Search Results for: variolation

Peter Doherty on Variolation

Two noteworthy media mentions of variolation:

1. The New Yorker features Douglas Perednia talking about controlled infection and variolation, as its Exhibit A on on why conservative media shouldn’t presume to write on health/medicine, as they will only say stupid obviously terrible things:

After the Federalist tweeted it out, Twitter, which has been cracking down on coronavirus misinformation, temporarily locked the Federalist’s account. … He’d submitted it to a number of medical journals and blogs. “They all turned it down with no comment,” … tried the Federalist, almost at random. … The site accepted his article the next day, no questions asked. …

On the site … most commenters found Perednia’s idea absurd, dangerous, hilarious, or all three. … many angry e-mails and calls … Andrew Lover, an assistant professor of epidemiology at the University of Massachusetts-Amherst, told the Times that Perednia’s article was “exceedingly ill-advised and not evidence-based in any way shape or form.” …

Perednia [said] the way to adapt his idea to this reality was to make sure that the infecting was done with ‘the lowest possible dose’ … a concept known as variolation—which, he thought, would cut the death rate among those who chose to take part. (more)

2. A month ago, Adam Ford interviewed me on voluntary infection. Yesterday, Ford posted his interview with Nobel laureate Peter Doherty, author of Pandemics (2012), wherein Ford asked Doherty about variolation. Here are selected quotes from that discussion (fuller quotes below the fold):

47:10 Ford: “Controversially, in leu of actual vaccine that could come, hopefully in 9 months, but maybe even in 18 months if things go okay, if social isolation doesn’t work well enough too, would something like strategic or voluntary small dose low dose infection, like variolation, work in order to gain immunity, or nudge herd immunity? Is that something that we should be considering?

Doherty: (laughing) “Well let’s tell people what variolation was. … What they did was do this in young children, young children had a good immune response, generally survived smallpox, so what they were doing essentially is giving them smallpox, and they survived, whereas if they got it when they were older, they’d have a much worse disease. … So its not an unthinkable thing. …

52:40 With Covid19 I don’t know, but it would take a brave soul to be a test candidate, With younger people who are not severely affected, it’s possible. But you’d have to be enormously careful that they didn’t get any dose through their nose. But there would be ways of doing this. …

53:40 Ford: Is this something that could be achieved in the near term, if the vaccine timeline ends up looking like its going to be longer?

Doherty: If it was an absolutely catastrophic situation, if it was like the situation that is depicted in Contagion, where everyone who is within 100 feet of the virus gets it and dies, yes it could be reasonable. But I think for a virus where 80+% of people are definitely mildly infected at worse, or not sick enough to go into hospital, I don’t think you would take risk of that. The thing about a vaccine is that you have to give it to large numbers of normal people. You can’t take risks with vaccines.

You can take risks with end stage therapy. If someone is very very sick, and you’ve got something you think might work, you can try it pretty easily. People will approve that, … But you can’t take risks with vaccines. And the magnitude of the severity of this threat is not great enough to do that. You could say, … we’ll take a vaccine that looks a bit risky, maybe, and we’ll give it to the elderly. These are the people who are at risk, they can try it. … People like me, say would volunteer, I certainly would. I’d give it a go, and see if that works. But I wouldn’t want to be giving a vaccine that had any risk at all to younger people. You know, these are all theoretical arguments. But there is no way anything is ever given to anybody in this sense without going through extremely thorough review processes. … I think it is pretty unlikely.

So Doherty accepts “variolation” as a term that applies outside the context of smallpox. He thinks it could work, but oddly seems to see the main concept as infecting the young, rather than controlling dose, delivery vector, or strain. And he sees it only as justified in extreme circumstances, which Covid19 will never be, as it isn’t deadly enough. Even if the Great Suppression crashes the economy worse than the Great Depression, and even if millions will likely die from accidental infections, in his eyes and those of regulators that’s no excuse for letting healthy people voluntarily take substantial personal risks. Continue reading "Peter Doherty on Variolation" »

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Variolation Test Design

Okay, what the variolation concept needs most now is a trial/test/experiment ASAP. So to help get the ball rolling, let me sketch a tentative plan. I’m NOT saying this plan is now good enough. I’m saying let’s talk together about how to make it better. (Not so interested here in those ever popular “this can never work” comments.)

As with most projects, the obvious first top issue is staffing, especially leaders. This needs leaders who not only have the ability and expertise to execute it, but who can also inspire confidence in its other staff, subjects, patrons, sponsors, and audiences. (The most I’ve ever led is an assistant, so alas I don’t seem a good candidate.) The main point here is to inspire audiences to action, and that won’t happen if audiences don’t believe the project’s purported results, nor if they find its people too odious to associate with.

So the main purpose of this post is to try to attract participants, especially leaders, to pick up this ball and run with it. I’ll run with you, but I can’t run it by myself. When someone makes a good suggestion, such as in the comments, I’m likely to edit this post to include it. You are warned. Continue reading "Variolation Test Design" »

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Reply to Cowen On Variolation

In the last nine days I’ve done two online debates on variolation, with Zvi Mowshowitz and Gregory Cochran. In both cases my debate partners seemed to basically agree with me; disagreements were minor. Last night Tyler Cowen posted 1000+ words on “Why I do not favor variolation for Covid-19”. Yet oddly he also doesn’t seem to disagree with my main claims that (1) we are likely to need a Plan B for all-too-likely scenario where most of the world seems likely to get infected soon, and (2) variolation is simple, mechanically feasible, and could cut Covid19 Deaths by a factor of 3-30.

