Tag Archives: Pandemic

The High Cost of Masks

In my debate last night with Tomas Pueyo, after I emphasized the high costs of lockdowns he said lockdowns are over. From now on we’ll let people go out, as long as they (M) wear masks and keep 6 feet apart when not at home. Which let me to wonder: just how much cheaper is M than lockdowns?

So I tried some Twitter polls. I asked:

  1. [1.14%] If you by law had to M unless you paid, what % of income would you pay?
  2. [4.6%] If you didn’t have to, but were offered % of income to M, what would it take?
  3. [19.6%] Like (2), except it is 2019 and there is no pandemic.
  4. [8.0%] Like (3), except half of the folks in your area are already M-ing
  5. [5.2%] Like (4), except only masks, no 6ft distancing.
  6. [15.8%] Like (4), except both at home and away.

In brackets before each question is the median answer (using lognormal fits to % responses re theses 4 options: <3%, 3-6%, 6-12%, >12%). Note how widely these estimates vary!

The following factors plausibly influence these responses: (A) personal pain and trouble of wearing masks and keeping apart, (B) endowment effect of preferring to stick with what current law seems to endorse, (C) not wanting to look or act too differently from others nearby, (D) wanting to be and seem pro-social and helpful in slowing the pandemic, and (E) wanting to support your side of current culture wars.

The big variation in median answers suggests that non-A effects are big! And the big variation within each poll also suggests that these costs vary greatly across individuals. We might gain lots from policies that let some pay to avoid M-like policies.

Question (4) seems to me to offer the best estimate of the real social cost of doing M. It has the best chance of avoiding effects C & D, and I don’t see a way to avoid E. Regarding B, I think we do want the endowment effect to go this direction, because in fact M was not the legal default a year ago. Yes we enjoy helping our community in a crisis, but we wouldn’t endorse creating crises just to enjoy such effects. So we shouldn’t include then when calculating how much to avoid or reduce crises.

Now this 8.0% median (27% mean) of income cost of masks and public distancing doesn’t include all costs; businesses and other places must also pay to accommodate your distancing. But it is probably a big fraction of costs. And it is quite a bit lower than the 32% of GDP estimate for recent strong lockdowns.

However, my estimate of the total cost of having 50% of the population infected at 0.5% IFR was 3 weeks of income, or 6% of one year’s income. So if we wear masks for 9 months, that single cost equals the entire cost of failing to contain. So as with lockdowns, we should be wary of spending more to prevent infections than the infections would cause. Yes, we should be willing to overspend for very effective preventions, with high elasticity. But masks aren’t plausibly such a very effective method.

Added 30May: I added new polls, included on the above list as #5,6. Seems more than half the cost is from the masks alone. It also seems that masks at home would give similar benefits, and the above suggests that it costs about the same too. So why isn’t there more of push to require that?

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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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Pandemic Futarchy Design

Researchers … use … feeds from a global network of students, staff and alumni to construct a “stringency index” that boils down to a single number how strictly governments in 160 countries are locking down their economies and societies to contain the spread of the virus. … plans to include state-by-state measures of stringency in the U.S. … latest version … draws on 17 indicators to determine the stringency of the government response. (More)

Not that I hear anyone eagerly clamoring to try, but let me sketch out how one would use decision markets to set pandemic policy. Just to plant another flag on how widely they could be usefully applied, if only enough folks cared about effective policy.

As you may recall, a decision market is a speculative (i.e., betting) market on a key outcome of a decision, conditional on which discrete decision is made. To apply these to the current pandemic, we need to pick

  1. key ex-post-measurable outcome(s) of interest,
  2. likely-enough key decisions which could substantially influence those outcomes,
  3. participants capable of learning a bit about how decisions related to outcomes,
  4. sponsors who care enough about informing these decisions, and
  5. legal jurisdictions that may allow such markets.

Regarding participants, sponsors, and permission, it makes sense to be opportunistic. Seek any sponsors interested in relevant questions, any participants you can get to trade on them, and any jurisdiction that let you want to do. Alas I have no sponsor leads.

