Category: Medicine

My Conversation with Adam Tooze

Tinges of Covid-19, doses on financial crises, but mostly about economic history.  Here is the audio and transcript.  Here is the summary:

Adam joined Tyler to discuss the historically unusual decision to have a high-cost lockdown during a pandemic, why he believes in a swoosh-shaped recovery, portents of financial crises in China and the West, which emerging economies are currently most at risk, what Keynes got wrong about the Treaty of Versailles, why the Weimar Republic failed, whether Hitler was a Keynesian, the political and economic prospects of various EU members, his trick to writing a lot, how Twitter encourages him to read more, what he taught executives at BP, his advice for visiting Germany, and more.

Here is one excerpt:

And:

Tooze’s discussion of his own career and interests, toward the end, is hard to excerpt but for me the highlight of the conversation.  He also provided the best defense of Twitter I have heard.

Definitely recommended.

Did non-pharmaceutical interventions actually help against the Spanish flu?

From three economics Ph.D students at Harvard, namely Andrew Lilley, Matthew Lilley, and Gianluca Rinaldi:

Using data from 43 US cities, Correia, Luck, and Verner (2020) find that the 1918 Flu pandemic had strong negative effects on economic growth, but that Non Pharmaceutical Interventions (NPIs) mitigated these adverse economic effects. Their starting point is a striking positive correlation between 1914-1919 economic growth and the extent of NPIs adopted at the city level. We collect additional data which shows that those results are driven by population growth between 1910 to 1917, before the pandemic. We also extend their difference in differences analysis to earlier periods, and find that once we account for pre-existing differential trends, the estimated effect of NPIs on economic growth are a noisy zero; we can neither rule out substantial positive nor negative effects of NPIs on employment growth.

I am very willing to publish a response from the original authors on this one.

Why isn’t Belarus being hit harder?

This is from my email, from Hayden Murray:

I’m an American, who lives in Belarus…[various disclaimers]

There’s no doubt that the government is underreporting Coronavirus deaths here, but also there’s no denying that there is very little problem. I don’t know anyone affected, (or even anyone that knows anyone,) yet I know many in California.

I think you were probably at least somewhat right with your idea that low consumption is already part of the culture. I think the difference in deaths is primarily due to better isolating the elderly, though. I’ve never seen an elderly person at a restaurant here, and I’ve been here for years. Compare this to California – and I mainly see older people (and often quite elderly) people at restaurants.

In addition, it seems that most elderly people in Belarus live in villages – which are often extremely isolated, even in normal times. Also, I have never heard of a nursing home here. I’ve seen many families taking care of extremely old family members, though. So, maybe this alone could explain some major differences. Couldn’t find hard stats on it though. But, putting all our most vulnerable into place, and then shuffling low-wage workers in and out constantly – seems like a recipe for disaster right now.

A multi-risk SIR model with optimally targeted lockdown

Or you could say “all-star economists write Covid-19 paper.”  Daron Acemoglu, Victor Chernozhukov, Iván Werning, and Michael D. Whinston have a new NBER working paper.  Here is part of the abstract:

For baseline parameter values for the COVID-19 pandemic applied to the US, we find that optimal policies differentially
targeting risk/age groups significantly outperform optimal uniform policies and most of the gains can be realized by having stricter lockdown policies on the oldest group. For example, for the same economic cost (24.3% decline in GDP), optimal semi–targeted or fully-targeted policies reduce mortality from 1.83% to 0.71% (thus, saving 2.7 million lives) relative to optimal uniform policies. Intuitively, a strict and long lockdown for the most vulnerable group both reduces infections and enables less strict lockdowns for the lower-risk groups.

Note the paper is much broader-ranging than that, though I won’t cover all of its points.  Note this sentence:

Such network versions of the SIR model may behave very differently from a basic homogeneous-agent version of the framework.

And:

…we find that semi-targeted policies that simply apply a strict lockdown on the oldest group can achieve the majority of the gains from fully-targeted policies.

Here is a related Twitter thread.  I also take the authors’ model to imply that isolating infected individuals will yield high social returns, though that is presented in a more oblique manner.

Again, I would say we are finally making progress.  One question I have is whether the age-specific lockdown in fact collapses into some other policy, once you remove paternalism as an underlying assumption.  The paper focuses on deaths and gdp, not welfare per se.  But what if older people wish to go gallivanting out and about?  Most of the lockdown in this paper is for reasons of “protective custody,” and not because the older people are super-spreaders.  Must we lock them up (down?), so that we do not feel too bad about our own private consumption and its second-order consequences?  What if they ask to be released, in full knowledge of the relevant risks?

