For me one of the most fun episodes, here is the audio, video, and transcript. And here is the longer than ever before summary, befitting the chat itself:
Audrey Tang began reading classical works like the Shūjīng and Tao Te Ching at the age of 5 and learned the programming language Perl at the age of 12. Now, the autodidact and self-described “conservative anarchist” is a software engineer and the first non-binary digital minister of Taiwan. Their work focuses on how social and digital technologies can foster empathy, democracy, and human progress.
Audrey joined Tyler to discuss how Taiwan approached regulating Chinese tech companies, the inherent extraterritoriality of data norms, how Finnegans Wake has influenced their approach to technology, the benefits of radical transparency in communication, why they appreciate the laziness of Perl, using “humor over rumor” to combat online disinformation, why Taiwan views democracy as a set of social technologies, how their politics have been influenced by Taiwan’s indigenous communities and their oral culture, what Chinese literature teaches about change, how they view Confucianism as a Daoist, how they would improve Taiwanese education, why they view mistakes in the American experiment as inevitable — but not insurmountable, the role of civic tech in Taiwan’s pandemic response, the most important remnants of Japanese influence remaining in Taiwan, why they love Magic: The Gathering, the transculturalism that makes Taiwan particularly open and accepting of LGBT lifestyles, growing up with parents who were journalists, how being transgender makes them more empathetic, the ways American values still underpin the internet, what he learned from previous Occupy movements, why translation, rotation, and scaling are important skills for becoming a better thinker, and more.
This bit could have come from GPT-3:
COWEN: How useful a way is it of conceptualizing your politics to think of it as a mix of some Taiwanese Aboriginal traditions mixed in with Daoism, experience in programming, and then your own theory of humor and fun? And if you put all of that together, the result is Audrey Tang’s politics. Correct or not?
TANG: Well as of now, of course. But of course, I’m also growing, like a distributed ledger.
COWEN: You’re working, of course, in Taiwanese government. What’s the biggest thing wrong with economists?
TANG: You mean the magazine?
COWEN: No, no, the people, economists as thinkers. What’s their biggest defect or flaw?
TANG: I don’t know. I haven’t met an economist that I didn’t like, so I don’t think there’s any particular personality flaws there.
COWEN: Now, my country, the United States, has made many, many mistakes at an almost metaphysical level. What is it in the United States that those mistakes have come from? What’s our deeper failing behind all those mistakes?
TANG: I don’t know. Isn’t America this grand experiment to keep making mistakes and correcting them in the open and share it with the world? That’s the American experiment.
COWEN: Have we started correcting them yet?
TANG: I’m sure that you have.
We estimate the impact of mask mandates and other non-pharmaceutical interventions (NPI) on COVID-19 case growth in Canada, including regulations on businesses and gatherings, school closures, travel and self-isolation, and long-term care homes. We partially account for behavioral responses using Google mobility data. Our identification approach exploits variation in the timing of indoor face mask mandates staggered over two months in the 34 public health regions in Ontario, Canada’s most populous province. We find that, in the first few weeks after implementation, mask mandates are associated with a reduction of 25 percent in the weekly number of new COVID-19 cases. Additional analysis with province-level data provides corroborating evidence. Counterfactual policy simulations suggest that mandating indoor masks nationwide in early July could have reduced the weekly number of new cases in Canada by 25 to 40 percent in mid-August, which translates into 700 to 1,100 fewer cases per week.
That is from a new NBER working paper by Alexander Karaivano, Shih En Lu, Hitoshi Shigeoka, Gong Chen, and Stephanie Pamplona.
That is the topic of my latest Bloomberg column, here is one excerpt:
The more time passes, the more I wonder if I have, in fact, contracted an asymptomatic version of Covid. The chance of that was quite small in February, but as each month passes it becomes modestly more likely. That realization could easily nudge many people into taking just a bit more risk.
Another train of thought considers the possibility of having a pre-existing protective immune response, perhaps from T-Cells. Experts are not sure of the likelihood or magnitude of this effect, but some have suggested that as many as one-third of Americans may have some built-in protection.
Again, as the months pass, it’s rational for me to upgrade the probability that I have such a protective immune response. With the passage of time, I will feel more protected than I used to.
The basic reasoning is straightforward: Since I haven’t caught a bad form of it by now, I must be relatively safe. Many Americans may or may not grasp the finer points of the immunology and the Bayesian statistical reasoning, but that is a very common-sense kind of response.
