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Where We Stand

There is good news and there is bad news.

Let’s start with the good news.The early results from the Pfizer vaccine are very good, 90% efficacy. That will probably fall a bit but it’s very good news not just for the Pfizer vaccine but for most of the vaccines in the pipeline which target the spike protein.

The Pfizer vaccine does require very cold storage which means it won’t work for large parts of the world. A distribution plan is in place for most of the United States and Pfizer already has 50 million doses, which can cover ~25 million people, in storage.

Many thousands of people are dying every week so Pfizer should apply for and the FDA should issue a EUA without further delay.

One issue is, given limited supply, how to distribute the vaccine. I have suggested we randomize distribution across hospitals, police and fire stations, and nursing homes (see also my piece in Bloomberg with Scott Kominers, The Case for a COVID Vaccine Lottery.) A vaccine lottery is fair, it will make distribution easier by limiting the number of vaccination locations and it will in essence create a very large clinical trial. With millions of participants we will be better able to make fine distinctions between the vaccine’s safety and efficacy in different populations and the results will come in quickly. Thus, if we randomize and collect data, limited capacity has a silver lining.

Second issue. Manufacturing capacity. Pfizer will have enough capacity to produce 1.3 billion doses in 2021 which sounds like a lot but it’s a two dose vaccine and there will be losses in distribution so maybe 500 million people vaccinated. We need to vaccinate billions.

The cost to the world economy of COVID is in the trillions so we want to vaccine a lot faster. Faster than private markets are willing to go. There are other vaccines in the pipeline but we still need to ramp up capacity. Increasing capacity is something that Michael Kremer, Susan Athey, myself and others at Accelerating Health Technologies have been working on since the beginning of the crisis. It’s not too late to do more.

Third issue is testing. Trump got it into his head that more tests means more cases when in fact a lot more tests means fewer cases. There is a Laffer curve for testing. Our failure to get ahead of the virus with tests has meant hundreds of thousands of excess deaths. We are still failing this test. Winter is coming. Infections and deaths are both rising.

Biden won’t be president until late January but there are things he can do now. In particular, Congress already allocated $25 billion to testing in April—that was far too little. We spent trillions on relief and comparatively little fighting the virus. But here is the real shocker, most of the $25 billion allocated in April hasn’t been spent. Let me say that again, most of the money allocated for testing in April has not been spent. Biden can signal today that that money and more will be spent. He can also signal, as in fact he has, that he wants rapid antigen tests approved.

Rapid antigen tests are cheap, paper strip tests that can check for infectiousness and are ideal to getting things like the schools running again.

Even if we start vaccinating this year, we won’t vaccinate a majority of the US population until well into 2021. That’s true but what’s underappreciated is that testing, masks, social distancing and vaccines are complementary. The more people are vaccinated, for example, the greater our testing capacity rises relative to the population at risk.

The pandemic is getting worse not better but we did flatten the curve, albeit imperfectly, and now if we can summon the will, we have the tools including rapid antigen tests, vaccines and monoclonal antibodies to really crush the virus.

Wednesday assorted links

1. GMU tenure-track assistant professor ad.

2. “We find that the fiscal, macroeconomic, and health benefits of rapid SARS-CoV-2 screening testing programs far exceed their costs, with the ratio of economic benefits to costs typically in the range of 4-15 (depending on program details), not counting the monetized value of lives saved.”  Link here.

3. Incentive-based approaches to addiction (NYT).

4. “Steiner says they tried negotiating to reopen with Actors’ Equity actors for outdoor shows, and they got nowhere.

5. Do swordfish stab and murder sharks? (NYT)

6. What do we know about business exit during Covid?

Monday assorted links

1. On the history and use of EUAs (NYT).

2. “…income dispersion created by a higher U.S. corporate tax rate offsets more than half of the distributional effects of reducing average returns to capital.

3. Sara Lowes on ethnographic and field data in economics.

4. Saez and Zucman respond to their critics in great detail.

5. The value of rapid self-testing for Covid-19.  Yes it works and the medical professionals and the FDA are wrong on this one.

6. Logistical problems with supplying monoclonal antibodies, important.  It is time to stop dumping on this treatment people, and get our act together.  Now.  Let’s not have another fiasco.  And a good NYT story on the whole topic, you can feel the media mood shifting toward the positive and away from the skeptical.