In the Race for a Coronavirus Vaccine, We Must Go Big

Today in the New York Times I have an op-ed with Susan Athey, Michael Kremer and Christopher Snyder. We argue for a big program to invest in vaccine capacity before any vaccine is tested and approved. We agree with Bill Gates that we want the vaccine factories to be warmed up by the time a vaccine is approved. We can’t leave it all to Gates, however. The US economy is hemorrhaging $150-$350 billion a month so the benefits of a vaccine to society are huge and we should go big.

Today, the U.S. government could go big and create a Covid-19 vaccine A.M.C., guaranteeing to spend about $70 billion on new vaccines — enough to make direct investments to support capacity installation or to repurpose capacity and to pay, say, $100 per person for the first 300 million people vaccinated.

An investment of that size can anticipate and overcome several challenges typical of vaccine development. If we want to achieve a 90 percent probability of success, we must take into account historical rates of success from publicly available data; doing that suggests that we need to actively pursue not two or three vaccine candidates, but 15 to 20.

…Usually, to avoid the risk of investing in capacity that eventually proves worthless, firms invest in large-scale capacity only after the vaccine has proved effective. But in the middle of a pandemic, there are huge social and economic advantages to having vaccines ready to use as soon as they have been approved. If we leave it entirely to the market, we will get too little vaccine too late.

An advance market commitment for Covid-19 should combine “push” and “pull” incentives. The “pull” incentive is the commitment to buy 300 million courses of vaccine at a per-person price of $100, for vaccines produced within a specified time frame. If multiple vaccines are developed, the A.M.C. fund will have authority to choose products to purchase based on efficacy, the availability of sufficient vaccine for timely vaccination or suitability for different population groups. So firms compete to serve the first 300 million people with the most attractive vaccines, and the “pull” component provides strong incentives for both speed and quality.

The “push” incentive guarantees firms partial reimbursement for production capacity built or repurposed at risk and partial reimbursement as they achieve milestones. The partial reimbursement ensures that manufacturers have “skin in the game,” while inducing them to build large-scale capacity before approval is certain.

More than usual, read the whole thing and please do help to circulate the ideas by posting and tweeting.

The op-ed draws on the work of a large team of economists and statisticians who have been working days and nights for weeks. You can find out more at AcceleratingHT where we will soon be posting additional analysis and tools.

It’s a great privilege for me to be working with this group. One day I will write the story but for now let me just say that I have never seen such a brilliant and dedicated group come together to apply their skills to a problem of such importance and urgency.

What happened to male youth movements?

I’ve been wondering, at what point did youth movements dissipate in America (and the West more generally?). It seems to be a perfect opportunity for organization and deployment of 18-25 year old men, who are nearly unphased by covid.

As workers in essential meat plants, factories, and other labor intensive supply chains grow sick and die, it seems that having an organized workforce of young men prepared to temporarily take over would be an ideal situation.  (Women of course have a role to play, but they are already playing an outsized role in medicine).

More generally, I’m reminded of your previous blog post ‘What the hell is going on?’. This type of event seems to be exactly what wayward young men live for — the ability to contribute to something greater than themselves. Combined with the fact that healthy young men are at remarkably low risk, isn’t the opportunity to support their country at little risk to themselves, and in return gain high status, the ideal situation?

What do you think the failure mode is here? Why does the idea of mobilizing a few thousand men or women in each locality to contribute to the greater good feel so weird? It’s so weird no one even suggests it. Could I suggest that this  even feels embarrassing? Why?

That is from an email from Simon Riddell.

Why aren’t there more Covid-19 deaths in U.S. prisons?

There are about 2.3 million prisoners in the United States, and so far the number of reported Covid-19 deaths is 251, or higher by the time you are reading this.  If you know of a better data source, please let me know.

For purposes of contrast, Rhode Island has about a million people and currently 266 deaths (and rising).  Connecticut has 2,339 Covid-19 deaths, and a population of about 3.5 million, or in other words almost ten times the deaths as the prisons without having even twice the population.  In other words, at least nominally the prison system seems to be doing better against Covid-19 than either The Nutmeg State or The Ocean State.

And I read this kind of line quite frequently:

Ohio officials found that more than 80% of those inmates had the virus with the vast majority showing no symptoms.

