Kevin Warn/ZUMA

The picture above, from my neighboring city of Huntington Beach, shows a typical protest against COVID-19 lockdowns. As you can see, nobody is wearing masks. Of course not! Live free or die!

Some of these people are just nuts and there’s nothing we can do about them. But I wonder if some of them are just misinformed? Hear me out on this. Your typical tea partier feels like the government should leave them alone: if they want to risk getting sick, then that’s their right. But that’s not what masks are for. They’re to keep you from getting other people sick—which can happen even if you’re feeling fine and don’t think you’re infected with the coronavirus. I think it’s possible that knowing this would actually motivate them to be good citizens more effectively.

I know this sounds kind of weird, and maybe I’m totally off base. But in general—and especially for libertarian-inflected tea party activists—I think people are more likely to do the right thing if they believe it helps other people. Conversely, if it only helps themselves, they figure it should be solely up to them since it doesn’t hurt anyone else if they go maskless.¹

We shouldn’t underestimate how difficult it is to get everyone into masks. They’re uncomfortable. They feel kind of stupid. President Trump is pretty unenthusiastic about them. But they’re also cheap and probably fairly effective. We really need to do a better job of selling them.

¹This isn’t right, but it’s probably too complicated to explain to most people. KISS.

Why did President Trump suddenly announce that he planned to cut off all immigration to the United States? Today the media will undoubtedly flood us with explanations, but I think we all know the real one: he’s got nothing in the pipeline to deal with COVID-19 so he resorted to the only thing he knows: appealing to the bigotry of his base. That’s it.

Any other questions?

It is perhaps one of the great sins of blogging that we tend to focus much more on stuff we disagree with than on stuff we think is great. Take Sean Illing’s interview with Annie Lowrey today about the plight of millennials. I think Lowrey is mostly right, but instead I’m going to focus on the one thing I think is way overstated:

There’s a huge economic body of literature that shows that graduating into a recession, like millennials did in 2008 and 2009, is unusually bad.

The part I disagree with is “millennials,” and it’s not just pedantic. First off, if we’re talking about college graduates, as we are here, that’s only 37 percent of the total cohort. Second, if we generously take the Great Recession to last from 2009 to 2013 (by which point unemployment among college grads was down to 3 percent), only about 31 percent of millennials graduated during the recession. So the share of millennials who suffered from graduating into a bad job market is about 11 percent. That’s not by any stretch “millennials.” It’s a tiny share of millennials.

I say this speaking as someone who really was unlucky enough to graduate into a severe recession in 1981. And guess what? I couldn’t find a job and ended up working at Radio Shack until the economy recovered. I did OK in the end, but that was hardly guaranteed. That said, no one would say that “boomers graduated into a recession.” That would sound ridiculous because it is ridiculous. A few boomers here and there graduated into a recession, but most of us didn’t.

Oh, and by the time I was in my late 20s and looking to buy a house, the housing market here in Southern California was booming. Millennials are hardly the only ones who have had to face that.

Now, millennials have clearly gotten screwed in general by the sluggish growth of middle-class wages, which was worse after 2000 than it was for my generation. On the other hand, the Reagan Recession was worse for wages of 25-34-year-olds than the Great Recession:

Boomers who graduated into the Reagan Recession saw their wages drop 15 percent from their peak, and it took 15 years for wages to recover. Millennials who graduated into the Great Recession saw their wages drop 8 percent from their peak and it took ten years for wages to recover.

Millennials have gotten squeezed in lots of ways. The housing market in big cities has been tough. Student debt has skyrocketed. But it’s wise not to overstate the impact of recessions. It’s a small fraction of millennials who graduated into a recession, and it affected them less than boomers who graduated into the Reagan Recession.

