Overall 1.14, outside of New York 1.18

One factor that affects daily totals at the covid tracking site that I rely on is that not all states have reported totals by the time that the site updates. Sometimes it means that it shows fewer deaths per day than the worldometers site, but today it is showing more, presumably because some state totals yesterday were reported late and showed up today in the covid tracking site.

Note that when New York “caught up” with about 4000 deaths from much earlier, the worldometers tallied them but the covidtracking site did not.

Anyway, I plan to wait until Tuesday to pronounce on the trend, if any.

1. Paul Romer wrote,

The simulated data here contrast policies that isolate people who test positive using four different assumptions about the quality of the test. Even a very bad test cuts the fraction of the population who are ultimately infected almost in half. And when I say bad, I mean bad – an 80% false negative rate

Pointer from commenter John Alcorn.

For a test-and-quarantine policy to be useful, you don’t have to pull every infected person out of circulation. Think of it as a race between how many infected people you pull out of circulation and how many people get infected by the folks who your test fails to catch. You come out ahead compared to doing nothing.

But a test can be bad the other way, easily producing one false positive for every true positive. You could easily end up quarantining one healthy person for every sick person. Of course, what we are doing now is at least as arbitrary.

Tyler Cowen points to a paper with a model (what else?) that supports doing testing and confining even when the tests are bad.

I’m sure it works well in the model. In the real world, I can think of a number of difficulties with execution. Show me a project management chart that includes all the steps needed before you can even start. Then with flawed tests, it takes much longer to get the benefits, and more costs are imposed on the false positives.

2. Henrik Salje and others write,

As of 14 April 2020, there had been 71,903 incident hospitalizations due to SARS-CoV-2 reported in France and 10,129 deaths in hospitals, with the east of the country and the capital, Paris, particularly affected. The mean age of hospitalized patients was 68y and the mean age of the deceased was 79y with 50.0% of hospitalizations occurring in individuals >70y and 81.6% of deaths within that age bracket; 56.2% of hospitalizations and 60.3% of deaths were male

Another Alcorn pointer. They try to get beyond numerator analysis and estimate the infection fatality rates for different demographic groups. But their methods struck me as sketchy, so I am just quoting the raw data.

3. Frances MK Williams and others write,

Here we report that 50% of the variance of ‘predicted covid-19’ phenotype is due to genetic factors. The current prevalence of ‘predicted covid-19’ is 2.9% of the population. Symptoms related to immune activation such as fever, delirium and fatigue have a heritability >35%. The symptom of anosmia, that we previously reported to be an important predictive symptom of covid-19, was also heritable at 48%. Symptomatic infection with SARS-CoV-2, rather than representing a purely stochastic event, is under host genetic influence to some extent and may reflect inter-individual variation in the host immune response. Viral infections typically lead to T cell activation with IL-1, IL-6 and TNF-α release causing flu-like symptoms such as fever. The genetic basis of this variability in response will provide important clues for therapeutics and lead to identification of groups at high risk of death, which is associated with a cytokine storm at 1-2 weeks after symptom onset

They use a twin-study method to estimate heritability. Another pointer from John Alcorn.

4. Veronique de Rugy and me on the credit line idea.

Roughly 99.9 percent of American firms, or 30 million, fit the definition of small business used by the Small Business Administration (SBA), and together these firms employ roughly 65 percent of American workers. The devastation of the small-business sector could therefore be disastrous for American families.

The stock market is relatively placid, and meanwhile a whole way of life seems about to go under for many people. That might not be sustainable.

I readily grant that if left to their own devices many individuals will make sub-optimal decisions, but primarily costing themselves and not others. I also believe that if individuals were left to their own devices we would not see anything close to what “re-opening the economy” sounds like. But giving decision-making power to President Trump and the various governors seems more obviously right to most other people than it does to me.

5. A data visualization, by state, based on the source I use to calculate 3DDRR. Pointer from Russ Roberts.

6. Olivier Blanchard writes,

a high inflation scenario requires the combination of three ingredients, each of which has a low probability of occurring in advanced economies. Put your own probabilities and multiply them: The resulting probability is very small. I asked some of my colleagues for their probabilities, and the product always came below 3 percent.