And so such people will take more risk — to the detriment of the broader community.
There is much more at the link, including a discussion of intertemporal substitution. These are some reasons why initially good (or bad) Covid responses tend to get worse, relevant for Europe as well.
Researchers from the Princeton Environmental Institute (PEI), Johns Hopkins University and the University of California, Berkeley, worked with public health officials in the southeast Indian states of Tamil Nadu and Andhra Pradesh to track the infection pathways and mortality rate of 575,071 individuals who were exposed to 84,965 confirmed cases of COVID-19, the disease caused by SARS-CoV-2. It is the largest contact tracing study — which is the process of identifying people who came into contact with an infected person — conducted in the world for any disease.
Lead researcher Ramanan Laxminarayan, a senior research scholar in PEI, said that the paper is the first large study to capture the extraordinary extent to which SARS-CoV-2 hinges on “superspreading,” in which a small percentage of the infected population passes the virus on to more people. The researchers found that 71% of infected individuals did not infect any of their contacts, while a mere 8% of infected individuals accounted for 60% of new infections…
The researchers found that the chances of a person with coronavirus, regardless of their age, passing it on to a close contact ranged from 2.6% in the community to 9% in the household. The researchers found that children and young adults — who made up one-third of COVID cases — were especially key to transmitting the virus in the studied populations.
“Kids are very efficient transmitters in this setting, which is something that hasn’t been firmly established in previous studies,” Laxminarayan said. “We found that reported cases and deaths have been more concentrated in younger cohorts than we expected based on observations in higher-income countries.”
I am very happy to see this new and urgently needed study. They have heeded the stricture to show their work. The authors are Donald A. Berry, Scott Berry, Peter Hale, Leah Isakov, Andrew W. Lo, Kien Wei Siah, and Chi Heem Wong, and here is the abstract:
We compare and contrast the expected duration and number of infections and deaths averted among several designs for clinical trials of COVID-19 vaccine candidates, including traditional randomized clinical trials and adaptive and human challenge trials. Using epidemiological models calibrated to the current pandemic, we simulate the time course of each clinical trial design for 504 unique combinations of parameters, allowing us to determine which trial design is most effective for a given scenario. A human challenge trial provides maximal net benefits—averting an additional 1.1M infections and 8,000 deaths in the U.S. compared to the next best clinical trial design—if its set-up time is short or the pandemic spreads slowly. In most of the other cases, an adaptive trial provides greater net benefits.
And what is an adapted trial you may be wondering?:
An adaptive version of the traditional vaccine efficacy RCT design (ARCT) is based on group sequential methods. Instead of a fixed study duration with a single final analysis at the end, we allow for early stopping for efficacy via periodic interim analyses of accumulating trial data…While this reduces the expected duration of the trial, we note that adaptive trials typically require more complex study protocols which can be operationally challenging to implement for test sites unfamiliar with this framework. In our simulations, we assume a maximum of six interim analyses spaced 30 days apart, with the first analysis performed when the first 10,000 subjects have been monitored for at least 30 days.
That means of course you might cut the trial short. Kudos to the authors for producing one of the most important papers of this year.
Tyrone — my evil twin brother — received so much hate and love mail from his recent pronouncements about QAnon that he felt emboldened to offer additional opinions. As you might expect, he prefers to spew his hateful bile on matters of life and death. In particular, he has been following the debates about Covid and whether new treatments should be accelerated in their availability. Anyway, I told him I was willing to pass along another of his letters, as a kind of experiment (not quite a clinical trial) whether Tyler or Tyrone is a more beloved writer on MR. I am sure you readers — and especially commentators — stand ready to defend my honor!
So here is his (as usual) fallacy-ridden missive:
Tyler, I don’t see why you let the defenders of FDA stalling get away with their dawdling. They all end up with the same argument — if we let wonderful, salt of the earth Americans take beneficial medicines, treatments, and vaccines, we will not be able to set up informative clinical trials. Why partake in the trial when you can just get the stuff through normal means?
That is so lame! First, they could simply pay people to partake in those trials. Isn’t that in essence what the NBA did with its Covid testing in the bubble? If the value of those clinical trials truly is so high, it should be possible to internalize enough of those benefits to encourage participation. If institutional barriers stand in the way there, let’s obsess over fixing those.
