Here goes, and here is the close:
Dang, that’s a lot of vaccine candidates. And as you can see, it’s a long-tail distribution – there are some big ones that everyone knows about, but a lot of people are bringing a lot of technologies to bear on the problem. This makes me think that we’re going to have a multichapter story, in the end. There will be the first vaccines approved, then the second wave, then the improvements on those, until we have (with luck, hard work, skill, and lots of money) tossed this virus out of the human population and back to the bats, pangolins, or whoever had it in the first place.
An excellent side effect is that vaccine technology will never be the same after this – it’s going to be like aircraft design before and after World War II, and for many of the same reasons. This whole pandemic has been awful, in many different ways, but we’re going to come out of it stronger and more capable than when we went in.
It is about fifteen minutes, and also I give you all a separate clip of me praising the new Matt Yglesias book (which was alas cut from the main edit, note there is a lag before the short clip pops up) and discussing “family capacity libertarianism.” Here is the main episode, with a few clips of text beneath the video itself:
I was quite happy with how this interview turned out, and I feel a bit that I got to jab just about everybody, including the herd immunity theorists.
Physicians who also have extensive training in scientific methods, often a Ph.D., are ideally suited to learn from the unusual clinical manifestations of Covid-19, such as strokes in young adults and autoimmune Kawasaki syndrome in children. Physician-scientists, however, are becoming extinct in the United States, comprising only about 1% of all physicians today, and with few young clinician researchers joining their ranks.
A solution to this crisis might be found in a quiet research program at the National Institutes of Health that flourished in the shadow of the Vietnam War. It may well have been the greatest medical research program in modern history. The two-year program, officially known as the NIH Associates Training Program, was started in 1953 as a way to bring newly minted physicians to the NIH campus in Bethesda, Md., so they could do research for two to three years under the guidance of senior NIH investigators…
Nine physicians who trained at the NIH during this period went on to win Nobel Prizes. From the class of 1968 alone, Robert Lefkowitz discovered a family of cellular receptors that one-third of all approved drugs target; Michael Brown and Joseph Goldstein discovered a cholesterol receptor that led to the development of cholesterol-lowering statin medications; and Harold Varmus discovered some of the fundamental mechanisms of cancer.
Here is the full StatNews article by Haider J. Warraich.
Every day I read maybe twenty or more tweets decrying Trump’s acceleration of the FDA vaccine approval process. And yet I do not see a single blog post with back of the envelope calculations. This is such an important decision, and it deserves better, just as we analyze the Fed’s monetary policy decisions in great detail. On those points, here is my latest Bloomberg column, excerpt:
One of your weaker arguments is that Trump’s push is disturbing because it is making the FDA “too political.” First, American responses to crises, such as Sept. 11 or the Great Recession, have always been political. Second, and more to the point, there is a strong case that the FDA should take politics into account more, not less.
The FDA has been too risk-averse in the very recent past, for instance in its reluctance to approve additional Covid-19 testing. Economists have generally concluded that the FDA is too risk-averse in the long term as well, considering all relevant trade-offs. What kind of fix might there be for those problems, if not a “political” one? Of course the initial risk-aversion was itself the result of a political calculation, namely the desire to avoid blame from the public and from Congress…
The American people will not buy the claim that the current [pre-Trump] FDA is above politics. Nor should they.
As a public-health expert, you are also missing the broader context behind the current vaccine debate. In the early months of the pandemic, as late as April, it was common to hear that there might not be a vaccine for at least four years, and many were not sure if it would be possible at all. It is now likely (though not certain) that there will be a pretty good vaccine within a year.
That is a wonderful development, and it speaks well of your intelligence and hard work. Still, given that recent history, is it crazy for the American people to wonder if the process could be accelerated further? After all, the Chinese have a vaccine right now (albeit probably an inferior one), and they have been known to complete complicated infrastructure projects with a speed not previously thought possible.
It’s not just about wanting to speed things up. One might argue that, due to the unprecedentedly high number of vaccines currently under consideration, the optimal threshold should be higher, not lower, for fear that the world will be left with a suboptimal choice.
Too often I have seen one of you cite a single factor on one side of the approval equation, then invoke your authority or some previously existing institutional standard to suggest that this factor is decisive. In a Trumpian world, where credentials and authority no longer settle a debate — on public health or other matters — this kind of argument is not sufficient.
My plea is that such arguments and others be accompanied by concrete numbers, if only rough back-of-the-envelope estimates, and that all of the factors be considered together. Those numbers should incorporate the human, economic and public-health costs of allowing the current situation to continue for months. The result could be a useful public debate about the optimal speed of vaccine approval.
Yes, blah blah blah. But — public health experts — show your work.
