Category: Medicine

HHS turned down a big opportunity to make a lot of masks early

Another HHS official, also speaking on the condition of anonymity, said: “There is a process for putting out contracts. It wasn’t as fast as anyone wanted it to be.”

The masks still are not being made, and this would be in Texas.  I’ll say it yet again: our regulatory state is failing us in this matter.  Here is a bit more:

From his end, Bowen [the mask maker] said his proposal seemed to be going nowhere. “No one at HHS ever did get back to me in a substantive way,” Bowen said.

The senior U.S. official said Bowen’s idea was considered, but funding could not easily be obtained without diverting it from other projects.

While we are on the topic of diverting funding, surely we would all agree that the NSF funding for the social sciences all should — for at least two years — be diverted to biomedical research?  I wonder how many economists are willing to tweet that policy recommendation.

The Risk of Immunity Passes

I argued earlier that if we have Immunity Passes they Must Be Combined With Variolation because “the demand to go back to work may be so strong that some people will want to become deliberately infected. If not done carefully, however, these people will be a threat to others, especially in their asymptomatic phase.” Thus, if we have immunity passes we must also have controlled infection.

In a new paper, Daniel Hemel and Anup Malani run the numbers and verify the intuition:

…Our topline result is that strategic self-infection would be privately rational for younger adults under a wide range of plausible parameters. This result raises two significant concerns. First, in the process of infecting themselves, younger adults may expose others—including older and/or immunocompromised individuals—to SARS-CoV-2, generating significant negative externalities. Second, even if younger adults can self-infect without exposing others to risk, large numbers of self-infections over a short timeframe after introduction of the immunity passport regime may impose significant congestion externalities on health care infrastructure. We then evaluate several interventions that could mitigate moral hazard under an immunity passport regime, including the extension of unemployment benefits, staggered implementation of passports, and controlled exposure of individuals who seek to self-infect. Our results underscore the importance of careful planning around moral hazard as part of any widescale immunity passport regime.

Did we lockdown some parts of America too early?

No, I am not referring to the preventive measures taken in California, Washington state, and parts of the Tri-state area.  Those made good sense to me at the time and in retrospect all the more.

I mean when the whole country started to shut down, including the South, Midwest, and other parts of the West.  And yes I know the legal lockdowns were not always the biggest factors, arguably it was when governments started scaring people.

Let’s say you have a simple model of political sustainability where Americans will tolerate [???] months of lockdown — shall we say two? — but not much more. (Maybe three months if we had Merkel as president.)  Then, if you scare/lock down in parts of the country where the virus is not yet evident, you create economic misery but not many public health gains.  Who after all thinks that Seattle should have been locked down last September?  Right?

Many parts of America now hate the lockdown, as they see the economic devastation, are not witnessing overloaded hospital systems, and just don’t quite “get it.”  And they are now taking off the lockdown, through both legal and informal means, before it is optimal to do so.  One loyal MR reader emailed me this:

The smaller town I am in was never hit hard, and therefore most people are somewhere on the spectrum between COVID is a bad flu and you should wash your hands to pick whatever conspiracy theory (plandemic).  People do not believe in the severity of the virus.  Not one family we know is social distancing. The ICU never got overrun, the only apocalypse to arrive is an economic one.  This is the fundamental point.  Most people’s only pain and sadness stems from loss of job, security, future NOT from sickness and death.  People here don’t work for big companies or the government.

Oddly, Trump’s big speech when he found “pandemic religion” may have been one of his biggest mistakes.  I fully understand that Denmark and Austria did well because they locked down early (and took other measures).  There is good evidence that NYC should have locked down earlier yet, but maybe (and I do mean maybe) other parts of the country — most of all rural America — should have locked down later, so they would have their lockdown active “when it really matters.”

In the meantime, we could have restricted or somehow taxed travel out of NYC, which seems to have been a major national spreader.

This is one reason why I am skeptical about models of epidemiology (and economics!) that do not consider political sustainability.  I am by no means sure that the claims in this post are correct, but they could be correct.  And a model that does not consider political sustainability and time consistency won’t even pick up these factors as concerns.  It will simply indicate that a lockdown should happen as quickly as possible.  But that was perhaps one of our big mistakes, namely to shut down many of the less dense parts of America before their problems were sufficiently acute, thereby rendering the whole program less sustainable.

And moralizing and blaming our current predicament on “Trump,” or “the yahoos who watch Fox News” is — even if correct — washing one’s hands of the responsibility to incorporate political sustainability into the model.

I fully admit, by the way, that I did not myself appreciate the import of this factor at the time.  This is all a sign of how backward our science is in this entire area.

By the way, here is a 55 pp. Powerpoint-like survey of lockdown models.  Many references, not much public choice or political economy to be seen.