His high inflation scenario is one in which our government can no longer pay the bills except by printing money. That is actually a hyperinflation scenario, as I imagine Blanchard would agree. Even at a probability of less than 3 percent, Anti-fragile Arnold does not want to take those chances.

Overall, stayed at 1.18 Outside New York, edged up to 1.23

Aaron Lindsey’s chart.

Commenter Blink’s chart, showing the 7DDRR. Smooth, gradual decline, starting at the end of March, before you would expect the lockdowns to affect deaths, and lately becoming an agonizingly slow decline.

1. The mayor of Las Vegas does not want to order Casinos closed.

I think they can do whatever they want. Anti-fragile Arnold is not going. Las Vegas was never his cup of tea. But if Risky Randy wants to go, that does not affect Arnold.

A lot of people think of government as a parent. It should tell them what to do and what not to do, and it should give them money when they need it. I think that smart phones have really increased the proportion of the public that views the government in those terms, because politicians and family members both appear on the same screen.

And in a Twitter world, people don’t take time to reflect. In Kahneman’s terms, their emotional System 1 is very pronounced and their reflective System 2 doesn’t get activated.

2. The Sacramento Bee reports,

Following Monday’s protest at the state Capitol where demonstrators defied Gov. Gavin Newsom’s orders banning large gatherings, the California Highway Patrol says it will no longer issue permits for events at any state properties, including the Capitol.

You knew this was coming. If we still had an American Civil Liberties Union, they would fight for freedom of assembly. But now I wonder if they are on the other side.

3. Nicolas Banholzer and others write,

The closure of venues is associated with a reduction in the number of new cases by 33 % (95% credible interval [CrI] 16–47 %). The reduction is lower for work bans on non-essential business activities (28 %; 95% CrI 10–42 %) and border closures (26 %; 95% CrI 13–37 %). School closures yield a reduction of only 11 % (95% CrI 0–27 %) and its relative impact is one of the lowest among the various policy measures considered in this analysis

They also look at the marginal effect of a lockdown, defined as only letting people leave home for essential purposes. This they find is even lower than the effect of school closings. Pointer from John Alcorn.

4. John Kay writes,

Despite the passage of four months since the first known human cases of COVID-19, our public-health officials remain committed to policies that reflect no clear understanding as to whether it is one-off ballistic droplet payloads or clouds of fine aerosols that pose the greatest risk—or even how these two modes compare to the possibility of indirect infection through contaminated surfaces (known as “fomites”).

Gaining such an understanding is absolutely critical to the task of tailoring emerging public-health measures and workplace policies, because the process of policy optimization depends entirely on which mechanism (if any) is dominant:

1. If large droplets are found to be a dominant mode of transmission, then the expanded use of masks and social distancing is critical, because the threat will be understood as emerging from the ballistic droplet flight connected to sneezing, coughing, and laboured breathing. We would also be urged to speak softly, avoid “coughing, blowing and sneezing,” or exhibiting any kind of agitated respiratory state in public, and angle their mouths downward when speaking.

2. If lingering clouds of tiny aerosol droplets are found to be a dominant mode of transmission, on the other hand, then the focus on sneeze ballistics and the precise geometric delineation of social distancing protocols become somewhat less important—since particles that remain indefinitely suspended in an airborne state can travel over large distances through the normal processes of natural convection and gas diffusion. In this case, we would need to prioritize the use of outdoor spaces (where aerosols are more quickly swept away) and improve the ventilation of indoor spaces.

3. If contaminated surfaces are found to be a dominant mode of transmission, then we would need to continue, and even expand, our current practice of fastidiously washing hands following contact with store-bought items and other outside surfaces; as well as wiping down delivered items with bleach solution or other disinfectants.

Pointer from Russ Roberts, via email. This is a great, great article. Kay takes pains to point out that he is not an epidemiologist or a virologist. But I would give him the highest praise. He is an epistemologist. Like Scott Alexander and like Russ, Kay focuses on what we might know and how we might know it.

