In 1957, when flu swept through Hong Kong, Mr [Maurice] Hilleman identified the virus as a new form to which people had no natural immunity and passed on his findings to vaccine-makers. When the virus reached the United States a few months later 40m doses of vaccine were ready to limit its damage.
Here is more from The Economist, circa 2005, via Brian LaRocca. How many of you have heard of Maurice Hilleman? He has other accomplishments, and according to Wikipedia “He is credited with saving more lives than any other medical scientist of the 20th century.” I say he is underrated!
2. 35 predictions about the world after coronavirus, some of them terrible (in quality that is, I don’t mean terribly pessimistic).
9. Chess in the time of corona. I liked this one.
13. “There’s plenty of competition, but most ineffective world leader responding to coronavirus right now goes to Brazil President Bolsonaro. This weekend he’s blasting governors taking lockdown measures. Will seriously damage his mandate.” Link here.
There are two problems, even internal contradictions, with segregating the elderly and letting others return to work. The first is fairly well known. When you run the numbers, as the British did, you find that a lot of young people would die. If we return to work too quickly it could easily happen that 20-40% of the US population gets COVID-19. Suppose 20% of the population gets it–that’s 66 million people. And let’s suppose the death rate is on the low end because healthy, young people get it rather than the elderly, say half of one percent, .005, then we have 330,000 deaths of healthy, young people.
Moreover, the numbers I just gave are conservative and don’t make a lot of sense because if 330,000 die then the hospital system is going to be overwhelmed and the death rate will be higher than .005. An internal contradiction.
The second internal contradiction is less well known. We probably can’t segregate the elderly because the more young people get COVID-19 the less realistic protecting a subset of the population becomes. In other words, the premise of the segregation argument is that we can protect the elderly but that premise becomes less plausible the more COVID-19 spreads but allowing it to spread is why we were locking down the elderly. An internal contradiction.
Are there some scenarios where all this works out? Probably but I wouldn’t bet on hitting the trifecta. The lesson of COVID-19 is that like it or not we are all in this together.
In our textbook, Modern Principles of Economics, Tyler and I explain the benefits of free trade and show why some common arguments against free trade are mistaken. Our goal, however, is to teach students how to think like economists and so we also explain the costs of free trade. In particular, we indicate the strongest arguments against free trade and explore when those arguments best apply. Here’s one of the better arguments against free trade, straight from the book:
If a good is vital for national security but domestic producers have higher costs than foreign producers, it can make sense for the government to tax imports or subsidize the production of the domestic industry. It may make sense, for example, to support a domestic vaccine industry. In 1918, more than a quarter of the U.S. population got sick with the flu and more than 500,000 died, sometimes within hours of being infected. The young were especially hard-hit and, as a result, life expectancy in the United States dropped by 10 years. No place in the world was safe, as between 2.5% and 5% of the entire world population died from the flu between 1918 and 1920. Producing flu vaccine requires an elaborate process in which robots inject hundreds of millions of eggs with flu viruses. In an ordinary year, there are few problems with buying vaccine produced in another country, but if something like the 1918 flu swept the world again, it would be wise to have significant vaccine production capacity in the United States.
If I may be permitted to advertise a bit (more). In Modern Principles, we explain the concept of externalities using flu shots. In macroeconomics, we deal with both real shocks and demand shocks and we list pandemics as one example of a real shock. We also explain how shocks are amplified and can create dis-coordination. These relevant, real world examples in Modern Principles are not an accident. There are different styles of textbooks. Some are written in a vanilla style so they don’t need to be updated or revised very often. In contrast, we wanted Modern Principles to have modern examples and to be relevant to the times. Sometimes, however, we’d like it to be a little less relevant.
Andrew Ross Sorkin explains (NYT):
The fix: The government could offer every American business, large and small, and every self-employed — and gig — worker a no-interest “bridge loan” guaranteed for the duration of the crisis to be paid back over a five-year period. The only condition of the loan to businesses would be that companies continue to employ at least 90 percent of their work force at the same wage that they did before the crisis. And it would be retroactive, so any workers who have been laid off in the past two weeks because of the crisis would be reinstated.
Strain and Hubbard call for $1.2 trillion in lending to smaller businesses (Bloomberg). John Cochrane considers a version of the plan. Here is Brunnermeier, Landau, Pagano, and Reis. I have been pondering the following points:
1. If you are an optimist about the cycle of recovery, this is very likely a good idea. If you let those companies fall apart, there is a significant loss of organizational capital and the matching problems in the labor markets have to be solved all over again. Recent experience on that front is not so encouraging.
