Author Archives: Arnold Kling

Vaccine testing and the trolley problem

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As you know, I am not ready to proclaim a vaccine a success based on what I see as a small number of cases in the sample population. A lot of you think I am wrong about that, and I hope I am.

But my intuition is still that there is something unsatisfying about the testing protocol.

The actual protocol seems to be to give the vaccine to a large sample and wait for people to get exposed to the virus as they go about their normal business. My inclination is to deliberately expose a smaller sample to the virus and see how well the vaccine works.

One argument against deliberate exposure is that the response of people to deliberate exposure may not be the same as their response to normal-business exposure.

But in favor of deliberate exposure:

–you can clearly test how well the vaccine does in a specific populations, such as people with and without obesity.
–you can clearly test how well the vaccine does at two levels of viral load.
–you can get results quickly, rather than wait for months for people in the sample population to become exposed the the virus
–you could identify the main contacts of people to whom the virus is exposed and make sure that the vaccine reduces spreading.

Whether you deliberately expose 100 people or wait for 100 cases to emerge, that is still 100 cases either way. It seems to me that deliberate exposure is equivalent to throwing the switch in the trolley problem. Those 100 cases are 100 cases either way, it’s just that the experimenter didn’t specifically choose them.

I think that the case for deliberate exposure as a testing protocol ends up being pretty strong. What am I missing?

UPDATE: a reader points me to a story about a proposed challenge trial.

Challenge trials are controversial because of the risks involved with infecting patients with a potentially lethal virus

But again I ask, what is the difference between infecting a group of people and waiting for a group of people to become infected?

Virus policy and inflation

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Subsidize demand, restrict supply.

In Specialization and Trade, I make the claim that most government intervention does not conform to the textbook model of dealing with market failure. In that model, when the market produces too little of something (use of masks in a pandemic), the government is supposed to subsidize either supply or demand. When the market produces too much of something (air pollution from automobiles), the government should penalize either supply or demand.

In practice, politicians don’t follow the textbooks. They obey interest groups. Every interest group once to see its supply restricted and its demand subsidized. So the national government subsidizes home purchases, but then at a local level it restricts housing construction. The government subsidizes the demand for health care and higher education, but it uses licensing and accreditation rules to restrict supply.

It occurs to me that virus policy is “subsidize demand, restrict supply” writ large. Lockdown-type rules restrict supply. And “stimulus” subsidizes demand.

What do you get when you subsidize demand and restrict supply? Higher prices. Eventually.

Further thoughts on a vaccine

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UPDATE: Thanks to a commenter for finding the study protocol for the Pfizer study. That helps a lot.

1. If you assume that everyone is identical, and if you want to try to eradicate the virus by giving everyone the vaccine, then you don’t need to show that it is 90 percent effective. My guess is that 20 percent effectiveness will do the trick. The problem you face is a PR problem. Most people hear the word “vaccine” and think “super-power that keeps me from getting sick.” But to be honest you would have to say “You might still get sick, but if everyone takes the vaccine and also exercises some degree of precaution, the virus will die out and eventually you won’t have to worry about it.”

2. But if your goal with the virus is to target high-risk populations or people whose working conditions might expose them to high viral loads and make them safe, then you want the super-power story to be true. I would want to see that high viral load does not degrade the effectiveness of the vaccine, and I would want to see that being in a high-risk category does not degrade the effectiveness of the vaccine.

3. The most I can find out about the Pfizer study is from this press release.

The first primary objective analysis is based on 170 cases of COVID-19, as specified in the study protocol, of which 162 cases of COVID-19 were observed in the placebo group versus 8 cases in the BNT162b2 group. Efficacy was consistent across age, gender, race and ethnicity demographics. The observed efficacy in adults over 65 years of age was over 94%.

There were 10 severe cases of COVID-19 observed in the trial, with nine of the cases occurring in the placebo group and one in the BNT162b2 vaccinated group.

There are a number of comparisons you could make between the placebo group and the treatment group.