Tyler lists 8 points, but really makes 11. If he had one strong argument, he’d have focused on that, and then so could I in my response. Alas, this way I can’t respond except at a similar length; you are warned. Continue reading "Reply to Cowen On Variolation" »

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Variolation (+ Isolation) May Cut Covid19 Deaths 3-30X

(Here I try to put my recent arguments together into an integrated essay, suitable for recommending to others.)

When facing a new pandemic, the biggest win is to end it fast, so that few ever suffer. This prize makes it well worth trying hard to trace, test, and isolate those near the first few cases. Alas, for Covid-19 and the world, this has mostly failed, though not yet everywhere.

The next biggest win is to find a cheap effective treatment, such as a vaccine. And while hope remains for an early win, this looks to be years away. To keep most from getting infected, at this point the West must apparently develop and long maintain unprecedented expansions in border controls, testing, tracing, and privacy invasions, and perhaps also non-home isolation of suspected cases. Alas, these ambitious plans must be implemented by the same governments that have so far failed us badly.

Yes, there remains hope here, which should be pursued. But we also need a Plan B; what if most will eventually be infected without a treatment? The usual answer is “flatten the curve,” via more social distance to lower the average of (and increase the variance of) infection rates, so that more can access limited medical resources. Such as ventilators, which cut deaths by <¼, since >~¾ of patients on them die.

However, extreme “lockdowns”, which isolate most everyone at home, not only limit freedoms and strangle the economy, they also greatly increase death rates. This is because infections at home via close contacts tend to come with higher initial virus doses, in contrast to the smaller doses you might get from, say, a public door handle. As soon as your body notices an infection, it immediately tries to grow a response, while the virus tries to grow itself. From then on, it is a race to see which can grow biggest fastest. And the virus gets a big advantage in this race if its initial dose of infecting virus is larger.

This isn’t just a theory. The medical literature consistently finds strong relations, in both animals and humans, between initial virus dose and symptom severity, including death. The most directly relevant data is on SARS and measles, where natural differences in doses were associated with factors of 3 and 14 in death rates, and in smallpox, where in the 1700s low “variolation” doses given on purpose cut death rates by a factor of 10 to 30. For example, variolation saved George Washington’s troops at Valley Forge.

Early on, it can be worth paying such high costs to end a pandemic. But once a pandemic seems likely to eventually infect most everyone, it becomes less clear whether lockdowns are a net win. However, the dose effect that lockdowns exacerbate, by increasing dose size, also offers a huge opportunity to slash deaths, via voluntary infection with very low doses. (As others have been also been suggesting.) Continue reading "Variolation (+ Isolation) May Cut Covid19 Deaths 3-30X" »

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We Are Over-Preventing Covid

In the Oct. 12 JAMA, David Cutler and Lawrence Summers estimate the total costs that the U.S. will suffer from the covid pandemic. Here is their key table:

So their numbers imply that we will lose $6.95T due to covid harms (deaths and impairments), and $9.17T from efforts to prevent those harms (lost income and mental impairment). Note that Cutler and Summers didn’t divide these costs into prevention versus harm prevented; that’s my division. And note that while they included the main covid harms, they missed some big costs from prevention, such as children getting worse schooling, less socializing, and a general dislike of wearing masks.

If we just look at the costs that Cutler and Summers consider, we get a prevention to harm cost ratio of 1.32, which is optimal if on average 1.0% more prevention effort cuts health harms by about 1.3%. I don’t know if that’s right, but at least it doesn’t seem crazy.

However, those virus harm estimates come from assuming a $7M value for each of these lives lost, and that I say does seem crazy. (They also assume 625K total virus deaths, 2 people impaired by 35% per death, and $7.6T income lost over the next ten years.)

As I’ve discussed before, it makes much more sense to value life-years lost, relative to income. And as we’ve so far seen 9.2 life-years lost on average per covid death (in U.S. through July 11), this $7M value estimate translates to a life-year lost being worth 12.1 years of income. And that’s crazy high.

For such crazy high estimates, we have no one to thank more than Kip Viscusi. He arguably started the literature estimating the value of life, and he’s been a big influence on it ever since, via co-authoring a huge number of papers (a big % of papers he cites in his review articles are by him), and editing a major journal that publishes stuff on the topic (J. of Risk & Uncertainty). And Viscusi is proud to present himself as a crusader for higher life-value estimates:

The watershed event that led to the adoption of the [Value of Statistical Life] was the 1982 conflict between the US Department of Labor and the Office of Management and Budget (OMB) over the proposed hazard communication regulation. The agency had valued the reduced mortality risks by the ‘cost of death’, leading to relatively modest benefit values. In its review of the regulatory proposal, the OMB concluded that the proposed regulation failed the required test that benefits must exceed costs. The Department of Labor appealed the decision to then Vice President George H.W. Bush, and I was asked to resolve the dispute. The only change I made to the OMB’s critique is that I introduced my VSL estimates into the agency’s analysis. Use of my VSL figure of US$7.4 million (in 2015 dollars) increased the estimated benefits of the regulation by a factor of 10. (more)

As I’ve noted before, since a lot of government regulation is justified as protecting citizen lives, those who seek to justify more regulation tend to seek higher value of life estimates. Just a year before, in 1981, Viscusi had just published an estimate that each U.S life was worth $17.9M in 1976$, implying a life-year lost was worth 20.3 years of income! That’s much higher than most of the estimates he’s published since, and his estimates tend to be higher than those of other authors. Also, Viscusi has long been skeptical of the idea of adjusting the value of life for the number of life years left – he says the value of life doesn’t depend on age.