The New York Times ran a fascinating op-ed on Monday, and I’m surprised that it hasn’t gotten more attention. Here’s the nickel summary: a hotshot ER doctor volunteered to spend time at Bellevue Hospital in Manhattan and discovered something odd. Practically everyone he saw had pneumonia caused by COVID-19:

Even patients without respiratory complaints had Covid pneumonia. The patient stabbed in the shoulder, whom we X-rayed because we worried he had a collapsed lung, actually had Covid pneumonia. In patients on whom we did CT scans because they were injured in falls, we coincidentally found Covid pneumonia. Elderly patients who had passed out for unknown reasons and a number of diabetic patients were found to have it.

And here is what really surprised us: These patients did not report any sensation of breathing problems, even though their chest X-rays showed diffuse pneumonia and their oxygen was below normal. How could this be?

You can—and should!—click the link to read the details, but the short answer turns out to be that COVID-19 attacks the lungs in an unusual way: it causes the air sacs to collapse and oxygen levels to fall, but the lungs still expel carbon dioxide normally. Since it’s carbon dioxide buildup that causes you to feel short of breath, patients had never even noticed anything was wrong:

A vast majority of Covid pneumonia patients I met had remarkably low oxygen saturations at triage — seemingly incompatible with life — but they were using their cellphones as we put them on monitors….Patients compensate for the low oxygen in their blood by breathing faster and deeper — and this happens without their realizing it….By the time patients have noticeable trouble breathing and present to the hospital with dangerously low oxygen levels, many will ultimately require a ventilator.

As you know, about 80 percent of people with COVID-19 have either mild symptoms or no symptoms. But the other 20 percent develop pneumonia and many end up on ventilators and eventually die. The problem is that they don’t feel anything for the first week, and by the time they do it’s too late. So how can we catch these cases earlier? With this:

This is a pulse oximeter, and it measures the level of oxygenation in your blood. You probably get a quick oxygenation test every time you see a doctor. So the answer is: test your blood oxygenation every day. If it falls below normal levels, get to an ER and get tested for COVID-19. Your chances of survival are way higher if you can get to it early.

There’s good news and bad news here. The good news is that pulse oximeters are cheap. You can get one on Amazon for forty bucks. The bad news is that if this becomes popular, I guarantee that we will soon realize we have a huge shortage of pulse oximeters. After all, who would have guessed we might need tens of millions of them for a weird virus that kills the lungs without giving any warning signs?

But there are other options. This might sound offbeat, but hospitals could have drive-up testing. Just zip in daily, stick your finger in a pulse oximeter for a few seconds, and go home. There are undoubtedly other ways of expanding oxygenation testing too.

It’s worth noting that this is not a substitute for normal COVID-19 testing. If you have no symptoms, your oxygenation level will be normal. However, regular testing would give us a head start on those patients who are likely to have the most serious reaction and the highest chance of dying. So why aren’t we doing this?

POSTSCRIPT: Consider this to be in the “news you can use” category. These things are cheap enough that I figure I’ll buy one tomorrow. Maybe you should too. And maybe buy one for any elderly relatives you know? They’re likely to be sold out pretty soon.

ANOTHER POSTSCRIPT: The fact that an ER doctor in New York is routinely finding COVID-19 in patients who come in for unrelated problems is yet another sign that the infection rate of the coronavirus may be much higher than we think.

Here’s the coronavirus death toll through April 20. Please keep in mind that each dot represents a 6-day rolling average. Spain, for example, recorded 399 deaths on Monday, or 8.5 deaths per million. However, the average over the past six days is 9.9 deaths per million. This is why the dots in my charts don’t match up precisely with charts that simply use the daily numbers.

(And why use a 6-day rolling average? Two reasons. First, there’s so much noise in the daily numbers that it’s often hard to detect much of a trend. Averaging helps to make the trend more visible. Second, it’s a bad idea to overreact to a single day’s worth of data. Using a 6-day average prevents you from staring endlessly at the daily data trying to suss out something that might represent a glimmer of a start to an inflection in the trendline. Please don’t do this. I guarantee it’s a mug’s game.)

By the way, I continue to get loads of email from Sweden. I absolutely love this, and even though I don’t answer much of it I want to assure my Swedish fans that I read all of it. The latest news is that (apparently) Johns Hopkins records deaths on the day they get the data. However, the Swedish authorities record deaths on the day the death actually happened. If you use the Swedish data, it looks a little more like Sweden might be close to peaking.