Yet asymptomatic cases in non-prison samples are often in the 40-50% range, not higher.  Furthermore, the Bureau of Prisons just tested 2000 prisoners (how random a sample?…but don’t forget the false negatives!) and 70% tested positive.  Again, the death rate does not seem to be through the ceiling.

How can this heterogeneity be?  I see a few options:

1. Actual Covid-19 deaths in prisons are much higher than reported.  This is quite possible, though I don’t see the media coverage that might go along with this.  At the very least, prisons might have longer death reporting and classification lags than does Connecticut.

2. Prison deaths are about to explode, due to exponential growth in the number of cases and their progression through time.  Again, this is quite possible, but you know what?  I thought of writing this post a few weeks ago and then figured I would be refuted by an explosion of the death total over the next few weeks.  So far it hasn’t happened.  It may yet.

3. Prisoners are younger.  Here is data on inmate ages, they are not that much younger than the general U.S. population.  But they are somewhat younger, and surely this is one factor.

4. Prisoners smoke a lot, and nicotine actually may have protective properties against Covid-19.  And is obesity low in prison?  I do not know.  Still, I don’t think of prisoners as a group in perfect physical health.

5. Prisoners are…um…locked up.  The superspreaders just aren’t that super, there are not many new entrants to the prison population, few tourists from Italy, and so on.  Not only do they live in cells, but the prison system as a whole is like thousands of scattered islands.

I see 1-5 all as possible significant options, with #4 as the weakest candidate.  What else might be playing a role here?

A critique of contact-tracing apps

Here are some relevant criticisms from Soltani, Calo, and Bergstrom:

Studies suggest that people have on average about a dozen close contacts a day—incidents involving direct touch or a one-on-one conversation—yet even in the absence of social distancing measures the average infected person transmits to only 2 or 3 other people throughout the entire course of the disease. Fleeting interactions, such as crossing paths in the grocery store, will be substantially more common and substantially less likely to cause transmission. If the apps flag these lower-risk encounters as well, they will cast a wide net when reporting exposure. If they do not, they will miss a substantive fraction of transmission events. Because most exposures flagged by the apps will not lead to infection, many users will be instructed to self-quarantine even when they have not been infected. A person may put up with this once or twice, but after a few false alarms and the ensuing inconvenience of protracted self-isolation, we expect many will start to disregard the warnings.

And:

At least as problematic is the issue of false negatives—instances where these apps will fail to flag individuals as potentially at risk even when they’ve encountered someone with the virus. Smartphone penetration in the United States remains at about 81 percent—meaning that even if we had 100 percent installation of these apps (which is extremely unlikely without mandatory policies in place), we would still only see a fraction of the total exposure events (65 percent according to Metcalf’s Law). Furthermore, people don’t always have their phones on them.

And:

There is also a very real danger that these voluntary surveillance technologies will effectively become compulsory for any public and social engagement. Employers, retailers, or even policymakers can require that consumers display the results of their app before they are permitted to enter a grocery store, return back to work, or use public services—is as slowly becoming the norm in China, Hong Kong, and even being explored for visitors to Hawaii.

 

Taken with the false positive and “griefing” (intentionally crying wolf) issues outlined above, there is a real risk that these mobile-based apps can turn unaffected individuals into social pariahs, restricted from accessing public and private spaces or participating in social and economic activities. The likelihood that this will have a disparate impact on those already hardest hit by the pandemic is also high. Individuals living in densely populated neighborhoods and apartment buildings—characteristics that are also correlated to non-white and lower income communities—are likelier to experience incidences of false positives due their close proximity to one another.

In another study:

Nearly 3 in 5 Americans say they are either unable or unwilling to use the infection-alert system under development by Google and Apple, suggesting that it will be difficult to persuade enough people to use the app to make it effective against the coronavirus pandemic, a Washington PostUniversity of Maryland poll finds.

And here are skeptical remarks from Bruce Schneier.

I also have worried about how testing and liability law would interact.  If the positive cases test as positive, it may be harder for businesses and schools to reopen, because they did not “do enough” to keep the positive cases out, or perhaps the businesses and the schools are the ones doing the testing in the first place.  Whereas under a lower-testing “creative ambiguity” equilibrium, perhaps it is easier to think in terms of statistical rather than known lives lost, and to proceed with some generally beneficial activities, even though of course some positive cases will be walking through the doors.

I wonder if there also is a negative economic effect, over the longer haul, simply by making fear of the virus more focal in people’s minds.  The plus of course is simply that contact tracing does in fact slow down the spread of the virus and allows resources to be allocated to individuals and areas of greatest need.