Kay looked for evidence in the reports of “superspreader events,” and the evidence seems to come closer to (1) above. This is consistent with the beliefs that I have.

1. Ventilators do not produce good outcomes. My guess is that there are some people walking around today who are happy after having been on a ventilator, but I don’t like the odds. If I were to give an advanced directive for how I want to be treated, it would be “Do not ventilate.” There are other benefits of “flattening the curve,” but I would not promote “making sure we have an adequate supply of ventilators” as a major influence on policy.

In general, treatment is proving to be very difficult. I hope that we will discover a set of protocols and pharmaceuticals that will be effective. For now, the virus seems to have effects on the body that are complex and variable. I can imagine that it will turn out that no one treatment method works for everyone. It could take a very long time to sort this out.

2. I am not counting on finding a vaccine soon. On the one hand, scientists are trying very hard and using a variety of approaches. On the other hand, the track record of not finding vaccines for some other viruses is sobering.

3. Testing does not work well. The problem is that even a low rate of false negatives and false positives can be very misleading, both for the individual and for policy makers. I won’t go through the arithmetic here (I did some in this post). Because of the way that seemingly small rates of false negatives and false positives undermine the efficacy of testing, I doubt that “test, track and trace” is the main way that Asian countries have contained the virus.

4. It is worse than the flu. I never doubted this, and very early on I attacked the point of view that this is just like an ordinary flu. But if you still want to hold onto that view, ask health care workers what they are seeing. Or wait a couple weeks until the number of deaths in the U.S. has doubled again.

5. The differences in severity by age group are staggering. It is catastrophically worse than the flu for patients in nursing homes. It may or may not be worse than the flu for people in their twenties, pending studies of long-term effects.

6. Close contact in enclosed spaces is a much more important transmission mechanism than doorknob effects. I don’t care any more that “the virus can live on surfaces for hours.” Case studies of how people got the disease point to personal contact and/or HVAC (heating and airconditioning).

7. Social distancing works less well than one would hope. That is, while it seems as though you can detect a bit of slowdown in infections in times/places where social distancing increased, the differences are not nearly as dramatic as the age differences or the Asian/Western difference. I am afraid that as a defensive system, social distancing as we practice it leaves too many gaps, especially around nursing homes and sectors that are essential, such as health care and food. People’s impulse to shelter in multi-generational families tends to undermine the benefits of social distancing–the “escape from New York” phenomenon.

To successfully drive down the infection rate close to zero, you need more drastic measures than what we have undertaken in the U.S. and Europe. You cannot let people leave home for “essential” purposes, but instead you have to deliver food rations via the army. You have to keep multi-generational families apart. If you want to quarantine infected people, you have to really do that in separate compounds, not in their homes. Maybe something like that can be enforced in Wuhan or Israel, but I would not want to even try it in this country. And even where it seems to work, the virus could come back.

8. A fresh-air lifestyle is good for you. I am struck by the low death rate among homeless people and in India. Those populations ought to be at high risk, and the only story I can come up with is that they don’t spend as much time as we do indoors with HVAC.

9. Masks are good for society. Places like Taiwan and Hong Kong, which have the sort of density conditions and indoor-living conditions that we have, nonetheless have performed much better. There are other differences in how they cope with the virus, but the contrast between East and West on mask-wearing stands out to me.

Those beliefs may or may not be correct. But I have tried to arrive at them by reading with an open mind. I do have strong political opinions, but I hope that I have not let those opinions drive what I believe about the virus.

Today, it edged up to 1.18 and outside New York it edged up to 1.22

As a reminder, this is the ratio of cumulative deaths as of today to that as of three days ago. The goal is to spot a dramatic drop in the spread rate as of a few weeks ago. My thinking is that testing protocols change too often to use reported cases as an indicator. But increasingly we read that reporting protocols for Covid deaths are variable. Some experts want to try to compute “excess deaths” by comparing each week to an average of the same week in past years. That is not a task that I want to take on.