We document four facts about the COVID-19 pandemic worldwide relevant for those studying the impact of non-pharmaceutical interventions (NPIs) on COVID-19 transmission. First: across all countries and U.S. states that we study, the growth rates of daily deaths from COVID-19 fell from a wide range of initially high levels to levels close to zero within 20-30 days after each region experienced 25 cumulative deaths. Second: after this initial period, growth rates of daily deaths have hovered around zero or below everywhere in the world. Third: the cross section standard deviation of growth rates of daily deaths across locations fell very rapidly in the first 10 days of the epidemic and has remained at a relatively low level since then. Fourth: when interpreted through a range of epidemiological models, these first three facts about the growth rate of COVID deaths imply that both the effective reproduction numbers and transmission rates of COVID-19 fell from widely dispersed initial levels and the effective reproduction number has hovered around one after the first 30 days of the epidemic virtually everywhere in the world. We argue that failing to account for these four stylized facts may result in overstating the importance of policy mandated NPIs for shaping the progression of this deadly pandemic.
That is the abstract of a new NBER paper by Andrew Atkeson, Karen Kopecky, and Tao Zha. You will note that when it comes to Covid-19 cases, the superior performance Europe had enjoyed over the United States seems to be evaporating, see here on France and here on Europe more generally.
We use data the Swedish authorities organized as an early release of all recorded COVID-19 deaths in Sweden up to May 7, 2020, which we link to administrative registers and occupational measures of exposure. Taxi and bus drivers had a higher risk of dying from COVID-19 than other workers, as did older individuals living with service workers. Our findings suggest however that these frontline workers and older individuals they live with are not at higher risk of dying from COVID-19 when adjusting the relationship for other individual characteristics. We also did not find evidence that being a frontline worker in terms of occupational exposure was linked to higher COVID-19 mortality. Our findings indicate no strong inequalities according to these occupational differences in Sweden and potentially other contexts that use a similar approach to managing COVID-19.
Overall I am quite surprised how large is the bus and taxi driver effect (even after adjusting for demographics), and how small are the other professional effects. Here is the paper, by Sunnee Billingsley, et.al., via Daniel B. Klein.
Yes it was a terrible tragedy, but many locales had much worse events fairly recently:
Between 1917 and 1918 New York City’s crude mortality rate increased by 3.173 deaths per 1000 persons. While tragic, the hollow circles in Figure 1 depict 12 other years where the year-over-year increase in mortality exceeded the magnitude of the 1917 to 1918 change. During the cholera epidemics of 1832, 1834, 1849, and 1854 the year-over-year increase in mortality was 3 to 5 times larger in magnitude than what occurred in 1918. As another comparison, the mortality rate in New York City was higher in nearly every year between 1800 and 1905 than the mortality rate in 1918.
The same is true for many other American cities, but here is a picture for NYC:
During the first half of the 20th century, Black Americans in urban areas died from infectious disease at a rate that was greater than what urban whites experienced during the 1918 flu pandemic every single year.
On a different but related topic:
…the evidence suggests that the 1918 pandemic was not a major determinant of U.S. stock market volatility.
That is all from the new and very interesting NBER paper by Brian Beach, Karen Clay, and Martin H. Saavedra, “The 1918 Influenza Pandemic and its Lessons for Covid-19.”
I know very little about this area, but found these results of interest and worthy of further investigation:
Mounting evidence across disciplines shows that psychotherapy is more curative than antidepressants for mild-to-moderate depression and anxiety. Yet, few patients use it. This paper develops and estimates a structural model of dynamic decision-making to analyze mental health treatment choices in the context of depression and anxiety. The model incorporates myriad costs suggested in previous work as critical impediments to psychotherapy use. We also integrate links between mental health and labor outcomes to more fully capture the benefits of mental health improvements and the costs of psychotherapy. Finally, the model addresses measurement error in widely-used mental health variables. Using the estimated model, we find that mental health improvements are valuable, both directly through increased utility and indirectly through earnings. We also show that even though psychotherapy improves mental health, counterfactual policy changes, e.g., lowering the price or removing other costs, do very little to increase uptake. We highlight two conclusions. As patient reluctance to use psychotherapy is nearly impervious to a host of a priori reasonable policies, we need to look elsewhere to understand it (e.g., biases in beliefs about treatment effects, stigma, or other factors that are as yet unknown). More broadly, large benefits of psychotherapy estimated in randomized trials tell only half the story. If patients do not use the treatment outside of an experimental setting—and we fail to understand why or how to get them to—estimated treatment effects cannot be leveraged to improve population mental health or social welfare.
That is from a new NBER working paper by Christopher J. Cronin, Matthew P. Forsstrom, and Nicholas W. Papageorge.
The available data seems to meet the bar for an EUA.