A few months ago I went through five other papers, mostly lit reviews, on the value of life, and I translated the favored median estimate in each paper into a median life-year-to-income ratio:

  • A 2002 review of 33 job papers found 1.76.
  • A 2003 review of 30 road safety papers found 2.92.
  • A 2011 review of 850 stated preference estimates found 2.98.
  • A 2003 study of 76 US federal regulations (the ones Viscusi is proud to have influenced) found 3.34.
  • A 2003 Viscusi review found 4.53 re 30 US labor market papers, 5.94 re 22 non-US labor market papers, and 1.88 re 11 U.S. housing and product market papers.

Setting aside the estimates Viscusi influenced, I’m comfortable with accepting an estimate of 3.0. But if we apply that to the covid estimates Culter and Summers used, we’d get only $1.08T and $0.64T for covid death and impairment harms, which gives a prevention to harm cost ratio of 5.31. (Which is close to the 5.2 median estimate from my most recent poll.)

And its crazy to think that on average we are getting a 5.31% cut in covid harm for each 1% increase in prevention cost we pay! But that’s what it would take to justify this level of prevention spending relative to harms prevented. In fact, in most recent poll, the median estimate is that we’d instead get only a 0.10% cut in covid harm from 1% more prevention. Over a factor of 50 weaker than needed. And that’s why I say we are way over-preventing covid. (A scenario I warned against back in March.)

Note that I’m not blaming all this excess prevention on government; private choices clearly drive much of it. I’m talking about the U.S.; prevention elsewhere may have been more effective. I’m not saying all prevention efforts are equally effective. And I’m not weighing in here on exactly what are the best prevention strategies, nor on what is their maximum possible effectiveness. Sure, the best probably are far more effective than what we are and have been doing. But, alas, doing less than what we have been doing seems to me a far more politically feasible option than proposing to identify and switch to far better strategies. (Like maybe trying variolation or vouching.)

I’ve long said that we spend way too much on medicine, because the marginal value is far below our marginal costs.  (A topic on which Cutler and I sparred before.) Seems that sort of thing continues to hold in a pandemic. And governments, instead of correcting for this problem, mainly just make it worse.

Added 26Oct: Tyler says this sort of marginal analysis is irrelevant due to “non-linearities”. Doesn’t really say more than that. But most econ systems are not linear, yet that doesn’t stop econ elsewhere. He could say because of “non-convexities”, but this requires that either we are at a boundary or that there be big moves from the status quo that beat all small moves. Yet for that to be a relevant critique here, Tyler needs to be able to point to big changes that we should adopt soon, and likely will adopt soon. Absent that, critiques of small changes to the status quo remain quite relevant.

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The World Forager Elite

My last post was on Where’s My Flying Car?, which argues that changing US attitudes created a tsunami of reluctance and regulation that killed nuclear power, planes, and ate the future that could have been. This explanation, however, has a problem: if there are many dozens of nations, how can regulation in one nation kill a tech? Why would regulatory choices be so strongly correlated across nations? If nations compete, won’t one nation forgoing a tech advantage make others all the more eager to try it?

Now as nuclear power tech is close to nuclear weapon tech, maybe major powers exerted strong pressures re how others pursued nuclear power. Also, those techs are high and require large scales, limiting how many nations could feasibly do them differently.

But we also see high global correlation for many other kinds of regulation. For example, as Hazlett explains, the US started out with a reasonable property approach to spectrum, but then Hoover broke that on purpose, to create a problem he could solve via nationalization, thereby gaining political power that helped him become U.S. president. Pretty much all other nations then copied this bad US approach, instead of the better prior property approach, and kept doing so for many decades.

The world has mostly copied bad US approaches to over-regulating planes as well. We also see regulatory convergence in topics like human cloning; many had speculated that China would be defy the consensus elsewhere against it, but that turned out not to be true. Public prediction markets on interesting topics seems to be blocked by regulations almost everywhere, and insider trading laws are most everywhere an obstacle to internal corporate markets.

Back in February we saw a dramatic example of world regulatory coordination. Around the world public health authorities were talking about treating this virus like they had treated all the others in the last few decades. But then world elites talked a lot, and suddenly they all agreed that this virus must be treated differently, such as with lockdowns and masks. Most public health authorities quickly caved, and then most of the world adopted the same policies. Contrarian alternatives like variolation, challenge trials, and cheap fast lower-reliability tests have also been rejected everywhere; small experiments have not even been allowed.

One possible explanation for all this convergence is that regulators are just following what is obviously the best policy. But if you dig into the details you will quickly see that the usual policies are not at all obviously right. Often, they seem obviously wrong. And having all the regulatory bodies suddenly change at once, even when no new strong evidence appeared, seems especially telling.

It seems to me that we instead have a strong world culture of regulators, driven by a stronger world culture of elites. Elites all over the world talk, and then form a consensus, and then authorities everywhere are pressured into following that consensus. Regulators most everywhere are quite reluctant to deviate from what most other regulators are doing; they’ll be blamed far more for failures if they deviate. If elites talk some more, and change their consensus, then authorities must then change their polices. On topic X, the usual experts on X are part of that conversation, but often elites overrule them, or choose contrarians from among them, and insist on something other than what most X experts recommend.