7. Can you even win at the Japanese crane game?  What else is like this?

8. The captain of Operation Warp Speed (WSJ).

9. How it enters your brain.  Or might.

10. A Fine Theorem on Milgrom and Wilson, recommended, note that Milgrom also does not have a Ph.D. in economics.

Wednesday assorted links

1. Now they are cancelling parrots.  And there is no satire anymore.  Or is it Straussian?

2. Oakland airport wants to attract passengers with free rapid Covid testing.

3. Should Matt Yglesias go on the warpath against car seats?

4. Virtual work partners to help you focus.

5. Survey of the evidence on declining Covid death rates.  And here is yet further evidence on the relevance of T-cells.  And new Covid results from lots of Indian data (NYT).

6. 15-minute test coming to Europe (Bloomberg).

7. Good thread on the new fusion developments.

Where and when does herd immunity kick in?

Here is the abstract of a new paper by Axel S LexmondCarlijn JA Nouwen, and John Paul Callan. So herd immunity yes, but at some point after fifty percent:

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.

They offer an implied exposure estimate of 72% for Afghanistan, 67% for Ethiopia, 74% for Kenya, and 80% for Madagascar.  Pakistan clocks in at 72%, South Africa at 71%.  Notice those are not case counts, rather it is working backwards, using a model, to infer exposure rates from the data we do have, assuming that not all cases are being measured.

Here is mostly good NYT coverage on herd immunity theories, though in my view unfair on T-Cell immunity issues — they confuse uncertainty with “there is no reason to believe anything here.”  Here is a new and good NYT article on the Swedish approach.  The different pieces still do not all fit together.

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.

Monday assorted links

1. Might changes in proton density, spurred by solar wind, predict earthquakes?  If true, this would really be something.

2. Violates Godwin’s Law right upfront anyway speak for yourself!  I genuinely find such hostile intentions difficult to understand.

3. Will a growth drug undermine “dwarf pride”? (NYT).

4. Robin Hanson on how and why remote work will matter.

5. Economics of the energy transition.  Some subtle and underpromoted points in this one.

6. Why we can’t have good things: I am not sure how much public health experts are to blame for the problems in this article about why we don’t have home testing.  The FDA won’t approve it?  Do something about that!  (Where is the outcry, other than from Paul Romer?)  The American people aren’t ready for it?  Well, are they ready for the alternatives you are proposing?  Overall I found this NYT piece a depressing sign of American and perhaps also public health malaise.

7. Using banned cell phones for prison extortion by calling loved ones back home, excellent NYT piece, amazing investigative journalism.

Further results on the return to talk therapy

Here was my original post, here is an email response from a specialist in the area, channeled by a reader:

The issue is really, really complicated. I have a lot of data on it because I spent time with Mark Goldenson, interviewing a lot of folks segmented by those who chose to seek mental health assistance from a clinician, those who stayed with that treatment versus those who turned away relatively early, and those who experienced severe mental health conditions that make them think that they should have seen a therapist, but ultimately chose not to, for reasons other than economic ones.

And we also talked to clinicians on the other side of that equation.

So between that and knowing the literature reasonably well, I have a lot of perspective on this.

The first thing is that talk therapy is in general not effective for most people. And I know the paper under examination showed that it’s more effective than antidepressants, but in general, most people do not generally stick with talk therapy. They get a benefit at a reasonably low rate for a reasonably short period of time…

Moreover, there’s some pretty strong evidence that talk therapy or at least CBT is becoming less effective over time – the effect sizes in studies & meta-analyses are going down. And there could be reasons for that that aren’t an indictment of the therapeutic model.

So for example, the modern world could just be becoming more stressful and the therapy is less equipped for it… It could be that as the treatment becomes more popular, rather than the more advanced or cutting-edge therapists using it, it’s used by an increasingly broad set of therapists that include low-skilled or ineffective ones.

So there are a lot of reasons that may not have to do with the merits of CBT as an approach, but the data are reasonably convincing on that front.

I think a lot of people are making a reasonably rational choice that, especially if they’re not going to stick with it for a long period of time, even starting therapy is a low-value proposition.

George Ainslie (the psychologist) has this kind of notion of playing a prisoner’s dilemma with your [future] self… let’s just say I want to start an exercise habit… there are a lot of parallels with exercise and talk therapy.

If I knew for a fact that I was going to stop doing it after one month, it actually doesn’t make sense to start at all. Right, because the benefits of accrued will pretty rapidly deteriorate and it’ll be as if I never did it…

People are not just considering, “Should I try talk therapy?”, they’re considering, “Will I do this for a sufficiently long period of time, or especially can I afford it for a long period of time, to where I will get and maintain the benefits from doing it?”