Limiting liability for a resumption of business activity

I have a short Mercatus policy brief on that topic, co-authored with Trace Mitchell.  Excerpt:

Risk from reopening cannot fall to zero, but investments in safety by employers can bring real gains in many cases. Ideally, a plan should both minimize risk and encourage employers’ safety investments. In essence, policymakers should (1) limit liability in the short term to cases of recklessness, (2) use direct regulation to prohibit some obviously risky options, and (3) create and fund a COVID-19 compensation program while capping liability for covered entities.

To understand how this combination of options might work in practice, consider the simple example of the restaurant. Many states are allowing partial reopenings of restaurants, albeit with social distancing, which might comprise outdoor seating, limited seating within the restaurant, or both. Yet some practices that would be very dangerous in the current situation, such as open buffets, have been made illegal per se. This arrangement takes some of the highest-risk problems off the table, and for the better. It is also appropriate for regulation to mandate soap-and-water washing facilities for workers in all restaurants, to provide another example of a sensible regulation.

It is still necessary, however, for these businesses to have stronger liability protection, so that restaurants may proceed with greater certainty, and also solvency. While the number of future COVID-19 transmissions in restaurants is unlikely to be zero, restaurants can only do so much to limit risk, vulnerable individuals still can opt to stay away and indeed are likely to do so, and tracing particular cases to particular restaurants is very difficult. For all of those reasons, we do not expect the traditional liability system to perform well in the case of restaurants, and we wish to limit its applicability, while of course keeping other safeguards in place. In essence, our proposal takes that commonsense approach to restaurants and applies it to the economy more broadly.

I would stress that nursing homes require a fully separate treatment.  Here is a related Marc Thiessen piece.  Here is Ross Marchand on state-level experimentation with liability.

Testing participation vs. testing capacity

This paper argues that testing participation –and not testing capacity–is the biggest obstacle to a successful “test and isolate”-strategy, as recently proposed by Paul Romer. If 𝑅0=2.5,at least 60percentof a population needs to participate in a testing program to make it theoretically possible to achieve an effective reproduction rate for the whole population,𝑅′′, below 1. I also argue that Paul Romer’s assumption about quarantine length is problematic,because it implicitly assumes that an infected and tested person is quarantined during the entire duration of the illness. With more realistic assumptions, where the fraction of the illness duration that is spent in quarantine depends on the test frequency, at least 80percentof the population must participate to keep 𝑅0′′<1, even if participants in the test program are tested every five days.Comprehensive testing,as proposed by Romer,is probably still a very cost-effective means of reducing the reproduction rate of the infection compared to mandatory lockdown policies, but it seems less promising than he suggests.How-ever, comprehensive testing might also reduce voluntary social distancing in a non-cost-effective way because testing and isolating infected individuals decreases the risk of infection for an individual if social distancing is not practiced.

Here is the full paper by Jonas Herby.

Should South Africa lock down?

The lockdown will lead to 29 times more lives lost than the harm it seeks to prevent from Covid-19 in SA, according to a conservative estimate contained in a new model developed by local actuaries.

The model, which will be made public today for debate, was developed by a consortium calling itself Panda (Pandemic ~ Data Analysis), which includes four actuaries, an economist and a doctor, while the work was checked by lawyers and mathematicians. The process was led by two fellows at the Actuarial Society of SA, Peter Castleden and Nick Hudson.

They have sent a letter, explaining its model, to President Cyril Ramaphosa. In the letter, headed “Lockdown is a humanitarian disaster to dwarf Covid-19”, they call for an end to the lockdown, a focus on isolating the elderly and allowing children to go back to school, while ensuring the economy restarts so that lives can be saved.

The paper also is at the link, and it is perhaps more of a rough and ready calculation than a formal model per se.  Nonetheless South Africa has a relatively young population and the core points are well taken:

In SA, they estimate that 5.4 years of life have been lost per Covid-19 death. They then multiply this by the range of deaths which they predict – 20,000 – as well as the actuarial society’s prediction of 88,000 fatalities. They factor in that the lockdown will have reduced some deaths, but not all. In the end, their model translated into a minimum of 26,800 “years of lives lost” due to Covid-19, and a maximum of 473,500 years. (This, critically, shouldn’t be confused with the actual number of fatalities expected from Covid-19.)

The actuaries then used the figures predicted by the National Treasury to model the impact on poverty. On Friday, the Treasury estimated that between 3-million and 7-million jobs will be lost due to the measures taken to combat the virus. The actuaries then work out that, conservatively, 10% of South Africans will become poorer, and as a result, will lose a few months of their lives.

It is a good question how many of the models used for the West have taken into account the “demonstration effect,” namely that poorer (and much younger) countries will be tempted to follow the same policies.  I’ve yet to see a good discussion of this.

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.