This puts me in a bind. On the one hand, I want to use the best data. On the other hand, I also want to use data that’s comparable from country to country, and simply using the JH data is the best way to do that. I’m already using a different source for the US data¹ thanks to New York City’s newly changed data reporting, and I don’t want to get in the habit of doing stuff like this for everyone. For now, then, I’m going to stick with the Johns Hopkins data. I’ll mention caveats in text if they seem important.

The raw data from Johns Hopkins is here.

¹From the COVID Tracking Project.

Igor Golovniov/SOPA Images via ZUMA

You have perhaps seen on news programs that there are already several dozen potential coronavirus vaccines in development already. Some of them have even been given to people! So what’s the deal with the 12-18 month timeline to get them ready for widespread deployment? Here’s a quick primer:

Most vaccines work by using a weakened or dead version of the virus, which stimulates your immune system into creating antibodies without actually making you sick. However, it generally takes 3-6 months just to develop these attenuated viruses, and we don’t have the time for that.

• So instead many groups are developing vaccines based on RNA or DNA that directly recreate the proteins found on the coronavirus surface, which should trigger your immune system into creating antibodies. Unfortunately, this has never been done before and no one knows for sure if it will work. It will take 3-6 months to perform animal testing that determines whether this kind of vaccine really does trigger the immune system adequately.
• Coronaviruses have an odd property that can cause vaccines to make things worse, rather than better. This happened with some trial vaccines for SARS, for example. Testing to make sure this doesn’t happen eats up another three months.
• Then you have to test for safety. This is a Phase 1 clinical trial and it’s important. We’ve had experience with vaccines that turned out to be deadly, and this phase of testing needs to demonstrate that the vaccine really is safer than just getting COVID-19 in the first place. Even at an accelerated pace, this eats up another 3-6 months.
• Then you need a Phase 2 trial that checks to see if the vaccine actually produces immune system activity in humans. If it does, it’s possible that it would be approved for emergency use while final trials were taking place. This is yet another 3-6 months.
• Finally, you need to manufacture billions of doses. Even if manufacturing facilities are pre-built and ready to go, this is almost certainly another 3-6 months.

This adds up to 15-27 months. Since new techniques are being used and we have never developed a coronavirus vaccine before, the low end of this estimate is unlikely. Even with lots of different groups pursuing lots of different avenues, 18-24 months is a lot more likely. Maybe a little less for emergency use on a smallish number of people. (And who would pick these lucky folks?) Maybe more if we’re being too optimistic about how well these trials will go.

Sure, that looks like a lot of storage. But it's mostly already spoken for.Shane Bevel/ZUMAPRESS

We’ve all had our fun, but after watching the evening news today I have to ask: Everyone knows that the price of oil didn’t really fall to negative $40 yesterday, right?

All that happened was that the price of one particular futures contract fell below zero. This contract comes due on Tuesday and requires the buyer to take physical possession of the oil. Unfortunately, thanks to the COVID-19 oil glut, there’s little storage available and its price has skyrocketed. Under these extreme conditions, taking delivery of the oil and buying storage for it would be a guaranteed huge loss. This caused many investors and speculators to panic and dump their contracts at any price—even if they had to pay someone to take it off their hands.

Anyway, that’s it. The price of one particular futures contract, late in the day, was a victim of panic selling. The price of oil in general was largely unaffected. It’s still dropping, mind you, but not in any kind of dramatic way.

At least the TSA lines are short now.Jack Kurtz/ZUMA

Here’s a headline in the LA Times today:

The accompanying story asks some good questions about how the airline industry is handling COVID-19, but over the course of nearly 2,000 words it doesn’t once tell us what we really need to know: is this a high number? Here’s a very rough guess:

• The BLS estimates there are about 400,000 airline workers (pilots, flight attendants, air traffic controllers, etc.) in the US. This means that 15 deaths comes to 0.0037 percent of the total workforce.
• There are 170 million working-age folks in the United States. Of those, about 7,000 have died of COVID-19. A little less than half of those deaths have been in the past nine days, so figure 3,000 deaths or so. That’s 0.0017 percent.