–number of people who tested positive for the virus
–number of people who tested positive and showed symptoms (this appears to be what they used)
–number of “severe cases” (this was reported in the press release)
–number of hospitalizations (is this the same as “severe cases”?)
–number of deaths

Suppose that nobody in either group died from the virus. A headline that says “Vaccine prevents zero deaths” would not be very inspiring, would it?

When a study can look at many possible outcome measures and chooses to report only those that favor the drug, this is known as p-hacking. I don’t know that Pfizer was p-hacking, but I don’t know that they weren’t.

UPDATE: the protocol specified the outcome measures in advance, so no p-hacking.

The context here is one in which people who spread the virus differ greatly in their ability to spread it (at least, that seems like a good guess), and people who come in contact with the virus differ greatly in the extent to which they get sick. In that context, a ratio of 162/22000 compared to 8/22000 is promising but not definitive. I would be much more impressed if it were 1620/22000 and 80/22000. With the smaller numbers, I can think of a dozen ways to get those results without the vaccine actually being effective.

UPDATE: Now that I have seen the protocol, I can go back to the first two points. For the purpose of trying to eradicate the virus with universal vaccination, you don’t need much efficacy. But I think you want to be really, really, confident that there is some efficacy, because otherwise you will have blown it with the public if your vaccine campaign does not eradicate the virus. If I were the public official in charge of making the decision, I would want to see a larger number of cases in the sample before I would make this kind of a bet.

For the purpose of protecting vulnerable populations, you need to conduct a different protocol, in my opinion. Again, you want to know how the vaccine does as viral load goes up and as vulnerability of the individual goes up. I think that would argue for a different study protocol altogether.

Testing a vaccine

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A follow-up/clarification to my earlier post:

I believe in what I call the Avalon-Hill model of how the virus affects people. That is, it depends on a combination of viral load and patient vulnerability. Accordingly, I would like to see a vaccine tested on various combinations of these factors. That means that the experimenter should control the viral load rather than leave it to chance in the context of selection bias (people who volunteer for the trial may be behaving in ways that reduce their probability of being exposed to high viral load).

In principle, that means assigning a high viral load to some high-risk subjects in both the control group and the placebo group. That could discomfit the experimenter, not to mention the experimental subjects.

But if you don’t do that, what have you learned? If the most severe cases in the real world come from people exposed to high viral loads, and almost no one in your trial was exposed to a high viral load, then you have at best shown that the vaccine is effective under circumstances where it is least needed.

Virus update

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1. I remain a vaccine skeptic. Consider these two recent reports.

First

Out of 170 adult volunteers in the nearly 44,000-subject trial who developed Covid-19 with at least one symptom, 162 received a placebo, while eight got the vaccine, Pfizer and BioNTech said.

Second

Ninety-five people in a 30,000-subject study developed Covid-19 with symptoms; of those, 90 had received a placebo and only five Moderna’s vaccine.

OK. Assume half received the placebo (Does anyone know the actual percent that received the placebo?). So with no vaccine, 162 out of 22,000 got the disease in the Pfizer study. That is less than 0.75 percent. 90 out of 15,000 got the disease in the Moderna study. That is 0.3 percent.

Extrapolate that to the entire population. Of 330 million people, if 0.5 percent get the disease, that would be 1.65 million people. If the fatality rate is 0.5 percent, then that would mean just over 8000 deaths, which is about one week’s worth in reality. If the whole country were like the sample that received the placebo, this disease would never have made it into the public consciousness.

Another way to look at it: The Pfizer study followed participants for more than three months, starting in late July. During that time, more than 6 million new U.S. cases were reported, or about 2 percent of the entire population (the percentage would be even higher if you exclude children from the numerator and the denominator). So more than twice as many people got it in the general population as got it in the placebo sample studied by Pfizer.

Still another way to look at it: the number of cases that emerged in the placebo population was less than what can emerge from a single super-spreader event. Apparently, there were zero super-spreader events in either study. So these studies tells us nothing about the ability of the vaccine to work against a super-spreader. I also suspect that they tell us almost nothing about the ability of the vaccine to work for vulnerable populations.