Why should we force so many Americans to be sacrificial lambs, just to subsidize the trial costs? Let those costs be taken out of grant overhead! (And admin. salaries, if need be.)
If the current medical establishment is not as able as the NBA, well OK, can’t they just admit it and plead patheticness? We can send them to take care of Major League Baseball, and put Adam Silver and Lebron James in charge of our health care.
Second, there is another way to keep the trial up and running. Approve use of the treatment, but allow the suppliers to charge very high prices! Better yet, use the law to make them charge high prices and if need be forbid insurance coverage.
“What will it be sucker? Fifty percent chance of the placebo, or 100k for those monoclonal antibodies?”
I assure you Tyler that will restore a separating equilibrium. Furthermore, in the meantime only the most meritocratic of wealthy men will get the treatment outside of the trial, all for the better. If need be, you can pull away the price floor when the clinical trial is complete, in the meantime you have satisfied the Pareto principle.
And what about the Hippocratic Oath ? “Do no harm”? Is that not invoked so selectively by the public health commentators? Surely you realize they court public opinion and high status by taking sins of commission far more seriously than the far less visible sins of omission?
Is it not harm to deny patients ready accessibility to a treatment with positive expected value?
Is it really such a great rejoinder to insist “We can’t let those patients improve their lot by raising pecuniary costs for the medical professionals running their trials! That is true Hippocratic harm and must be avoided at all costs, because in fact we medical people would be too feckless to overcome that problem…”
Sigh. At that point I had to stop reading and transcribing. I am sorry readers, I didn’t know that Tyrone in his spare time was studying economics and indeed some logic as well. Maybe he has even been reading MR. That makes him less interesting, less funny, and maybe a bit too much like Tyler. That is not why you come to read Tyrone, and indeed you might as well be reading Tyler.
What can I do to make Tyrone better and more eccentric again? Perhaps try to get him premature access to some of those special treatments? Stay tuned….
Here is the story, note the treatment is making a very good impression:
Prof Peter Horby, who is part of Oxford University’s national Recovery trial, which aims to identify potential treatments for Covid-19, said “about three hospitals in the north” began using the drug last weekend. He said the drug was due to be rolled out to another 30 to 40 UK hospitals next week.
He told BBC Radio 4’s Today programme that the drug, REGN-COV2, was “very promising” and “very potent”.
“The class of drugs, these artificial antibodies, have been around for quite a while now, and they’ve been extensively used in inflammatory conditions and cancers, and they’re pretty safe and well understood, and so the technology is something that I think we have confidence in,” Horby said.
“This particular drug has probably been given to, I would think now, four or five hundred patients, mild or severe patients in different trials, and so far there’s been no worrying safety signals.
“In the laboratory, in cell cultures, it has a very strong effect against the virus, and there have been studies in artificial animals where it also shows benefits. So probably of the drugs that are available, it’s one of the most promising.”
Horby said a single dose of the treatment provided prolonged protection for a month to six weeks, making it “quite attractive for the older population”.
I hope Donald Trump “twists” the arms of the scientists at the FDA into speedy Emergency Use Authorization, and “politicizes” them into doing the right thing.
Twist, Donald! Yes, they are accountable too. Twist harder! That’s why we gave you the monoclonal antibodies.
And please don’t tell me in response that we can expect ordinary Americans to apply for the compassionate use exception, or sign up for clinical trials.
Well, which one is it?
If you consider the treatments of remdesivir or monoclonal antibodies for President Trump, their application is either positive expected value or negative expected value.
If they are positive expected value, you should be for using them! (I don’t mean that as a political statement, sub in another patient’s name if you need to.)
If they are negative expected value, you should oppose the current widespread use of remdesivir in hospitals (not necessarily in every case, of course), and you should probably oppose the Advance Market Commitment already in place for Regeneron’s monoclonal antibody treatment, not to mention its successful advance through various trials.
I don’t see anyone taking those stances.
Instead, I see commentators — including highly esteemed public health experts — claiming there is not yet enough data, “expressing reservations,” referring to other public health catastrophes, referring to more general irresponsible habits of the patient under consideration, and serving up various other rhetorical devices to indicate a negative attitude toward the treatment without actually saying “I think this treatment is negative expected value.”
That is a very bad thought and writing habit!
Made worse by Twitter, I might add. You are trying to create negative affect and mood affiliation without making the corresponding epistemic and predictive commitment.
Please just say you think it is negative expected value, and then apply that view consistently across the board. Stand your ground and defend it.