This looks a lot like the ancient forager system of conflict resolution within bands. Forager bands would gossip about a problem, come to a consensus about what to do, and then everyone would just do that. Because each one would lose status if they didn’t. In this system, there were no formal rules, and on the surface everyone had an equal say, though in fact some people had a lot more prestige and thus a lot more influence.

This world system also looks new – I doubt this description applied as well to the world centuries or millennia ago, even within smaller regions. So this looks like another way in which our world has become more forager-like over the last few centuries, as we’ve felt more rich and safe. Big world wars probably cut into this feeling, so there was probably a big jump in the few decades after WWII, helping to explain the big change in attitudes ~1970.

Elites like to talk about this system as if it were “democratic”, so that any faction that opposes it “undermines democracy”. And it is true that this system isn’t run by a central command structure. But it is also far from egalitarian. It embodies a huge inequality of influence, even if individuals within it claim that they are mainly driven by trying to help the world, or “the little guy”.

This system seems a big obstacle for my hopes to create better policy institutions driven by expert understanding of institutions, and to get trials to test and develop such things. Because as soon as any policy choice seems important, such by triggering moral feelings, world elite culture feels free to gossip and then pressure authorities to adopt whatever solution their gossip prefers. Experts can only influence policy via their prestige. Very prestigious types of experts, such as in physics, can win, especially on topics about which world elites care little. But otherwise, elite gossip wins, whenever it bothers to generate an opinion.

That is, the global Overton window isn’t much wider than are local Overton windows, and often excludes a lot of valuable options.

Notice that in this kind of world, policy has varied far more across time than across space. Context and fashion change with time, and then elites sometimes change their minds. So perhaps my hopes for policy experiments must wait for the long run. Or for a fall of forager values, such as seems likely in an Age of Em. Alas neither I nor my allies have sufficient prestige to push elites to favor our proposals.

Added 11p: It seems to me that the actual degree of experimentation and variance in policy is far below optimum in this conformist sort of policy world. We are greatly failing to try out as many alternatives as fast as we should to find out what works best. And we are failing to listen enough to our best experts, and instead too often going with the opinions of well-educated but amateur world elites.

Added4p: As John Nye reminds me, in the early years of a new tech, only a few nations in the world may be able to pursue it. They then set the initial standards of regulation. Later, more nations may be able to participate, but risk-averse regulators may feel shy about defying widely adopted initial standards.

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Time to Mitigate, Not Contain

In a few hours, I debate “Covid-19: Contain or Mitigate?” with Tomas “Hammer & Dance” Pueyo, author of many popular pandemic posts (e.g. 1 2 3 4 5 6 7). Let me try to summarize my position.

We have long needed a Plan B for the scenario where a big fraction of everyone gets exposed to Covid19, and for this plan I’ve explored variolation and other forms of deliberate exposure. To be ready, variolation just needs a small (~100) short (1-2mo.) trial to verify the quite likely (>75%) case that it works (cuts harm by 3-30x), but alas, while funding and volunteers can be found, med ethics panels have consistently disapproved. (Months later, they haven’t even allowed the widely praised human challenge trials for vaccines, some of which would include variolation trials.)

One big reason we aren’t preparing enough for Plan B is that many of us are mentally stuck in a Plan A “monkey trap.” Like a monkey who gets caught because it won’t let go of a tasty nut held in its fist within a gourd, we are so focused on containing this pandemic that we won’t explore options premised on failing to contain.

Containment seeks to keep infections permanently low, via keeping most from being exposed, for at least several years until a strong lasting vaccine is widely applied. Mitigation, in contrast, accepts that most will be exposed, and seeks only to limit the rate or exposure to keep medical systems from being overwhelmed, and to maintain enough critical workers in key roles.

Succeeding at containment is of course a much bigger win, which is why containment is the usual focus early in a pandemic. Catch it fast enough, and hit it hard enough with testing, tracing, and isolation, and the world is saved. But eventually, if you fail at that Plan A, and it grows big enough across across a wide enough area, you may need to admit failure and switch to a Plan B.

And, alas, that’s where we seem to be now with Covid-19. Over the last 7 weeks since the cases peak the official worldwide case count has been rising slowly, while official deaths are down ~25%. In the US, deaths are down ~1/2 since he peak 6 weeks ago. You might think, “yay, declines, we are winning!” But no, these declines are just too slow, as well as too uncertain.

Most of the US decline has been in New York, which has just now reached bottom, with no more room to decline. And even if US could maintain the rate of declining by 1/3 every 6 weeks, and repeat that 5 times over 30 weeks (= 7 months), not at all a sure thing, that would only bring daily US cases from 31K at the peak down to 4.2K. Which isn’t clearly low enough for test and trace to keep it under control without lockdown. And, more important, we just can’t afford to lockdown for that long.

You see, lockdown is very expensive. On average, around the world, lockdowns seems to cost about one third of local average income. Yet I estimate the cost of failing to contain, and letting half the population get infected with Covid-19 (at IFR ~0.5%), to be about 3 weeks of income. (Each death loses ~8 QALY.) So 9 weeks of strong lockdown produces about the same total harm as failing to contain! And where I live, we have almost had 10 weeks of lockdown.

If without lockdown the death rate would double due to an overloaded medical system, then paying for less than 9 weeks of added lockdown to prevent that is a good deal. But at that point, paying more than an additional 9 weeks of strong lockdown to prevent all deaths would not be a good deal. So our willingness to pay for lockdowns to cut deaths should really be quite limited. Sure, if we were at a tipping point where spending just a bit more would make all the difference between success and failure, then sure we should spend that bit more. But that’s just not plausibly where we are now.