And many people do in fact have misinformation about how quickly they can experience certain types of benefits, and how much work is involved – it’s clear that there’s a lot of work involved, and many people don’t want to do that work.

From an operant conditioning standpoint, the experience of a therapy session is frankly more punishing than it is rewarding (for many people, a lot of the time). Like any negative stimulus, they’re going to engage in behaviors that cause that stimulus to be experienced at a lower rate.

Sometimes the benefits don’t accrue during the session, they accrue afterwards. It takes a lot of work to experience them and [can] involve emotional trauma to even retrieve them.

It’s not consistent with people’s ROI calculation, or what they would like to see in their ROI calculation. Again, it’s really similar to physical exercise – we know physical exercise works. It works better than antidepressants. It accrues all the benefits that this paper Cowen cited discovered in terms of energy and mood and earnings and so on and so forth.

But people still don’t engage in exercise, and in fact I think the rate of physical activity is actually on the decline, in the industrialized world at least.So, it’s more complex than “Does the behavior accrue benefits if you do it consistently?” It’s also not entirely about access because many forms of physical activity are free, and as the paper examines the seeking of talk therapy is not super sensitive to [price].

So it goes beyond the mere cost of the service, although the cost of the services is definitely prohibitive for a large cross-section of people.

How does ketamine or any other substance relate to this?

I think it relates very favorably in that people may actually have the opposite misconception around psychedelic-assisted therapy. They might view regular talk therapy as something where they’re going to have to do this tedious hour a week for months before they get any benefits or they solve any problems in their lives.

[With ketamine] they probably think that they’re going to do one ketamine session, and all of their issues are going to be solved right their PTSD is cured and they no longer experience any symptoms of anxiety, depression, etc… It’s probably a little bit overhyped in the minds of people who have only casually exposed themselves – they’re seeing an article in The New Yorker, or they’re seeing it on a blog, or someone goes on a podcast and talks about an experience. They’re not looking at it with the measured view of someone from the Johns Hopkins team or whatever. So I think that it does work in your favor….

People may overestimate the level of benefit they’re likely to achieve and it seems like the medicine is doing the work, rather than them. Even though I know that that isn’t really the case….

By the way, fun stuff from that research sprint we did with Goldenson  – the average person in our cohort (who did ultimately get therapy), put it off for over two years.

It was a pretty wide range – some people sought help after, perhaps, six weeks I think was the shortest. Nobody has a bad day or think they’re experiencing depression or experiencing dysfunction in their work life or their romantic life or whatever it is and goes straight to a therapist…

They also tend to do a fair bit of research – they research different therapeutic methods and kind of choose one that fits their personality or their values, almost more so than efficacy.

And most of the people who ended up with a stable relationship with a provider trial between two and five different folks.

Those words are from Chris York, via MR reader Milan Griffes.

The Beginning of the End?

It’s taken far too long and it’s still not FDA approved for at-home use or for asymptomatic individuals but the new $5,15-minute, easy to use, Abbott test and the Trump administration’s promise to purchase 150 million of them is a big deal. Abbott has been building capacity for months according to their lead scientist interviewed in the Atlantic by Alex Madrigal and in a few weeks will be producing 50 million tests a month:

Madrigal: Fifty million tests a month is a huge number. That’s more than twice the number of tests the U.S. completes in a month. How did you ramp up production so massively?

Hackett: This was the challenge of this program. We needed some sort of reliable testing that could be affordable and that doesn’t require instrumentation. You need scale. The more frequently you could test people, frankly, even tests with lower sensitivity would be very effective at identifying people quickly and slowing the spread. As we were developing the test, there were people working in parallel looking at supply chain and logistics. Abbott took a lot of risk—hundreds of millions of dollars were spent building two new manufacturing facilities focused solely on those tests. We hoped we could come to a solution that would be where we needed it from an overall accuracy perspective, but if you weren’t building capability simultaneously, there was no way it could be the answer.

The US has performed about 80 million tests since the pandemic began, so an additional 50 million tests a month is a big increase in capacity. As noted, the test is not approved for at-home use but it’s a CLIA-waived test which means that a doctor’s office, a CVS or Walmart clinic, even a school nurse could qualify for a waiver and perform the tests. The test is not approved for asymptomatic individuals but I suspect that won’t mean much in practice, it can be prescribed off-label although the fact that a prescription is required is limiting. I hope the necessity for a prescription will be lifted as we get more experience with these tests. False positives (~1.5%) are low and by taking the strain off the PCR system we can improve triage and afford to do more double checks. False positives will be more of an issue as we wipe out the virus but that will take time.