Or if you think it is positive expected value, praise its use, and then of course it is fine to add qualifiers and reservations.
If you genuinely have no opinion (ha), it is fine to say that too, but then you can drop the negative rhetoric and maybe don’t tweet about it at all.
To be sure, there are various heterogeneities and I am not applying the appropriate qualifiers in each sentence above, for reasons of expositional convenience. For instance, is Trump different from other patients? Are the treatments being applied at the right time? Who exactly has the private information here? And so on. Incorporating those factors should not change the basic analysis above, though for the most part they should push you toward a more positive attitude toward the treatments.
Mayank Gupta emails me:
The absolute number of false positives would rise dramatically under slightly inaccurate, broad surveillance testing. At least initially, the number of people going to the doctor to ask what to do would also rise. One can imagine if doctors truly flubbed and didn’t know how to advise patients accurately, a lot of individual patients would lose trust in the medical system (testing, doctors, or both). The consequence of this would be more resistance to health public policy measures in the future.
I see this as quite similar to what happened on three mile island. There was a clear utilitarian benefit to taking on some small amount of nuclear accident risk. The public was never taught how or why to internalize and cope with this risk. When the risk manifested, individuals saw the risk but not the public benefit and turned against nuclear. This change of public opinion was reflected in public policy after.
I’m sure there’s some mismatches in this analogy, but I’m using it to point out that in general I find thinking on the margin without thinking about the public’s ability to think on the margin can result in setbacks on the margin.
In an age where science is both more capable of solving social problems and more complex to understand, but the public has too much complex information to sort through, the central problem of governance seems to be how to solve public choice, without creating a monopoly on information.
To be clear, I do favor rapid testing, but it is worth giving this problem further thought.
In an interview Friday afternoon, Regeneron’s chief executive, Dr. Leonard S. Schleifer, said Mr. Trump’s medical staff reached out to the company for permission to use the drug, and that it was cleared with the Food and Drug Administration.
“All we can say is that they asked to be able to use it, and we were happy to oblige,” he said. He said that so-called compassionate use cases — when patients are granted access to an experimental treatment outside of a clinical trial — are decided on a case-by-case basis and he is not the first patient to granted permission to use the treatment this way. “When it’s the president of the United States, of course, that gets — obviously — gets our attention.”
In my non-specialist but not entirely uninformed opinion, this is basically an effective treatment, and barring major unobserved genetic risk factors Trump will recover. The risk of side effects is not significant. But of course neither the FDA nor Regneron will let me do the same. Or you.
There is such cacophony when Trump pushes the FDA to speed vaccine approval — mere pressure rather than an action. Yet when he actually gets a promising treatment through the process “prematurely” — only for himself — not a single person is yelping. Not even his worst enemies and most vicious opponents. Nor do I see anyone arguing that the President is being allowed to take excess risk, and that the judgments of the regulators should be enforced consistently and for the good of the office of the presidency.
Nope. Model that! (Hint: start with the idea of status.)
In the meantime, I think the common intuition about the Trump monoclonal antibodies case is essentially correct, and it ought to be applied most broadly. And not just for presidents.
Here is the full NYT story.
A key unsolved question in the current coronavirus disease 2019 (COVID-19) pandemic is the duration of acquired immunity. Insights from infections with the four seasonal human coronaviruses might reveal common characteristics applicable to all human coronaviruses. We monitored healthy individuals for more than 35 years and determined that reinfection with the same seasonal coronavirus occurred frequently at 12 months after infection.
That is from a new research paper by Arthur W D Edridge, et.al. That is not conclusive proof concerning Covid-19, but it’s not exactly great news either.
A herd immunity data point: Borough Park in NYC has one of the highest antibody rates seen in the developed world: 43.9%, based on a huge testing program covering almost 1/3 of local pop. This week positivity rates of Covid-19 tests coming back hit 17%.
