people in a city that size already, one would think, and some small but detectable percentage of that group should have developed fevers. Shouldn’t there be some recent spike? If not, then maybe fewer people have been infected than the Oxford study would imagine, which means maybe the virus is less contagious than it imagines, which means maybe the death rate isn’t as low as we hope.

In lieu of an exit question, read this grim piece about what the next few months will look like if the theories about a massive undetected population of infected people are wrong. Quote: “A recent analysis from the University of Pennsylvania estimated that even if social-distancing measures can reduce infection rates by 95 percent, 960,000 Americans will still need intensive care. There are only about 180,000 ventilators in the U.S. and, more pertinently, only enough respiratory therapists and critical-care staff to safely look after 100,000 ventilated patients. Abandoning social distancing would be foolish. Abandoning it now, when tests and protective equipment are still scarce, would be catastrophic.”