I hope these tests will open up air travel within a month or two. I also hope to see more of these types of tests approved. Derek Lowe has more technical details.

It won’t be all smooth sailing, Abbott may not be able to produce as much or as quickly as they say they can and quality in the field may fall. The government may distribute the tests poorly. The virus could pickup in the fall, as in 1918. I expect more problems and challenges but we now have a chance to get ahead of the virus which is very welcome news.

Addendum: This type of public-private partnership with private firms building capacity in advance of approval for tests and vaccines on the foundation of government push and pull funding is exactly the structure that the Accelerating Health Technologies team has been recommending both to the US government and to governments around the world.

Shoring Up the Vaccine Supply Chain

Supply chains were hit hard early in the pandemic. Disinfectant couldn’t be produced because of a lack of bottles, tests couldn’t be processed because nasal swabs or PPE wasn’t available, the decline of passenger air traffic hit commercial delivery and so forth. I worry about forthcoming stresses on the vaccine supply chain. Billions of doses of vaccine will be demanded in the next year and a lot will depend on complicated supply lines including cold storage, air traffic, styrofoam, vials, bags, needles and many other inputs. Companies and the awesome team at CEPI (give them all a Nobel prize) are planning for vials and needles and other inputs but there are many non-obvious inputs higher up in the supply chain that also need shoring up.

Shark livers–they make vaccines better! From https://www.dutchsharksociety.org/do-you-have-a-shark-on-your-face/

Writing in Bloomberg, Scott Duke Kominers and I look at some of the odder inputs to vaccines like horseshoe crab blood, shark livers and the vaccinia capping enyzme, VCE. We are actually not too worried about horseshoe crab blood and shark livers as these are used in other industries. Shark livers, for example, are used to produce a lot of cosmetics so we should be able to divert supply as needed. VCE, however, is rarer.

DNA and mRNA vaccine technologies have shown promising results, and two of the leading vaccine contenders, from Pfizer Inc. and Moderna Inc., use mRNA technology. But mRNA has never been used to produce a commercial vaccine for humans, let alone at scale. And scaling these technologies may not be easy. In particular, mRNA degrades rapidly. To prevent this, it must be “capped” by a very rare substance called vaccinia capping enzyme.

Just over 10 pounds of this VCE is enough to produce a hundred million doses of an mRNA vaccine — but the current manufacturing processes for VCE require so much bioreactor capacity that making 10 pounds would cost about $1.4 billion. More important, global bioreactor capacity cannot support production at that level while also producing other vaccines and cancer-fighting drugs.

If we work hard now, we may be able to find more efficient means of producing VCE. Expanding bioreactor production and repurposing bioreactors from existing large-scale industrial applications will also help to lessen the pressure on the supply chains for multiple types of vaccines.

In addition to supply chains per se we also face the problem that companies are not raising prices enough. Ironically, this means that we need more public investment.

Of course, we might think that private companies would have incentives to coordinate supply chains themselves — and to some extent, they are doing so. But many have pledged to keep their vaccine prices close to costs, both out of altruism and because they may fear public backlash (or legal action) if they’re perceived as “price gouging” in the middle of a pandemic. And if companies don’t stand to profit much from Covid-19 vaccines, then they don’t have much incentive to invest in increasing capacity. In short: If prices can’t rise, then the only way to encourage companies to invest more in production is to reduce their costs — and that means we need public investment.

More generally, it’s not too late to be building more vaccine capacity and to repurpose bioreactor capacity from non-GMP sources, perhaps including veterinary and food sources. There are lots of vaccines in development. The science is promising. We need to take action now so that we can deliver on that promise.

Read the whole thing.

Why herd immunity is worth less than you might think

That is the topic of my latest Bloomberg column.  The evidence in favor of at least partial herd immunity continues to pile up, but still don’t get too cheery.  One worry is that herd immunity might prove only temporary:

First, many herd immunity hypotheses invoke the idea of “superspreaders” — that a relatively small number of people account for a disproportionate amount of the contagion. Perhaps it is the bartenders, church choir singers and bus drivers who spread the virus to so many others early on in the pandemic. Now that those groups have been exposed to a high degree and have acquired immunity, it might be much harder to distribute the virus.