Following the trend in the 3DDRR, I was much more optimistic two weeks ago than I am today. I want to see the ratio drop to something like 1.002, and it looks like it is going to take a long time to get there.

Arnold is anti-fragile. One house, one spouse. Defensive driver. He would rather not be infected with the virus now. He hopes that by the time he is infected there will be a safe and effective treatment.

Randy is a risk-taker. Likes to go 75 mph on his motorcycle. Thinks that people who eat to live have it backwards. He would rather meet friends at a crowded bar than worry about when he gets infected with the virus.

It is possible that Randy’s behavior imposes a cost on Arnold. That is, the more that Randy risks getting infected and infecting others, the more difficult it becomes for Arnold to avoid contact with people getting the virus. Instead of going to the grocery in the afternoon, Arnold feels like he has to order for delivery or else get up early in the morning to shop in the store while Randy and his friends are still hung over.

Is this additional cost enough to justify the government stepping in and closing the bar so that Randy cannot go there? I do not believe so. I think that government should stay out of it, and let Arnold and Randy make their own choices. Back when we were afraid that Randy could cause excess crowding in hospitals, there was a persuasive public-good argument to change his behavior. Now there isn’t.

Brian Doherty tries to steel-man “openers” (who want to end lockdowns) and “closers.”

Closers see and acknowledge the economic damage we are suffering, but see most of that damage already inherent in the unchecked spread of a disease that kills or seriously harms people to a greater extent than any we’ve dealt with in a century. They thus don’t see the economic problems solvable just by “opening up America.”

As an “opener,” I do not think that lifting restrictions will do a lot to help the economy. I have made that point repeatedly. I agree with the “closer” view that most of the damage comes from the virus itself and the understandable individual responses to it.

The “closer” side annoys me when their rhetoric is based on intentions rather than consequences. That is, they try to make it seem as though “openers” want people to get infected and “closers” don’t. But it is likely that the only margin on which lockdowns can make a difference is that they will make more people get infected later rather than sooner. The number of lives that can be saved by doing that is likely to be small, and it may even be negative. Particularly if almost all of the people whose infections get shifted into the future are healthy people who will get mild or asymptomatic cases, and meanwhile we fail to develop and implement an approach that protects nursing homes.

Overall, I am only mildly on the “opener” side. My problem with Lockdown Socialism is the socialism.

By socialism, I mean the money-printing orgy to have the government send feel-good stimulus checks to households while lavishing bailouts on banks and other large corporations, without raising taxes or cutting spending elsewhere. I also mean taking capital allocation out of the private sector and giving it to the Fed. Whatever the intentions of the backers of the “stimulus” or the “quantitive easing” might be, inflationary finance and turning the Fed into Gosplan are the most important consequences. And in this case, I am going to insist on judging the consequences, not just the intentions.

Another forecast gets bitten by the Tuesday effect? The Texas people were sure that we had passed the peak in one-day death rates. But today was the biggest one-day death rate, at least according to this tabulation.

The 3DDRR only went up a bit, to 1.17. Outside NY, it is at 1.21

The main point of tracking the 3DDRR is to get an idea of what the trend in infections was a few weeks earlier. And I don’t see any point at which you can argue that “Aha, this was when the lockdowns got going, and you can see that a few weeks later the spread rate started to plummet.”

Lockdowns started to become widespread around March 20. So we would expect the big decline in the increase in deaths to begin somewhere between April 5 and April 15. But if you look at the chart, the big decline in the death rate was taking place from around March 26 through April 6, and subsequently the declines have been more gradual.

Perhaps the lockdowns failed to dramatically reduce the overall spread rate. But I think that a more likely scenario is that they did slow the spread rate–among the population that is least likely to die from the disease. The overall death rate remained high, because we have not figured out how to protect the elderly, particularly in nursing homes.

If my hypothesis is correct, then a weekly series of random-sample tests in the population would show a sharp decline in the spread rate, but a demographic breakdown of deaths by week would show an increase in the proportion of deaths among the elderly. I know we don’t have the former data. Are the latter data available?