2. If you are a pessimist about the cycle of recovery, I am less sure how well this will work. Let’s say a vaccine is difficult and there a few waves of the virus. Many of the smaller or even larger businesses may be going under anyway, as they cannot live off aid forever. In the meantime, you might actually want those resources to be reallocated to good transport, biomedical testing, and so on. If the wartime analogy is apt, you don’t want to freeze the previous capital structure into place, unless of course you get lucky and win the war early.
3. If you a pessimist about the solvency of banks (have you ever seen a stress test for 30% unemployment?), you have not gotten the government out of the business of capital allocation.
4. The bridge loans might work especially poorly for start-ups. Yes, StubHub or some company like that is around for the long run, and if the bridge loans can keep them up and running until concerts return, so much the better. But what about the eighty wanna-bees next in line, most of whom are likely to fail? Do they too get bridge loans? (Do note the ecosystem as a whole is yielding positive value.) The market itself chose the venture capital financing form for those entities, not debt. And yet now the government is stepping in and propping them up with debt, even though we know virtually all of them are likely to fail (even pre-coronavirus that was the case). You might think “well, we will know not to do that.” But on what legal basis would those other “likely to fail start-ups” be excluded from the bridge loans?
4b. Is it all about “banks decide”? How do we stop banks from simply hoarding the new money? (The Fed already has flooded the banking system with liquidity.) Just loaning the money to super-safe firms for de facto negative rates? What exactly are the regulatory requirements here? To the extent the loans are de facto guaranteed, won’t banks lend to a large number of lemons? What do the interest rates and collateral requirements look like on these loans and how are those set in what is now a non-competitive setting?
5. Overall my sense is that American policy, if only for cultural reasons, has to proceed on an optimistic basis. It is not clear what the relevant alternative is, and I do not oppose bridge loans. Nonetheless I am seeing too many people jump uncritically at bridge loans with a “throw everything at the wall” approach and not thinking hard enough about their possible downsides. At the very least, being critical about bridge loans will help us make bridge loans better.
6. No, I don’t favor governmental bridge loans for non-profits. De facto, that this means this is a huge relative shift of resources away from non-profits and toward businesses. YMMV.
7. I have received numerous reader emails telling me how bad, slow, and cumbersome is the Small Business Administration process for getting loans. Will this new regime do better?
8. It is the same government that could not organize testing and mask production that we are expecting to run what might amount to a $1 trillion plus bridge loans program.
Have a nice day.
We extend the canonical epidemiology model to study the interaction between economic decisions and epidemics. Our model implies that people’s decision to cut back on consumption and work reduces the severity of the epidemic, as measured by total deaths. These decisions exacerbate the size of the recession caused by the epidemic. The competitive equilibrium is not socially optimal because infected people do not fully internalize the e§ect of their economic decisions on the spread of the virus. In our benchmark scenario, the optimal containment policy increases the severity of the recession but saves roughly 0.6 million lives in the U.S.
I would add this: if you hold the timing and uncertainty of deaths constant, death and output tend to move together. That is, curing people and developing remedies and a vaccine will do wonders for gdp, through the usual channels. The tricky trade-off is between output and the timing of deaths. Whatever number of people are going to die, it is better to “get that over with” and clear up the uncertainty. Policy is thus in the tricky position of wishing to both minimize the number of deaths and yet also to speed them along. Good luck with that! In terms of an optimum, might it be possible that some of the victims do not…get infected and die quickly enough? Might that be the more significant market failure?
Via Harold Uhlig. In any case, kudos to the authors for focusing their energies on this critical problem.
Angela Merkel’s cabinet is meeting on Monday to approve new borrowing of €356bn — equivalent to nearly 10 per cent of Germany’s gross domestic product — marking a new era in fiscal policy and a radical departure from Berlin’s long-held aversion to debt.
Here is the FT piece, but this is being covered everywhere. (Imagine a day where this isn’t even necessarily the biggest story, and here we are.) Of course the content of the spending matters a great deal, but this is in principle the right thing to do. But here is the catch: out on social media, and in the old days of the blogosphere, there was so much Merkel hatred: “the austerity queen who killed thousands,” etc. But now she has been vindicated. We all can agree that a government should (on average) run surpluses in good times and deficits in bad times. Well…2011-2012…those were the good times. Yikes.