That logic makes some sense except for one issue: namely, that the identities of potential superspreaders can change over time. For instance, perhaps choir singers were superspreaders earlier in the winter, but with most choral singing shut down, maybe TSA security guards are the new superspreaders. After all, air travel has been rising steadily. Or the onset of winter and colder weather might make waiters a new set of superspreaders, as more people dine inside.

In other words, herd immunity might be a temporary state of affairs. The very economic and social changes brought by the virus may induce a rotation of potential superspreaders, thereby undoing some of the acquired protection.

In other words, the fight never quite ends.  Here is another and possibly larger worry:

Another problem is global in nature and could prove very severe indeed. One possible motivation for the herd immunity hypothesis is that a significant chunk of the population already had been exposed to related coronaviruses, thereby giving it partial immunity to Covid-19. In essence, that “reservoir” of protected individuals has helped to slow or stop the spread of the virus sooner than might have been expected.

There is a catch, however. If true, that hypothesis means that the virus spreads all the more rapidly among groups with little or no protection. (Technically, if R = 2.5, but say 50% of the core population has protection, there is an R of something like 5 for the unprotected population, to get the aggregate R to 2.5.) So if some parts of the world enjoy less protection from cross-immunities, Covid-19 is likely to ravage them all the more — and very rapidly at that.

Again, this is all in the realm of the hypothetical. But that scenario might help explain the severe Covid-19 toll in much of Latin America, and possibly in India and South Africa. Herd immunity, as a general concept, could mean a more dangerous virus for some areas and population subgroups.

There are further arguments at the link.

The case for GPT-3

That is the topic of my latest Bloomberg column, here is one excerpt:

As a very rough description, think of GPT-3 as giving computers a facility with words that they have had with numbers for a long time, and with images since about 2012.

The core of GPT-3, which is a creation of OpenAI, an artificial intelligence company based in San Francisco, is a general language model designed to perform autofill. It is trained on uncategorized internet writings, and basically guesses what text ought to come next from any starting point. That may sound unglamorous, but a language model built for guessing with 175 billion parameters — 10 times more than previous competitors — is surprisingly powerful.

The eventual uses of GPT-3 are hard to predict, but it is easy to see the potential. GPT-3 can converse at a conceptual level, translate language, answer email, perform (some) programming tasks, help with medical diagnoses and, perhaps someday, serve as a therapist. It can write poetry, dialogue and stories with a surprising degree of sophistication, and it is generally good at common sense — a typical failing for many automated response systems. You can even ask it questions about God.

Imagine a Siri-like voice-activated assistant that actually did your intended bidding. It also has the potential to outperform Google for many search queries, which could give rise to a highly profitable company.

GPT-3 does not try to pass the Turing test by being indistinguishable from a human in its responses. Rather, it is built for generality and depth, even though that means it will serve up bad answers to many queries, at least in its current state. As a general philosophical principle, it accepts that being weird sometimes is a necessary part of being smart. In any case, like so many other technologies, GPT-3 has the potential to rapidly improve.

There is much more at the link.

Rescheduling for thee, but not for me

When Wisconsin Republicans refused to move their election day, Democrats, experts, and various media types decried the decision as immoral and dangerous during a pandemic. “Regularly scheduled, orderly elections with direct governmental consequences were either too dangerous, or insufficiently compelling,” Adam wrote in a late-night email. “Contrast that, of course, with Democrats’s evident belief that we absolutely must not delay these protests against police brutality. The protests—spontaneous not scheduled, disorderly not orderly, emotive not concretely consequential—simply had to go on.”

Protests and demonstrations are more important and indispensable than elections. The deliberate act of voting, essential to a democracy, can be put on a schedule delay but political catharsis must proceed on its own schedule. Mario Cuomo used to say that “We campaign in poetry but we govern in prose.” Now it’s poetry or nothing.

Here is more by Jonah Goldberg.  I am not looking to attack or make trouble for any individual person here, so no link or name, but this is from a leading figure in biology and also a regular commenter on epidemiology:

As a citizen, I wholeheartedly support the protests nonetheless.