I found this Adam Rogers Wired piece insightful and the best single treatment so far, and also interesting more generally on RCTs:
“Fifty thousand people have been given a treatment, and we cannot know whether it worked or not,” says Martin Landray, one of the leaders of the Randomised Evaluation of Covid-19 Therapies (or Recovery) Trial in England, a large-scale, multi-center, multi-drug randomized controlled trial that showed that the corticosteroid dexamethasone saved the lives of Covid-19 patients and the autoimmune drug hydroxychloroquine did not. (That 50,000 number was from a few weeks back, just after the plasma preprint came out.)
The main arguments against the decision from Trump/FDA seem to be “do RCTs” and “convalescent plasma isn’t shown to be so great.” But those points have it exactly backwards. Patients for trials are extremely scarce right now, and if convalescent plasma is not the highest probability big winner (and I suspect it isn’t), you won’t want to waste scarce patients on doing the RCT. Moreover, if you can’t get the RCT done with 98,000 or so patients, maybe you’re just not up to doing it period! (Please do think at the margin.) In the meantime, convalescent plasma does not seem to involve harms or risks, and it may offer some benefits. So why not let more people have easier access to it?
And might there be a tiny chance that American citizens demand stronger payment incentives for the relevant supplies here and also for other treatments?
If all people have is “do RCTs and CP isn’t shown to be so great,” I don’t think they have begun to engage with the arguments. And additionally politicizing the FDA is definitely a real cost to be reckoned with, but the Twitter noise I am seeing from public health experts seems oblivious to the fact that the FDA’s ex ante risk-averse stance was politicized to begin with (which is not necessarily a bad thing, but yes this is a basic fact — “politicization for me, but not for thee,” etc.).
Billions of dollars in federal funds earmarked for boosting nationwide Covid-19 testing remain unspent months after Congress made the money available, according to the U.S. Department of Health and Human Services.
In April, Congress allocated roughly $25 billion for federal agencies and states to expand testing, develop contact-tracing initiatives and broaden disease surveillance.
According to HHS data, only about 10% to 15% of that total has been drawn down, meaning the cash has been spent or committed to various efforts…
Of the $25 billion, some $10.25 billion was sent to states and U.S. territories in May to expand testing and develop contact-tracing programs at their discretion, but as of Aug. 14, just $121 million of that pool of funds had been drawn down.
Fast Grants it ain’t. Here is the full WSJ article by Scott Patterson and Sarah Krouse.
Sebastian Garren, to found John Paul II Preparatory School’s South Campus in St. Louis, a hybrid on-line and in-person educational alternative for K-12, also stressing Western history and the classics.
John Durant, for career development and writing, and explorations into notions of angels.
Krishaan Khubchand, 20 years old, studying law at Birkbeck, to study mega-projects and capital allocation, he is also a Progress Studies fellow.
Vignan Velivela. He started as a robotics engineer at Cruise Automation, is a member of the Explorers Club (wiki, BBC) for his work on the lightest planetary rover at Carnegie Mellon, worked on a peer-to-peer lending startup in India that was acqui-hired by PayTm, went to college (BITS Pilani) in India studying EE and Economics, and now is co-founder of AtoB.
Wasteland Ventures (no web page), to support their efforts in talent search and development.
And two Emergent Ventures anti-Covid prizes have been awarded to:
Witold Wiecek, Bayesian statistician and consultant, for his work on the Bayesian modeling of the COVID-19 epidemic, and the design of an optimal vaccine portfolio, in cooperation with the Accelerating Health Technologies team.
Arthur W. Baker (no web page, and not this guy) for his efforts on incentive design for vaccines, in cooperation with the Accelerating Health Technologies team.
Here are previous winners of Emergent Ventures grants and prizes.
That is the topic of my latest Bloomberg column, here is one excerpt:
…here is why I am not yet an unreconstructed economic optimist. Covid-19 cases have acquired a stigma, and that stigma is likely to persist above and beyond the dangers associated with the virus itself.
If, say, 20 Covid-19 cases were identified within a high school today, there is a very real risk that those infected students would carry the virus home and infect older and more vulnerable people. There is also a small risk that the students would sustain damage themselves. Not surprisingly, most schools won’t reopen because they cannot deal with the burden — institutionally, legally or otherwise — of being connected to significant numbers of Covid-19 cases.
The question is how this stigma ends. If rates of death and possible long-term damage fell to half of their current levels? One-third? Less? I strongly suspect these same schools still would be unwilling to reopen, due in part to phantom risk.
If rates of death and damage fell to one-fifth of their current level, perhaps, there would be more reopenings — but there would still be a lot of reluctance to restore previous levels of attendance. How about one-tenth the level of mortality? It is hard to say when people will feel comfortable once again.
Along these lines, as long as clusters of reported cases are possible — regardless of mortality rates — many high-rise office buildings will not let workers and visitors simply pile into their elevators.