Yes, sometimes we pay more to prevent harm than we suffer on average from such harms. For example, we pay more for door locks, and security guards, than we lose on average from theft. But those are very effective ways to prevent harm; paying 10% more there cuts harms by much more than 10%. Yet according to my Twitters polls, most see 10% more spent on lockdown as producing much less than 10% fewer deaths. If so, we should spend much less on lockdowns than we suffer from pandemic deaths.

Now if Pueyo is reading this, I suspect he’s screaming “But we’ve been doing it all wrong! Other possible policies exist that are far more effective, and if we use them containment becomes cost-effective. See Taiwan or South Korea.” And yes, other places have achieved better outcomes via better policies. We might not be able to do as well as them now that we’ve lost so much time, but we might well do much better than currently. Pueyo has sketched out plans, and they even seem to be good sketches.

So if we suddenly made Tomas Pueyo into a policy czar tomorrow, with an unlimited budget and able to run roughshod across most related laws or policies, we’d probably get much better Covid-19 outcomes, perhaps even cost-effective containment. But once such a precedent was set, I’d fear for the effectiveness of future czars. Ambitious politicians and rent-seekers would seek to manufacture crises and pseudo-Pueyo-czar candidates, all to get access to those unlimited budgets and legal powers.

Which is a big part of why we have the political systems we do. All around the world, we have created public health agencies tasked with pandemic policy, and political systems that oversee them. These agencies are staffed with experts trained in various schools of thought, who consult with academic experts of varying degrees of prestige. And all are constrained by local legal precedent, and by public perceptions, distrust, and axes of political conflict. These are the people and systems that have produced the varying policies we have now, all around the world.

Yes, those of us in places which have seen worse outcomes should ask ourselves how strong a critique that fact offers of our existing institutions and political cultures, and what we might do to reform them. But there is no easy and fast answer there; good reforms will have to be carefully considered, tested, and debated. We can hope to eventually improve via reforms, but, and this is the key point, we have no good reason to expect much better pandemic policy in the near future than we have seen in the near past. Even when policy makers have access to well-considered policy analyses by folks like Pueyo.

Now it might be possible to get faster political action if Pueyo and many other elites would coordinate and publicly back one specific standard plan, say the “John Hopkins Plan”, that specifies many details on how to do testing, tracing, isolation, etc. Especially if this plan pretty directly copied a particular successful policy package from, say, Taiwan. If enough people yelled in unison “We must do this or millions will die!”, why then politicians might well cave and make it happen.

But that is just not what is happening. Instead, we have dozens of essays and white papers pushing for dozens of related but different proposals. So there’s no clear political threat for politicians to fear defying. Whatever they do, come re-election time politicians can point to some who pushed for some of what they did. So all these divergent essays have mainly limited short term political effects, though they may do much more to raise the status of their authors.

So if political complexity argues against containment now in many places, why doesn’t that same argument apply equally well to mitigation? After all, mitigation can also be done well or badly, and it must be overseen by the same agencies and politicians that would oversee containment. As there is no escaping the fact that many detailed policy choices must be made, why not push for the best detailed packages of choices that we know?

Imagine that you were driving from A to B, and your first instinct was to take a simple route via two interstate freeways, both in big valleys. Your friend instead suggests that you take a backroad mountain short cut, using eight different road segments, many of them with only one lane, and some very wiggly. (Assume no phone or GPS.) That plan might look like it would take less total time, but you should worry about your competence to follow it. If you are very tired, bad at following road directions, or bad at sticking to wiggly roads, you might prefer to instead take the interstates. Especially if it was your tired 16 year old teen son who will do the driving.

Like the wiggly backroad short cut, containment is a more fragile plan, more sensitive to details; it has to be done more exactly right to work. To contain well, we need the right combination of the right rules about who can work and shop, and with what masks, gloves, and distance, tests going to the right people run by the right testing orgs, the right tracing done the right way by the right orgs with the right supporting apps, and the right rules requiring who gets isolated where upon what indications of possible infection. All run by the right sort of people using the right sort of local orgs and legal authority. And coordinated to right degree with neighboring jurisdictions, to avoid “peeing section of the pool” problems.

Yes, we might relax lockdown badly, but we are relaxing toward a known standard policy: no lockdown. So there are fewer ways to go wrong there. In contrast, there are just more ways to go wrong in trying to lockdown even more strictly. And that’s why it can make sense for the public to say to the government, “you guys haven’t been doing so well at containment, so let’s quit that and relax lockdown faster, shooting only for mitigation.” Yes, that might go badly, but it can’t go quite as badly as the worse possible scenario, where we trash the economy with long painful lockdowns, and yet still fail and most everyone gets exposed.

And that’s my argument for mitigation, relative to containment.

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The Plan A Winner’s Circle Alliance

Plan A is how to contain Covid19 until a vaccine or other strong treatment shows up. Plan B is how to deal with Plan A failing, and a substantial fraction (>20%) of the population getting infected.

While I’ve mostly focused on Plan B analysis, many nations and sub-regions seem to be doing okay so far at Plan A, keeping infections low and now declining in rate. It isn’t at all clear that they can maintain this until a vaccine arrives, but it is clear that they will keep trying for a while. And most other places have been shamed into giving lip service to Plan A. So much so that they may well induce much more damage from such efforts than they’d suffer from quitting and moving on to Plan B.