My worries run deep.  Should the original lockdown recommendations have been asterisked with a “this is my lesser, non-citizen self speaking” disclaimer?  Should those who broke the earlier lockdowns, to save their jobs or visit their relatives, or go to their churches, or they wanted to see their dying grandma but couldn’t…have been able to cite their role as “citizens” as good reason for opposing the recommendations of the “scientists”?  Does the author have much scientific expertise in how likely these protests are to prove successful?  Does typing the word “c-i-t-i-z-e-n” relieve one of the burden of estimating how much public health credibility will be lost if/when we are told that another lockdown is needed to forestall a really quite possible second wave?  Does the author have a deep understanding of the actual literature on the “science/citizen” distinction, value freedom in science, the normative role of the advisor, and so on?  Does the implicit portrait painted by that tweet imply a radically desiccated, and indeed segregated role of the notions of “scientist” and “citizen”?  Would you trust a scientist like that for advice?  Should you?  And shouldn’t he endorse the protests “2/3 heartedly” or so, rather than “wholeheartedly”?  Isn’t that the mood affiliation talking?

On May 20th, the same source called a Trump plan for rapid reopening (churches too, and much more) “extraordinarily dangerous” — was that the scientist or the citizen talking?  And were we told which at the time?  Andreas’s comments at that above link are exactly on the mark, especially the point that the fragile consensus for the acceptability of lockdown will be difficult to recreate ever again.

If you would like a different perspective, bravo to Dan Diamond.  Here is his article.  And here are some better options for public health experts.  Here is a useful (very rough) estimate of expected fatalities from the protests, though it does not take all-important demonstration effects into account.  I can say I give credit to the initial source (the one I am criticizing) for passing that tweet storm along.

We really very drastically need to raise the quality and credibility of the advice given here.

How tourism will change

That is the topic of my latest Bloomberg column, here is one bit:

Some of the safer locales may decide to open up, perhaps with visitor quotas. Many tourists will rush there, either occasioning a counterreaction — that is, reducing the destination’s appeal — or filling the quota very rapidly. Then everyone will resume their search for the next open spot, whether it’s Nova Scotia or Iceland. Tourists will compete for status by asking, “Did you get in before the door shut?”

Some countries might allow visitors to only their more distant (and less desirable?) locales, enforcing movements with electronic monitoring. Central Australia, anyone? I’ve always wanted to see the northwest coast of New Zealand’s South Island.

Some of the world’s poorer countries might pursue a “herd immunity” strategy, not intentionally, but because their public health institutions are too weak to mount an effective response to Covid-19. A year and a half from now, some of those countries likely will be open to tourism. They won’t be able to prove they are safe, but they might be fine nonetheless. They will attract the kind of risk-seeking tourist who, pre-Covid 19, might have gone to Mali or the more exotic parts of India.

And:

laces reachable by direct flights will be increasingly attractive. A smaller aviation sector will make connecting flights more logistically difficult, and passengers will appreciate the certainty that comes from knowing they are approved to enter the country of their final destination and don’t have to worry about transfers, delays or cancellations. That will favor London, Paris, Toronto, Rome and other well-connected cities with lots to see and do. More people will want to visit a single locale and not worry about catching the train to the next city. Or they might prefer a driving tour. How about flying to Paris and then a car trip to the famous cathedrals and towns of Normandy?

Maybe. But I might start by giving Parkersburg, West Virginia, a try.

Universities with Hospitals and Labs

Mitch Daniels, the President of Purdue, has outlined a preliminary plan to reopen involving test, trace and supported isolation on campus.

We intend to know as much as possible about the viral health status of our community. This could include pre-testing of students and staff before arrival in August, for both infection and post-infection immunity through antibodies. It will include a robust testing system during the school year, using Purdue’s own BSL-2 level laboratory for fast results. Anyone showing symptoms will be tested promptly, and quarantined if positive, in space we will set aside for that purpose.

We expect to be able to trace proximate and/or frequent contacts of those who test positive. Contacts in the vulnerable categories will be asked to self-quarantine for the recommended period, currently 14 days. Those in the young, least vulnerable group will be tested, quarantined if positive, or checked regularly for symptoms if negative for both antibodies and the virus.

This paper provides details on transforming a university lab into a testing center. In essence, a major university with a hospital (which Purdue doesn’t have) should be able to do it technically but to work to reopen for students it probably has to be a university located outside of a major urban area. Here are a few possibilities:

  • Baylor University
  • Vanderbilt University
  • University of Michigan, Ann Arbor
  • University of Virginia
  • University of Iowa
  • University of Utah
  • University of Alabama

Mitch Daniel also notes:

Our campus community, a “city” of 50,000+ people, is highly unusual in its makeup. At least 80% of our population is made up of young people, say, 35 and under. All data to date tell us that the COVID-19 virus, while it transmits rapidly in this age group, poses close to zero lethal threat to them.

which does seem to miss (ahem) an important group necessary for reopening.