This is just the vaguest kind of horseback guesswork, but it suggests that airline workers might be dying at twice the rate of other workers. Then again, there’s this:

An American Airlines gate agent at Los Angeles International Airport, an aircraft mechanic at a Tulsa, Okla., airport, a baggage handler at Dallas-Fort Worth and a food services manager at JFK airport in New York are all counted among the recent dead. And the human toll of air travel is mounting.

We’re including baggage handlers and food services folks? That might double the total number of workers, in which case the death rate in the airline industry would be entirely average. Then again, I don’t know how many airline workers have been furloughed. Maybe there are only 200,000 left these days, in which case we’re back to airline workers dying at twice the rate of other workers. Oh, and the count of deaths could be way off on both sides.

The point here isn’t whether my guesswork is accurate. It could easily be off by a factor of two or more. The point is that you have to at least ask the question and get some experts to weigh in. If you don’t, you have no idea if there’s really a story here in the first place. If, in fact, it turns out that the fatality rate in the airline industry is just average, then there’s no reason it should affect whether planes are still flying.¹

¹There are still plenty of other reasons to argue that planes shouldn’t be flying—wasted fuel, etc.—but COVID-19 deaths wouldn’t be one of them.

Ringo Chiu/ZUMA

A week ago we got the results of a study in Santa Clara County that tested a few thousand people for the presence of COVID-19 antibodies. If you test positive, it means you were infected at some point even if you didn’t know it. The study’s conclusion was that the true infection rate was far higher than we’ve assumed until now.

However, critics pounced. Aside from the usual stuff about proper controls and so forth, the most serious criticism was the false positive rate of the antibody test that was used: it was high enough that it meant the results might be nonsense. The error bars were so wide they didn’t even rule out the possibility that the infection rate was zero.

Now we have a new study, this time in Los Angeles County. The recruiting method was a little better, and LA is probably a more representative county than Santa Clara, so that’s all good:

Based on results of the first round of testing, the research team estimates that approximately 4.1% of the county’s adult population has antibody to the virus. Adjusting this estimate for statistical margin of error implies about 2.8% to 5.6% of the county’s adult population has antibody to the virus—which translates to approximately 221,000 to 442,000 adults in the county who have had the infection. That estimate is 28 to 55 times higher than the 7,994 confirmed cases of COVID-19 reported to the county by the time of the study in early April. The number of COVID-related deaths in the county has now surpassed 600.

Shazam! They figure the true infection rate is 28-55 times higher than the “official” case estimate. That’s a lot.

But . . . I’m not ready to take this at face value yet. First, the only thing that’s available right now is a press release, not the paper itself. Second, the researchers used the same antibody test with the same false positive rate as the Santa Clara folks. Third, even though the critique of the Santa Clara results is well known, it’s not even mentioned in the writeup. Fourth, they seem to take some care to avoid telling us the sample size. Even press releases usually do that.

Now, having said that, if we keep getting results like this then the margin of error is going to steadily decrease and the point estimates are going to be more reliable. I wouldn’t be surprised at all if the true infection rate turns out to be not just 10x the official case estimates but more like 20-40x.

Still, once burned, twice shy. I want some more details on this study before I accept its results.

JUST TO REMIND YOU: The reason this is important is that if the infection rate is 20x higher than we thought, it means the fatality rate is 20x lower than we thought. That has huge implications for public policy.

This is a picture of Marble Canyon, taken from the Navajo Bridge spanning the Colorado River. I stopped here even though the sun was going down and I was late getting to my actual destination, Horseshoe Bend. Was it worth it? I’m still not sure. This is a pretty picture, but if I had gotten to Horseshoe Bend 20 minutes earlier I’ll bet my picture of that would have been a lot better. I suppose I’ll never know.