Soon the places that are doing well under Plan A will consider carefully relaxing their controls, while standing ready to reassert them should infections rise. And one of their key choices will be how much contact to have with other places. They will be much more willing to interact with places that also seem to be doing well at Plan A.

If X opens to Y who opens to Z, that makes X vulnerable to Z. Thus a winner’s circle of places doing well at Plan A will want to coordinate on who opens to who. They may want to share monitoring efforts re who is worthy to join their circle, and standards re how to grade their openings. And how to prevent hidden openings to the contagious centers that are failing at Plan A. And eventually, how if at all to open to places that fail so much as to achieve local “herd immunity”.

I’m not sure what names people will give to these two groups. Competent circle versus incompetent basket case centers? Clean versus unclean? High vs low state capacity? But whatever they are called, the US seems a likely candidate to stay in the bad group, with Europe a close second, and US rivals will eagerly push for a new international alignment that keeps them there.

US and European prestige will take a huge hit if this situation persists long. You might think this would shame us into reorganizing better to succeed, but apparently not. Yet we seem inclined to pay large costs to pursue plan A with our poor organization. So we risk the worst of both: trashing our economy far more than do they, and yet still ending up excluded from the winner’s circle.

Of course if success at Plan A is only temporary, and infections from the contagious centers infect most of the world before vaccines arrive, it will be the Plan B places who achieve herd immunity that will form the growing and relatively successful alliance. In that case, the Plan A alliance will shrink and suffer while they limit their connections to the Plan B group.

Note that places that achieve herd immunity have less need to coordinate on who they open to. And if these really organized into hostile alliances of nations, some may be willing to do the extreme things that nations have long done against competing alliances. The Plan A alliance may accuse the Plan B group of trying to infect them on purpose, and in at least some cases, they may be right.

Added 2May: Here’s an article on a Plan A alliance.

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Vouch For Pandemic Passports

Car pollution is an externality. Via pollution, the behavior of some hurts others, an effect that injurers may not take into account unless encouraged to by norm, contract, liability, or regulation. However, as the pollution from one vehicle mixes with that from many others, liability is poorly suited to discourage this; it is too hard to identify which cars hurt you, and there are too many of them. It seems to work better use regulations regarding car design and maintenance to limit the pollution emitted per mile driven, and to tax those miles driven.

Assault is also an externality; you can hurt someone by punching them. But in contrast to pollution, regulation is poorly suited to assault. We could require everyone to wear boxing globes and headgear, and we might ban insults and alcohol consumption, or perhaps even all socializing. But such regulations would go too far in restricting useful behavior. It works better to just hold liable those who punch others, via tort or criminal law. Yes, to discourage assault in this way, we must hold (or at least threaten to hold) expensive trials for each assault. But that still seems far cheaper than regulatory solutions.

These two examples illustrate a well-known tradeoff in choosing between (strict) liability and regulation. On the one hand, making people pay damages when they hurt others encourages them to take such harms into account, while also letting their behavior flexibly adapt to other context. On the other hand, regulation lets us avoid expensive court trials that require victims to prove who hurt who when where and how much. Though regulation induces more uniform behavior that is less well adapted to circumstances, it works acceptably well in many cases, like auto pollution, even if less well in others, like assault. (The mixed solution of negligence liability is discussed below.)

In our current pandemic, the main externality is infection, whereby one person exposes another to the virus. Conventional public health wisdom says to discourage infection via regulation: tell everyone when to get tested and isolated, and make them tell you who they met when and where. Tell them who can leave home when and for what reasons, and what they must wear out there. However, as we are all now experiencing first hand, not only are such changes to our usual behaviors quite expensive, such rules can also induce far from optimal behavior.

Recent pandemic rules have banned bike riding, but not cars or long walks. You can take only one exercise trip per day, but there’s no limit on how long. Members of a big home can all meet in their yard together, but members of two small adjacent homes may not meet in one of their yards. You can’t go meet distant friends, even if they only ever meet you. All parks are closed regardless of how densely people would be in there. The same rules were set in dense cities and in sparse rural areas. Alcohol store workers are deemed critical, even though alcohol can be mailed, but not auto repair, which cannot be mailed. Six feet is declared the safe distance, regardless of how long we stay near, if we wear masks, if we are outdoors, or which way the air is moving. Workplaces are closed regardless of the number of workers, how closely they interact, or how many other contacts each of them have. The same rules apply to all regardless of age or other illness. You may have to wear a mask, but it doesn’t have to be a good one.

Imagine that we instead used legal (strict) liability to make as many of us as possible expect to suffer personally and directly from infecting others, and to suffer more-so the worse their symptoms. In this scenario, such people would try to take all these factors and more into account in choosing their actions. For actions that risk infecting others, they would consider not only on how important such acts are to them, but also on how likely they are personally to be infected now, how vulnerable each other person they come near might be to suffering from an infection, how vigorously their activity moves the air near them, where such air currents are likely to go, how well different kinds of masks hinder infected air, and so on. If allowed, they might even choose variolation.

Of course, for the purpose of protecting ourselves from getting infected by others, we already have substantial incentives to attend to such factors. The problem is that simple regulations don’t give us good incentives to attend to these factors for the purpose of preventing us from infecting others. With regulations, we have incentives to follow the letter of the law, but not its spirit. So we don’t do enough in some ways, and yet do too much in others. But if liability could make us care about infecting others as well as ourselves, then it might simultaneously reduce both infections and the economic and social disruptions caused by lockdowns. With strong and clear enough liability incentives, we wouldn’t need regulations; we could just let people choose when and how to work, shop, travel, etc.