Many sites likely to experience identifiable, traceable clusters of cases will keep their doors shut, or open them on only a very limited basis. Further declines in the mortality rate won’t help much, because “37 Covid-19 Cases Identified at UC-Berkeley” is enough of a headline to create reputational risk and an institutional response. Even if everyone makes a speedy recovery, that won’t get the same kind of media coverage.
There is much more at the link, and my point will grow increasingly relevant, first of all in NYC and environs (partial herd immunity there, at least for the time being).
We compare COVID-19 case loads and mortality across geographic areas that hosted more vs fewer NHL hockey games, NBA basketball games, and NCAA basketball games during the early months of 2020, before any large outbreaks. We find that hosting one additional NHL/NBA game leads to an additional 783 COVID-19 cases during March-mid May and an additional 52 deaths. Similarly, we find that hosting an additional NCAA Division 1 men’s basketball games results in an additional 31 cases and an additional 2.4 deaths. Back of the envelope calculations suggest that the per-game fatality costs exceed consumption benefits by a wide margin.
That is from Coady Wing, Daniel H. Simon, and Patrick Carlin. I think we have not a good enough model of the heterogeneities of prevalence across regions for those to be reliable estimates. Still, I am happy to see more work on the question of what in particular causes Covid cases, and also whether sporting events play a significant role.
Malaysia has detected a strain of the new coronavirus that’s been found to be 10 times more infectious.
The mutation called D614G was found in at least three of the 45 cases in a cluster that started from a restaurant owner returning from India and breaching his 14-day home quarantine. The man has since been sentenced to five months in prison and fined. The strain was also found in another cluster involving people returning from the Philippines…
The mutation has become the predominant variant in Europe and the U.S., with the World Health Organization saying there’s no evidence the strain leads to a more severe disease.
Here is the Bloomberg story, please consider this subject to further revision!
The FDA has just approved a new and important Covid-19 test:
“Wide-spread testing is critical for our control efforts. We simplified the test so that it only costs a couple of dollars for reagents, and we expect that labs will only charge about $10 per sample. If cheap alternatives like SalivaDirect can be implemented across the country, we may finally get a handle on this pandemic, even before a vaccine,” said Grubaugh.
One of the team’s goals was to eliminate the expensive saliva collection tubes that other companies use to preserve the virus for detection. In a separate study led by Wyllie and the team at the Yale School of Public Health, and recently published on medRxiv, they found that SARS-CoV-2 is stable in saliva for prolonged periods at warm temperatures, and that preservatives or specialized tubes are not necessary for collection of saliva.
Of course this part warmed my heart (doubly):
The related research was funded by the NBA, National Basketball Players Association, and a Fast Grant from the Emergent Ventures at the Mercatus Center, George Mason University.
The NBA had the wisdom to use its unique “bubble” to run multiple tests on players at once, to see how reliable the less-known tests would be. This WSJ article — “Experts say it could be key to increasing the nation’s testing capacity” — has the entire NBA back story. At an estimated $10 a pop, this could especially be a game-changer for poorer nations. Furthermore, it has the potential to make pooled testing much easier as well.
Here is an excerpt from the research pre-print:
The critical component of our approach is to use saliva instead of respiratory swabs, which enables non-invasive frequent sampling and reduces the need for trained healthcare professionals during collection. Furthermore, we simplified our diagnostic test by (1) not requiring nucleic acid preservatives at sample collection, (2) replacing nucleic acid extraction with a simple proteinase K and heat treatment step, and (3) testing specimens with a dualplex quantitative reverse transcription PCR (RT-qPCR) assay. We validated SalivaDirect with reagents and instruments from multiple vendors to minimize the risk for supply chain issues. Regardless of our tested combination of reagents and instruments from different vendors, we found that SalivaDirect is highly sensitive with a limit of detection of 6-12 SARS-CoV-2 copies/μL.
No need to worry and fuss about RNA extraction now. Here is the best simple explanation of the whole thing.
The researchers are not seeking to commercialize their advance, rather they are making it available for the general benefit of mankind. Here is Nathan Grubaugh on Twitter. Here is Anne Wyllie, also a Kiwi and a Kevin Garnett fan. A further implication of course is that the NBA bubble is not “just sports,” but also has boosted innovation by enabling data collection.
All good news of course, and Fast at that. And this:
“This could be one the first major game changers in fighting the pandemic,” tweeted Andy Slavitt, a former acting administrator of the Centers for Medicare and Medicaid Services in the Obama administration, who expects testing capacity to be expanded significantly. “Rarely am I this enthusiastic… They are turning testing from a bespoke suit to a low-cost commodity.”
And here is coverage from Zach Lowe. I am very pleased with the course of Fast Grants more generally, and you will be hearing more about it in the future.