For key decisions, we could consider using bills before legislatures, administrative rulings, or election results. But there are a great many of these, we don’t get much warnings about many, and most have little overall impact. So I’d prefer to aggregate decisions, and summarize policy via three key choice metrics per region:
Lockdown Strictness. As described in the quote above, some have created metrics on lockdown strictness across jurisdictions. Such metrics could be supplemented by cell-phone based data on trips outside the home.
Testing Volume. The number of tests per unit time, perhaps separated into the main test types, and perhaps also into accuracy classes.
Tracing Volume. The number of full-time equivalent tracers working to trace who infected whom. Perhaps supplemented by the % of local folks use apps that report their travels to tracing authorities.

Yes, worse pandemic outcomes will likely cause more lockdown, tests, and tracing. But one could look at outcomes that happen after decisions. Such as how average future outcomes depend on the decisions made this month or quarter.

For key outcomes, the obvious options are deaths and economic growth.

For deaths, we can avoid testing problems by looking at total deaths, or equivalently “excess” deaths relative to prior years. It helps to note the ages of deaths, which can be combined with local mortality tables to estimate life-years lost. Even better, if possible, note the co-morbidities of those who died, to better estimate life-years lost. And even more better, have estimates of the relative quality of those life-years.

For economic growth, just take standard measures of regional income or GDP, and integrate them many years into the future, using an appropriate discount factor. Assuming that the temporary disruption from a pandemic is over within say 10 years, one could end the bets after say ten years, projecting the last few years of regional income out into the indefinite future.

As usual, there will be a tradeoff here re how far to go in accounting for these many complexities. I’d be happy to just see measures of life years lost related to lockdown strictness, perhaps broken into three discrete categories of strictness. But I’d of course be even happier to include economic growth as an outcome, and tests and tracing as decisions. Either aggregate all outcomes into one overall measure (using values of life years), or have different markets estimate different outcomes. For decisions, either separate markets for each type of decision. Or, ideally, combinatorial markets looking at all possible combinations of outcomes, decisions, and regions.

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Farrell On Who Pushes To Open

Recently I wrote:

While the public will uniformly push for more opening, elites and experts push in a dozen different directions. If elites would all back the same story and solution, as they did before, they would probably get it. … So elites and experts don’t speak with a unified voice, while the public does. And that’s why the public will win. While the public tends to defer to elites and experts, and even now still defers a lot, this deference is gradually weakening. We are starting to open, and will continue to open, as long as opening is the main well-supported alternative to the closed status quo. … public pushes will will tend to be correlated in a particular direction, in contrast with the elite pushes which are much more diverse.

Also, my poll on “If in your region, pandemic continues to grow, or decline very slowly, for N more months, you will support a weaker lockdown,” got a median answer N = 1.2.

Henry Farrell responded:

People … are in favor of stay at home orders, … It could be that people are lying …but it would be unprecedented for so many of them to be lying. … So why then, may the equilibrium break down? It’s clearly not because of express demand from the public. Nor because of cheating … The plausible answer is that private power asymmetries are playing a crucial role in undermining the equilibrium. Some people – employees with poor bargaining power and no savings – may find themselves effectively coerced into a return to work as normal. … this is certainly a situation where the state and private actors are looking to get into cahoots, but not in the ways that public choice economists have devoted significant analytic energy to. And if you want an illustration of Marxist arguments about the “structural power of capital” to threaten politicians … Where public choice people seem to perceive a “public” that collectively wants to return to work, I see something different – a set of asymmetric power relations that public choice scholars are systematically blind to …

So here’s my bet. If the public choice analysis is right, and this is about some kind of broad and diffuse “public” pushing back against impossible regulations, then we will see a return to the economy sooner rather than later. But we can reasonably presume that this return will be roughly symmetric. … In contrast, if I’m right, we will see a very different return to “normality.” The return to the economy will be sharply asymmetric. Those who are on the wrong end of private power relations – whether they are undocumented immigrants, or just the working poor – will return early and en masse. Those who have the choice and the bargaining power will tend instead to pick safety. …[This] highlights the frequently brutal power relations that public choice scholars shove under the carpet when they talk about the “public” wanting an end to lockdown and a return to past economic relations.

So, Farrell says that it might look like people want to work, but this is only because “power asymmetries” let bad firms force them. If those firms would just be good enough to keep paying full wages, why then workers would happily stay home forever. Thus proving its not ordinary people who push to open, it is really the evil capitalists pushing. As also proven by those polls. Economic theory (what “public choice” scholars use to study politics) just can’t explain why poor people with less savings might be more eager to work; for that you need “private power relations” theory.