But is it feasible to use liability to discourage infections? Yes, if we can satisfy two conditions: (1) most people are actually able to pay for damages if they are successfully sued for infecting others, and (2) enough of those who infect others are actually and successfully sued, and so made to pay.

On the first condition, ensuring that people can pay damages if they are found guilty, it is sufficient to require people who mix with others to buy infection liability insurance, similar to how we now require car drivers to get accident liability insurance. That is, to get a “pandemic passport” to excuse you from a strong lockdown, you must get an insurance company to guarantee that you will pay damages if you are shown to have infected someone. In a sense they “vouch” for you, and so are your “voucher”. The more types of voucher-client contract terms we are willing to enforce, the more levers vouchers gain to reduce risks.

The premiums for such insurance will be low if you can convince a voucher that you have already recovered from the virus, and so are relatively immune, or that you will leave your lockdown only rarely, to safe destinations. Otherwise, a voucher may require you to install an app on your phone to track your movements, or they may spot check your claims that you have sufficient supply of good masks that you use reliably when you leave home.

Okay, but what about the second condition, that enough infectors are actually made to pay? For this we need enough data to be collected on both sides, the infector and the infected, so that one can frequently enough match the two, to conclude that this person likely infected that one at this location at this time.

Now, we don’t need to be always absolutely sure of who infected who. In ordinary civil trials, the standard is a “preponderance of the evidence”; courts need only be 51% or more sure to convict the defendant. And sometimes we add on extra “punitive” damages, up to four ties as large as basic damages, often to compensate for a lower chance of catching offenders. So if we can find evidence to convince a court at the 51% or better standard for only one fifth of offenders, but we can add four times punitive damages, then offenders who do not know if they will be caught still expect to on average to pay near the basic damage amount.

Okay, but we still need to collect enough info to see who infected who at least one fifth of the time. Is this feasible? Well it is clearly quite feasible early in a pandemic, when few have been infected. Early on, if the times and places, i.e., space-time path, consistent with you being infected then and there overlap with the space-time path when someone else was likely infectious, then it was most likely their fault. This is the “contact trace” process usually recommended by public health workers early in a pandemic.

The problem gets harder later in a pandemic, when your infected path may overlap with the infectious paths of many others. Here it might be possible to use info on which virus strain you and they had to narrow the field. But even so there may still be several consistent candidates. In this case it seems reasonable to divide the liability over all of them, perhaps in proportion to the size of the path overlap. For the purpose of creating incentives to avoid infecting others, it isn’t that important to know later who exactly infected who when.

But yes, we still need info on who was infected and infectious where and when, perhaps supplemented by data on who had what virus strains. How can we get this info? People who might get infected have incentives to collect info on their path, to help them sue if infected. But people who might infect others would seem to want to erase such info, to keep them from being sued. I’ve recently outlined a more general approach to induce the collection of info sufficiently likely to be useful in later lawsuits. But for this essay, I’ll just propose that collecting key info be another condition required to get a pandemic passport, with violations punished by fines also guaranteed by your voucher.

Let me also note that yes, legal liability doesn’t work to discourage harms if typical harms get so small that people wouldn’t bother to sue to recover damages. In this case we could use a random lottery approach to dramatically lower the average cost of suing.

So let’s put this all together. You must stay at home, locked down, unless you get a “pandemic passport”, in which case you can go where you want when, to meet anyone. To get such a passport, you must get someone to vouch for you. They guarantee that you will pay should someone successfully sue you for infecting them, if you agree to their terms of premiums, behavior, monitoring, punishment, and co-liability. Defendants who pay damages may have to pay extra, to compensate for most infectors not getting caught in this way. When several infector candidates are consistent with the data, they can divide the damages. And for low damage levels, a random lottery approach can lower court costs.

To get and keep a passport, your voucher also guarantees that you will collect info that can help others to show that you infected them, but which can also help you to sue others if they infect you, and win you bounties via showing that others did not collect required info. For example, perhaps you must track your movements in space and time, regularly record some symptoms like body temperature, and also save regular spit samples. This info is available to be subpoenaed by those who can show sufficient reason to suspect that you infected them. Such info seems sufficient to catch enough infectors.

And by catching a sufficient fraction of infectors who then actually pay on average for the harms that they cause by infecting, (strict) legal liability can give sufficient incentives to individuals to avoid infecting others. If so, we don’t need crude lockdown regulations telling people what to do when and how; individuals can instead more flexibly adapt to details of their context in deciding when and where to work, shop, travel etc. Yes, voucher rules would not let them do such things as freely as they would in the absence of a pandemic. But behavior would be more free and impose lower economic costs than under crude regulations which similarly suppress the pandemic spread.

Note that today the most common form of legal liability is actually negligence, which we can see as a mixed form between simple regulation and simple strict liability. With negligence, the court judges if your behavior has been consistent with good behavior standards, which are essentially behavior regulations. But you are only punished for violating these regulations in situations where your behavior contributed to the harm of a particular person. Today courts tend to limit strict liability to cases where courts find it hard to define or observe good behavior details, such as using explosives, keeping a pet tiger, or making complex product design choices. As courts find it harder to define and observe good behavior in a new pandemic, strict liability seems better suited to this case.

Note also that none of this requires employers to be liable for their infected employees. Someone who is sued for infecting others may turn around and blame their employer for pushing them into situations that cause them to infect others. Employer-employee contract could usefully address such issues.