Maybe the vaccines are 90 percent effective, in which case it is easy to recommend them. Maybe they are 0 percent effective, in which case it is easy to dismiss them. But what if in reality they are 50-70 percent effective? That would create a dilemma. From a central planner perspective, you want everyone to take a vaccine even if it is only 50 percent effective, because that would dramatically slow the spread of the virus. But meanwhile, a lot of individuals who got the vaccine will still get sick and die. That would put the agencies in charge in an awkward position, without any credibility left to deal with the next pandemic.

2. While I am being contrarian, let me go after the “keep R below 1” theory. That is the theory that if we can get the reproduction rate below 1 and keep it there, we can eradicate the disease. Ergo, even a mostly-ineffective intervention, such as an inaccurate test, or an unreliable vaccine, or a mostly-useless lockdown, if it brings R below 1, can achieve eradication.

My problem with “keep R below 1” is that it is a representative-agent model. That is, it treats everyone the same, with identical probability of getting or spreading the disease. But in fact people differ greatly in terms of vulnerability and in terms of propensity to spread the disease. Inferences that “scientists” draw from the representative-agent model are generally bogus. I don’t trust anyone who would make policy based on a representative-agent model, and that includes anyone who uses the “keep R below 1” theory.

3. I am still not impressed with “the science.” They (scientists) are still arguing over the extent of asymptomatic transmission. They are still arguing about the effectiveness of masks. Katya Simon, to whom Tyler Cowen provides a link, writes,

Implement indoor mask mandates for public spaces. Outdoor mask mandates are ridiculous. COVID19 does not appear to transmit outdoors. Enjoy our great outdoors!

Heather Heying and Bret Weinstein say the same thing. But Cambridge Massachusetts, which is where a lot of leading-edge biological research takes place, is a paragon of outdoor mask-wearing.

They are still arguing about the effectiveness of lockdowns.

They are still arguing about how long immunity lasts.

They are still arguing about long-term effects.

I believe that they are still arguing about the mechanism by which the virus causes illness.

All of this reinforces my doubts that a vaccine will prove as effective in practice as it has in trials.

Note that many of the issues about which there are arguments could be clarified, if not completely settled, by careful controlled experiments. As I pointed out more than 6 months ago, experiments would be really useful, but the people you would count on to do them are not willing to do so.

Experimental results are signal. Pronouncements that are not based on experiments are noise. Don’t tell me to “listen to the science” when what I am being asked to listen to is noise.

4. So where are we today? As of the other day, the average daily death totals were higher than at any time since early May. (Tyler Cowen shows a chart.) Unless you are more impressed than I am about the vaccine test results, it is appropriate to be a virus pessimist right now.

I think that there is at least a 25 percent chance that we will be as fearful of the virus a year from now as we are now. And if our fears have declined, this may be due mostly to a change in reporting about the virus. Perhaps someone with congestive heart failure who dies with the virus will no longer be counted as a virus death. Perhaps the press will no longer report cases of long-term damage from the virus. Should such a change in reporting take place, a cynic might call it the “Biden effect.”

Data on the black family

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Erol Ricketts writes,

What is strikingly different in 1950 is that blacks overtake whites in their level of urbanization. After 1950, blacks become more urbanized than whites, and they continue to urbanize. Whites de-urbanized after 1970. Blacks moved to the cities after World War II, en masse. And it is after this move that severe family-formation problems began to emerge. The data suggest that the clues to recent family-formation problems among blacks are to be found in the circumstances of black urbanization after 1950.

Pointer from John Alcorn. The data in the paper show that before 1950, marriage rates of black women were even higher than those of white women.

What happened to the black family?

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This question is posed, and not answered, in the podcast in which Loury, McWhorter, Steele, and Steele discuss the latter’s Michael Brown documentary.

UPDATE: transcript of the conversation

Conservatives want to blame the War on Poverty and welfare programs. This story is exemplary normative sociology–the study of what you want the cause of a problem to be. The problem is that the dissolution of black families preceded the War on Poverty.

Loury points out that the black family was stronger in 1930 than in 1960. What happened in the meantime?

My thought is that what happened was the Great Migration of blacks from the rural south to the urban north. One can imagine that this produced a cultural shock that could have weakened marriages through a number of channels.

1. Lowering the status of the black matriarch. Your rejected your grandmother’s rural ways, so she could not apply moral pressure on you to follow marital norms.