Merkel goes up in status with this, big time. And of course it is no surprise that a bunch of Germans would have a better sense of what the bad times really can look like.
Correlation ain’t causation, but nonetheless it is worth looking at correlation:
Via Daniel Wilson. And here is a story about defiant Iranians.
1. Segregating old people, and letting others go about their regular business. Given how many older people now work (and vote), and how many employees in nursing homes are young, I’ve yet to see a good version of this plan, but if you favor it please do try to write one up. One of you suggested taking everyone over the age of 65 and encasing them in bubble wrap, or something.
3. Testing as many Americans as possible, or at least a representative sample, to get data.
I hope to analyze these more in the future.
1. A thread on the economics of Covid vaccines. Good stuff.
2. The cultural foundations of democracy. Not about Covid, but interesting.
6. Alec Stapp on what exactly went wrong with testing. “There have been three major regulatory barriers so far to scaling up testing by public labs and private companies: 1) obtaining an Emergency Use Authorization (EUA); 2) being certified to perform high-complexity testing consistent with requirements under Clinical Laboratory Improvement Amendments (CLIA); and 3) complying with the Health Insurance Portability and Accountability Act (HIPAA) Privacy Rule and the Common Rule related to the protection of human research subjects.”
11. New calibrated estimates, possibly important, no paper but with NYT graphics. One implication is that already far more people have it than we had thought.
I am happy to announce the first cohort of Emergent Ventures prize winners for their work fighting the coronavirus. Here is a repeat of the original prize announcement, and one week or so later I am delighted there are four strong winners, with likely some others on the way. Again, this part of Emergent Ventures comes to you courtesy of the Mercatus Center and George Mason University. Here is the list of winners:
Dr. Helen Y. Chu, an infectious disease expert in Seattle, knew that the United States did not have much time…
As luck would have it, Dr. Chu had a way to monitor the region. For months, as part of a research project into the flu, she and a team of researchers had been collecting nasal swabs from residents experiencing symptoms throughout the Puget Sound region.
To repurpose the tests for monitoring the coronavirus, they would need the support of state and federal officials. But nearly everywhere Dr. Chu turned, officials repeatedly rejected the idea, interviews and emails show, even as weeks crawled by and outbreaks emerged in countries outside of China, where the infection began.
By Feb. 25, Dr. Chu and her colleagues could not bear to wait any longer. They began performing coronavirus tests, without government approval.
What came back confirmed their worst fear. They quickly had a positive test from a local teenager with no recent travel history. The coronavirus had already established itself on American soil without anybody realizing it.
And to think Helen is only an assistant professor.
Data gathering and presentation prize: Avi Schiffmann
Here is a good write-up on Avi Schiffmann, excerpt:
A self-taught computer maven from Seattle, Avi Schiffmann uses web scraping technology to accurately report on developing pandemic, while fighting misinformation and panic.
Avi started doing this work in December, remarkable prescience, and he is only 17 years old. Here is a good interview with him:
I’d like to be the next Avi Schiffmann and make the next really big thing that will change everything.
Here is Avi’s website, ncov2019.live/data.
Prize for good policy thinking: The Imperial College researchers, led by Neil Ferguson, epidemiologist.
Neil and his team calculated numerically what the basic options and policy trade-offs were in the coronavirus space. Even those who disagree with parts of their model are using it as a basic framework for discussion. Here is their core paper.
The Financial Times referred to it as “The shocking coronavirus study that rocked the UK and US…Five charts highlight why Imperial College’s research radically changed government policy.”
The New York Times reported “White House Takes New Line After Dire Report on Death Toll.” Again, referring to the Imperial study.
Note that Neil is working on despite having coronavirus symptoms. His earlier actions were heroic too:
Ferguson has taken a lead, advising ministers and explaining his predictions in newspapers and on TV and radio, because he is that valuable thing, a good scientist who is also a good communicator.
He is a workaholic, according to his colleague Christl Donnelly, a professor of statistical epidemiology based at Oxford University most of the time, as well as at Imperial. “He works harder than anyone I have ever met,” she said. “He is simultaneously attending very large numbers of meetings while running the group from an organisational point of view and doing programming himself. Any one of those things could take somebody their full time.
“One of his friends said he should slow down – this is a marathon not a sprint. He said he is going to do the marathon at sprint speed. It is not just work ethic – it is also energy. He seems to be able to keep going. He must sleep a bit, but I think not much.”