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A Perfect Storm of Inflexibility

Most biological species specialize for particular ecological niches. But some species are generalists, “specializing” in doing acceptably well in a wider range of niches, and thus also in rapidly changing niches. Generalist species tend to be more successful at generating descendant species. Humans are such a generalist species, in part via our unusual intelligence.

Today, firms in rapidly changing environments focus more on generality and flexibility. For example, CEO Andy Grove focused on making Intel flexible:

In Only the Paranoid Survive, Grove reveals his strategy for measuring the nightmare moment every leader dreads–when massive change occurs and a company must, virtually overnight, adapt or fall by the wayside–in a new way.

A focus on flexibility is part of why tech firms tend more often to colonize other industries today, rather than vice versa.

War is an environment that especially rewards generality and flexibility. “No plan survives contact with the enemy,” they say. Militaries often lose by preparing too well for the last war, and not adapting flexibly enough to new context. We usually pay extra for military equipment that can function in a wider range of environments, and train soldiers for a wider range of scenarios than we train most workers.

Centralized control has many costs, but one of its benefits is that it promotes rapid thoughtful coordination. Which is why most wars are run from a center.

Familiar social institutions tend to be run by those who have run parts of them well recently. As a result, long periods of peace and stability tend to promote specialists, who have learned well how to win within a relatively narrow range of situations. And those people tend to change our rules and habits to suit themselves.

Thus rule and habit changes tend to improve performance for rulers and their allies within the usual situations, often at the expense of flexibility for a wider range of situations. As a result, long periods of peace and stability tend to produce fragility, making us more vulnerable to big sudden changes. This is in part why software rots, and why institutions rot as well. (Generality is also often just more expensive.)

Through most of the farming era, war was the main driver pushing generality and flexibility. Societies that became too specialized and fragile lost the next big war, and were replaced by more flexible competitors. Revolutions and pandemics also contributed.

As the West has been peaceful and stable for a long time now, alas we must expect that our institutions and culture have been becoming more fragile, and more vulnerable to big unexpected crises. Such as this current pandemic. And in fact the East, which has been adapting to a lot more changes over the last few decades, including similar pandemics, has been more flexible, and is doing better. Being more authoritarian and communitarian also helps, as it tends to help in war-like times.

In addition to these two considerations, longer peace/stability and more democracy, we have two more reasons to expect problems with inflexibility in this crisis. The first is that medical experts tend to think less generally. To put it bluntly, most are bad at abstraction. I first noticed this when I was a RWJF social science health policy scholar, and under an exchange program I went to the RWJF medical science health policy scholar conference.

Biomed scholars are amazing in managing enormous masses of details, and bringing up just the right examples for any one situation. But most find it hard to think about probabilities, cost-benefit tradeoffs, etc. In my standard talk on my book Age of Em, I show this graph of the main academic fields, highlighting the fields I’ve studied:

Academia is a ring of fields where all the abstract ones are on one side, far from the detail-oriented biomed fields on the other side. (I’m good at and love abstractions, but have have limited tolerance or ability for mastering masses of details.) So to the extent pandemic policy is driven by biomed academics, don’t expect it to be very flexible or abstractly reasoned. And my personal observation is that, of the people I’ve seen who have had insightful things to say recently about this pandemic, most are relatively flexible and abstract polymaths and generalists, not lost-in-the-weeds biomed experts.

The other reason to expect a problem with flexibility in responding to this pandemic is: many of the most interesting solutions seem blocked by ethics-driven medical regulations. As communities have strong needs to share ethical norms, and most people aren’t very good at abstraction, ethical norms tend to be expressed relatively concretely. Which makes it hard to change them when circumstances change rapidly. Furthermore we actually tend to punish the exceptional people who reason more abstractly about ethics, as we don’t trust them to have the right feelings.

Now humans do seem to have a special wartime ethics, which is more abstract and flexible. But we are quite reluctant to invoke that without war, even if millions seem likely to die in a pandemic. If billions seemed likely to die, maybe we would. We instead seem inclined to invoke the familiar medical ethics norm of “pay any cost to save lives”, which has pushed us into apparently endless and terribly expensive lockdowns, which may well end up doing more damage than the virus. And which may not actually prevent most from getting infected, leading to a near worst possible outcome. In which we would pay a terrible cost for our med ethics inflexibility.

When a sudden crisis appears, I suspect that generalists tend to know that this is a potential time for them to shine, and many of them put much effort into seeing if they can win respect by using their generality to help. But I expect that the usual rulers and experts, who have specialized in the usual ways of doing things, are well aware of this possibility, and try all the harder to close ranks, shutting out generalists. And much of the public seems inclined to support them. In the last few weeks, I’ve heard far more people say “don’t speak on pandemic policy this unless you have a biomed Ph.D”, than I’ve ever in my lifetime heard people say “don’t speak on econ policy without an econ Ph.D.” (And the study of pandemics is obviously a combination of medical and social science topics; social scientists have much relevant expertise.)

The most likely scenario is that we will muddle through without actually learning to be more flexible and reason more generally; the usual experts and rulers will maintain control, and insist on all the usual rules and habits, even if they don’t work well in this situation. There are enough other things and people to blame that our inflexibility won’t get the blame it should.

But there are some more extreme scenarios here where things get very bad, and then some people somewhere are seen to win by thinking and acting more generally and flexibly. In those scenarios, maybe we do learn some key lessons, and maybe some polymath generalists do gain some well-deserved glory. Scenarios where this perfect storm of inflexibility washes away some of our long-ossified systems. A dark cloud’s silver lining.

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