Rapid progress from Fast Grants

I was pleased to read this NYT reporting:

Yet another team has been trying to find drugs that work against coronavirus — and also to learn why they work.

The team, led by Nevan Krogan at the University of California, San Francisco, has focused on how the new coronavirus takes over our cells at the molecular level.

The researchers determined that the virus manipulates our cells by locking onto at least 332 of our own proteins. By manipulating those proteins, the virus gets our cells to make new viruses.

Dr. Krogan’s team found 69 drugs that target the same proteins in our cells the virus does. They published the list in a preprint last month, suggesting that some might prove effective against Covid-19…

It turned out that most of the 69 candidates did fail. But both in Paris and New York [where the drugs were shipped for testing], the researchers found that nine drugs drove the virus down.

“The things we’re finding are 10 to a hundred times more potent than remdesivir,” Dr. Krogan said. He and his colleagues published their findings Thursday in the journal Nature.

The Krogan team was an early recipient of Fast Grants, and you will find more detail about their work at the above NYT link.  Fast Grants is also supporting Patrick Hsu and his team at UC Berkeley:

And the work of the Addgene team:

When will discrimination against superspreaders arrive?

Garett Jones emails me:

How soon until superspreader discrimination studies becomes an academic field? Is it already, on a Straussian level?

Will employment discrimination law react quickly or slowly?

IIRC after 9/11 it took about a year for the left to start bringing up serious concerns about detainee treatment.

Perhaps social media and the naturally greater sympathy people may have toward probabilistic superspreaders will encourage a faster response to the injustice of treating people differently on the basis of personal E(R0 | Covid +).

This will shape the medium-term spread of Covid if it hasn’t already.

Nursing homes across nations

This is all from Michael A. Alcorn, from my email, no further indentation offered:

“Just to keep hammering on this nursing home point… I saw your Tweet about Eastern vs. Western Europe and decided to explore the nursing home angle there too. The WHO has data on the number of nursing and elderly home beds for different countries here. Unfortunately, the data only goes up to 2013-ish for many countries, but it’s suggestive nonetheless.

Italy and France were clearly trending up seven years ago in its number of beds… would be interesting to see if Italy had a similar jump to Spain at some point. The number of beds gives us a proxy for the number of people who are highly vulnerable to COVID-19. Obviously, these countries have different total populations, but I don’t think that should matter too much because I suspect nursing homes tend to be highly concentrated within countries (e.g., how many of France’s nursing homes are in the Paris metro?). Based on what I’ve read about nursing home staff often being low paid and so perhaps coming to work when sick and working at multiple facilities, I suspect nursing home density is nonlinearly related to the number of COVID-19 deaths in a country (especially when you account for some of the truly horrifying government decisions regarding nursing homes).

Here are those Nordic countries everyone likes to compare:

You can get exact numbers on the website, but Sweden had twice as many nursing home beds as Finland and three times as many as Norway. The ship might have sailed on what we can do to protect these vulnerable populations, but I would love to see a Fast Grant go towards investigating the COVID-19/nursing home tragedy.”

USA non-existing facts of the day

Want to know how many tuberculosis cases there were in the U.S. last year? Ask the CDC. Want to know about health-care-associated infections? Ask the CDC. It knows.

But ask how many Covid-19 tests have been done, and the CDC’s doesn’t have an answer. Want a daily update on how many people are getting hospitalized for Covid-19? The CDC isn’t tracking it. Want to know if social distancing is making a difference? The CDC doesn’t know.

During this pandemic, when accurate, timely, nationwide information is the lifeblood of our response, the CDC has largely disappeared.

The performance of the world’s leading public health agency has been surprising, and by that I mean surprisingly disappointing. When the outbreak began, the CDC decided to forgo using the World Health Organization’s testing kit for Covid-19 and build its own. The test it shipped out to states was faulty, creating problems that stretched for weeks and slowed response as states waited for replacement tests.

Here is more from Ashish K. Jha.  As I’ve said before, our regulatory state has been failing us.

Washington Post covers Fast Grants

Here is the opening:

Economist Tyler Cowen first sounded the alarm that America is unprepared for a pandemic in 2005, when he wrote a paper outlining ways the country should respond and, for a few years, ran a blog focused on the possibility of an avian flu outbreak.

Fifteen years later, as a novel coronavirus brings Cowen’s fears into reality, the George Mason University professor is trying to fix what he and others view as a structural problem impeding the scientific response to the crisis: the months-long application and review process scientists must endure to get their research funded.

Here is the full story by Will Hobson.  Recommended.

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.