Here is the abstract of a new paper by
We have studied the evolution of COVID-19 in 12 low and middle income countries in which reported cases have peaked and declined rapidly in the past 2-3 months. In most of these countries the declines happened while control measures were consistent or even relaxing, and without signs of significant increases in cases that might indicate second waves. For the 12 countries we studied, the hypothesis that these countries have reached herd immunity warrants serious consideration. The Reed-Frost model, perhaps the simplest description for the evolution of cases in an epidemic, with only a few constant parameters, fits the observed case data remarkably well, and yields parameter values that are reasonable. The best-fitting curves suggest that the effective basic reproduction number in these countries ranged between 1.5 and 2.0, indicating that the curve was flattened in some countries but not suppressed by pushing the reproduction number below 1. The results suggest that between 51 and 80% of the population in these countries have been infected, and that between 0.05% and 2.50% of cases have been detected; values which are consistent with findings from serological and T-cell immunity studies. The infection rates, combined with data and estimates for deaths from COVID-19, allow us to estimate overall infection fatality rates for three of the countries. The values are lower than expected from reported infection fatality rates by age, based on data from several high-income countries, and the country population by age. COVID-19 may have a lower mortality risk in these three countries (to differing degrees in each country) than in high-income countries, due to differences in immune response, prior exposure to coronaviruses, disease characteristics or other factors. We find that the herd immunity hypothesis would not have fit the evolution of reported cases in several European countries, even just after the initial peaks; and subsequent resurgences of cases obviously prove that those countries have infection rates well below herd immunity levels. Our hypothesis that the 12 countries we studied have reached herd immunity should now be tested further, through serological and T cell immunity studies.
Via Alan Goldhammer.
Addendum: From Catinthehat in the comments:
It’s a simple homogeneous model Ni(t+1)= Ni(t) * Ro * Si(t) / Ntot -> Infected at time t+1 = Infected at time t * Ro * the proportion ( of the population) susceptible at time t. where t is discretized.
They fit the step t to an infection duration , then they fit Ro, to reproduce the shape of the curve for each country and at each step they multiply the infected by a parameter p (the undetected case ratio) to fit to the total population. This acts as an accelerant to the epidemic . Each country has its own p.
The main issue is that you can look at any epidemic curve and fit it that way and you will rather automatically reproduce this high immunity threshold which comes from your homogenous model.
In Europe you can’t assume the undetected ratio is so high ( 1000x to 2000 x) so you must conclude social distancing stopped the epidemic, because your strategy would not fit experimental data.
In the countries fitted , the paper must conclude the epidemic raged fairly undetected, fairly quickly and infected most of the population.
The most productive part of medical care is treatment for cardiovascular disease, both acute conditions and risk factors. Productivity estimates for acute cardiovascular diseases are $89,000 in aggregate — 79% of the total increase [in health care productivity from 1999 to 2012].
There has been very little progress over that same period in treating mental illness, arthritis, and musculoskeletal conditions. How about this:?
Despite a vast increase in the number of people treated with drugs for mental illness, the population’s mental health showed essentially no change over time.
Overall medical care was increasing in productivity over that period by about 0.7% a year, still great stagnation territory as they say.
That is all from a new paper by David M. Cutler, Kaushik Ghosh, Kassandra Messer, Trivellore Raghunathan, Allison B. Rosen, and Susan T. Stewart.
That is the topic of my latest Bloomberg column, here is one excerpt:
Now consider another of my favorite pastimes, watching professional basketball. I have been following the NBA bubble with great interest. The Miami Heat are now favored to reach the NBA Finals, even though they were only the fifth-ranked team in the East at the end of the regular season. What happened? They have played with grit and determination, and their entire active roster showed up in first-rate physical shape. That’s not easy to do after a five-month layoff, as it required tremendous discipline.
In contrast, the Los Angeles Clippers were among the favorites to win the NBA title. They were recently eliminated by the Denver Nuggets, a very good team but not previously a top contender. In the final quarter of the last game of the series, the victorious Nuggets played with energy and verve, while the Clippers seemed to be gasping for air. After their defeat, some of the Clippers admitted that inferior conditioning was part of their problem.
So “staying in shape during a five-month layoff” is now a critical skill for a basketball player. But this doesn’t necessarily mean the Clippers need to revamp their roster. Maybe they should just wait for a return to normal times.
Might these changes in quality affect your choices beyond work — such as your decisions about friends, family relations, romance, and much more? Should you buy a dog, knowing you probably won’t be homebound two years from now? How about dating? On a first date, presumably, looks should matter less and social carefulness more. But again, for how long? It would be very strange, and probably unwise, to form a lasting relationship based on how well your romantic interest wears a mask.
Sadly the world has entered a new paralysis, most of all because no one knows when things will return to normal, or what might become normal, or what might remain strange. When this pandemic ends, one thing we can all look forward to is making better plans.
Recommended, at least until the pandemic is over.