Prize for rapid speedy response: Curative, Inc. (legal name Snap Genomics, based in Silicon Valley)
Originally a sepsis diagnostics company, they very rapidly repositioned their staff and laboratories to scale up COVID-19 testing. They also acted rapidly, early, and pro-actively to round up the necessary materials for such testing, and they are currently churning out a high number of usable test kits each day, with that number rising rapidly. The company is also working on identifying which are the individuals most like to spread the disease and getting them tested first. here is some of their progress from yesterday.
Testing and data are so important in this area.
General remarks and thanks: I wish to thank both the founding donor and all of you who have subsequently made very generous donations to this venture. If you are a person of means and in a position to make a donation to enable this work to go further, with more prizes and better funded prizes, please do email me.
I’ve read the comments section of your post on herd immunity pretty carefully and a point nobody has yet brought out is the importance of variance in R0. Suppose that an average R0 of 2.72 is made up of a) a low spreader subset of 90% of the population with R0 of 0.8 and b) 10% of super spreaders with an R0 of 20.
If what makes super spreaders different from the rest is just some invisible genetic factor, then using the average R0 of 2.72 in simulations may be a good approximation, and relaxing social distancing after the first wave may indeed lead to a large second wave.
But if what makes super spreaders different is a behavioral characteristic that also makes them much more likely to be infected than the rest of the population during the first wave, then the effect of the first wave may be much more permanent than the average R0 of 2.72 can capture.
Suppose the first wave infects 5% of low spreaders and 50% of high spreaders. Then after the first wave the uninfected population consists of a much smaller proportion of super spreaders than before and R0 for that population drops dramatically (to 1.86 in this example).
More generally if there is variance in systematic individual characteristics that affect R0 (and not just chance factors particular to the first wave), then stopping the epidemic requires only that enough of the high R0 individuals acquire immunity. That may happen naturally in the first wave, or it might be something that policy could influence. We may soon be able to test this by looking for a second wave in China as restrictions are relaxed.
An even more general point is that, unlike in many other familiar contexts, inequality in R0 is really good news. It reduces the size of the set of individuals whose behavior you need to influence. The more inequality the better!
That is the topic of my latest Bloomberg column. Yes trolling, but trolling with the truth. Here are scattered excerpts:
— The egalitarianism of the progressive left also will seem like a faint memory. Elites are most likely to support wealth redistribution when they feel comfortable themselves, and indeed well-off coastal elites in California and the Northeast are a backbone of the progressive movement. But when these people feel threatened in their lives or occupations, or when the futures of their children suddenly seem less secure, redistribution will not be such a compelling ideal…
— The case for mass transit also will seem weaker, because subways and buses will be associated with the fear of Covid-19 transmission. In a similar fashion, the forces of NIMBY will become stronger, relative to those of YIMBY, because people secure in their isolated suburban homes will feel less stressed than those in densely packed urban apartment buildings.
— There is likely to be much more government intervention in some parts of the health-care sector, but it will focus on scarce hospital beds and ventilators, and enforce nasty triage, rather than being a benevolent move toward universal coverage. If anything, it will drive home the message that supply constraints are binding and America can’t have everything — hardly the traditional progressive message.
— — The climate change movement is likely to be another victim. How much have you heard about Greta Thunberg lately? Concern over the climate will seem like another luxury from safer and more normal times. In addition, the course of anti-Covid-19 efforts may not prove propitious for the climate change movement. If the fight against Covid-19 suddenly improves (perhaps a vaccine working very quickly?), Americans may come to expect the same in the fight against climate change.
There is much more at the link, of course some of you will hate it. And of course Sanders and Warren did not exactly dominate voter sentiment, and that was largely pre-Covid.
And, despite not knowing what threat the SETREP-ID would be enacted for, the group had pre-emptive ethical clearance to immediately gather samples from patients – something which would take weeks or months in other countries.
It is believed that this has saved thousands of lives, here is the full story, via Rohan Claffy.
Adam Tooze at the NYT has the very best piece I have seen on this question. You do need to read the whole thing, but here is part of the opening bit:
For the second time this century, the world is facing an acute shortage of dollar funding. This is a big problem: An enormous amount of global financial activity depends on the use of the dollar. If we are to contain the fallout from the crisis, America’s central bank must act as a lender of last resort not just to America’s financial system but also to the entire world’s.