2. Greater inequality among black males, weakening marriage. The poorer males are undesirable husbands, and the richer males have leverage to disdain monogamy.

3. Communities no longer church-centric, so that there is less social pressure to follow marital norms.

4. Availability of many more opportunities to have sex outside of marriage.

Trying to tell this migration story leads me to ask why a similar drift toward family breakdown did not occur among Italians, Irish, and others when they migrated in large numbers to the U.S. Perhaps they just had the good fortune to undertake these migrations in an earlier era. People who arrived between 1880 and 1930 had a very hard life, with little time to pursue sex outside of marriage. Also, this was before Freud and others had convinced people of the need to be less repressed about sex.

The state of the electorate

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1. A fascinating interview with Democratic pollster David Schor, which you may have already seen. Hard to excerpt, but here is one:

some of the factors that traditionally have been theorized to make people more conservative as they age — having kids, getting married, etc. — are complicated. Fertility rates are substantially lower than they were 10 or 15 years ago, to the point where it is statistically important. And at the same time, the median age at first marriage is like a decade higher than it was 15 years ago. That means that Democrats have more time and can own a longer part of voters’ life cycles.

He does see the Democratic Party these days as the party of HEEs

2. Another hard-to-excerpt essay comes from James R. Rogers.

Conservative market-skeptics engage in wishful thinking that Republicans can win without traditional commitment to a relative emphasis on markets in a mixed economy and on tax cuts.

. . .Trumpists do not currently own the Republican Party. The American Party/Know Nothing faction continues to represent about a third of the party. It’s been that way for decades. It is a sizeable fraction. But it is not a majority. Because there is nowhere else to go, it is, largely, a dependable component of the Republican coalition, and will continue to be so.

I look at the Republican Party somewhat differently. To me, the anti-establishment vote looms as more significant than it seems to appear to Rogers.

In 2024, the Republicans will face a challenge. If they don’t praise Mr. Trump, they risk de-motivating his supporters. If they do praise Mr. Trump, they risk motivating those who hate him. The Democrats face a similar problem with their far-left supporters, but I think it will be easier for them to get away with ambiguity, as Mr. Biden had done.

Nonfiction books of the year, 2020

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1. Joseph Henrich, The WEIRDest People in the World. Analysis of human culture that is broad, deep, and bold. In a functioning academic world, graduate students in many social science disciplines would be mining this book for dissertation topics. My review could not do it justice.

2. Helen Pluckrose and James Lindsay, Cynical Theories. A must-read on the intellectual foundations of the Woke movement. My review suggests ways it might have been better executed.

3. Kevin Davies, Editing Humanity. Tells the stories of the scientists involved in the discovery and development of the gene editing technology known as CRISPR, two of whom were awarded a Nobel Prize in chemistry the week that the book came out. The book is history of science reported with maximum melodrama, which makes for an entertaining and informative read.

4. Robert P. Saldin and Steven M. Teles, Never Trump. A look at the way that conservative intellectuals agonized over Mr. Trump. My review shows where I agree with them and where I part company.

5. Peter Zeihan, Disunited Nations. Zeihan has strong opinions about the way that demographics and resources affect the way nations operate in the world. As my review says, I find his opinions very provocative, even though he does not subject them to rigorous testing the way Henrich does his ideas.

House prices up

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The WSJ reports,

In nearly two-thirds of the metro areas tracked by NAR, prices posted double-digit gains. The biggest gainers were Bridgeport, Conn., where the median price rose 27.3%, and Crestview, Fla., up 27.1%.

My thoughts:

1. The NAR tracks the median price of homes sold, which depends on the mix of homes transacted. If the demand surge is for bigger homes, some of the rise in the NAR measure represents a mix shift.

2. I assume that not all of the real estate market is healthy. Apartment rents are probably down, at least in places like NY and SF. Commercial real estate is probably in bad shape.

3. The economic impact of the virus is probably very uneven. Affluent people who have kept working from home are spending less and banking their salaries, which can now go into housing. But job losers are not getting into the housing market.

4. Maybe we are starting to see some inflationary consequences of lockdown socialism.