Wow. As you can see, I am not making this up.

Look, even if we kept printing plenty of money to hand out to workers to all stay home, eventually there wouldn’t be anything to buy, because no one was making and distributing products and services. And then no one would be happy to stay home. The fact that someone needs to work in order to make our world function isn’t some conspiracy foisted on us by the asymmetrically powerful, it is just a basic fact about our world that would also apply in Marxist heaven, or any other social system.

There are many channels by which such fundamental pressures will be communicated to the political equilibrium, but they must all lead to the same place. We are paying a real price for not working, we will only continue if we see sufficient value in it, and even then for only a limited time. Every non-crazy theory of politics must predict this. And economists, including those who study politics, do in fact predict that the poor will push first and harder, as they run out of resources first. Maybe you blame the very existence of the poor on evil capitalists, but this outcome happens regardless of why there are poor, it only requires that they exist.

Who pushes the least? Rich elites who can work from home selling abstract arguments that blame all problems, even pandemics, on (other) evil rich.

Note that we also have many non-work social needs that push us to open. And employers are similarly willing to stay home if we keep sending them checks.

Added: Farrell quickly responded:

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Why Openers Are Winning

Three main relevant groups have vied lately to influence pandemic policy: public, elites, and experts. Initially, public health experts dominated, even when they screwed up. But then they seemed to publicly assume that it was too late to contain Covid19, and the only viable option was “flattening the curve” to get herd immunity. At that point, elite opinion worldwide objected loudly, and insisted that containment be the official policy.

Experts and the public demurred, and elites got their way. Everywhere in the world, all at once, strong lockdown polices began, and containment became the official goal. But elites did not insist on any particular standard containment policy. Such as, for example, the packages of polices that seem to have worked initially in Wuhan or South Korea. Instead elites seemed satisfied to let the politicians and experts in each jurisdiction craft their own policy packages, as long as they seemed “strong”, involving much public sacrifice. And they allowed official public messages suggesting that relatively short durations would be sufficient.

A few months later, those duration periods are expiring. And in the different jurisdictions, the diverse policies now sit next to quite diverse outcomes. In some places, infections are low or declining, while in others they are flat or increasing. The public is feeling the accumulated pain, and itching to break out. If these flat or increasing trends continue, containment will fail, and lockdown harms will soon exceed plausible future gains from preventing medical system overload.

Elites are now loudly and consistently saying that this is not time to open; we must stay closed and try harder to contain. When confronted with the discouraging recent trends, elites respond with a blizzard of explanations for local failures, and point to a cacophony of prophets with plans and white papers declaring obvious solutions.

But, and this is the key point, they mostly point to different explanations and solutions. For example, this polls shows very little agreement on the key problem:

So while the public will uniformly push for more opening, elites and experts push in a dozen different directions. If elites would all back the same story and solution, as they did before, they would probably get it. If they would say “We agree that this is what we did wrong over the last few months, and this is the specific policy package that will produce much different outcomes over the next few months.” But they aren’t saying this.

So elites and experts don’t speak with a unified voice, while the public does. And that’s why the public will win. While the public tends to defer to elites and experts, and even now still defers a lot, this deference is gradually weakening. We are starting to open, and will continue to open, as long as opening is the main well-supported alternative to the closed status quo, which we can all see isn’t working as fast as expected, and plausibly not fast enough to be a net gain. Hearing elites debate a dozen other alternatives, each supported by different theories and groups, will not be enough to resist that pressure to open.

Winning at politics requires more than just prestige, good ideas, and passion. It also requires compromise, to produce sufficient unity. At this game, elites are now failing, while the public is not.

Added 3p: Many are reading me as claiming that the public is unified in the sense of agreeing on everything. But I only said that the public pushes will will tend to be correlated in a particular direction, in contrast with the elite pushes which are much more diverse. Some also read me as claiming that strong majorities of the public support fast opening, but again that’s not what I said.

Added 6May: Here is data suggesting people are getting out more. Here is data suggesting increasing support for opening.

Added 7May: This poll suggests patience is thin. Lognormal fit says only willing to wait median of 1.2 months (mode 0.08, mean 4.7).

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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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Constant Elasticity Prevention

While many engaged Analysis #1 in my last post, only one engaged Analysis #2. So let me try again, this time with a graph.

This is about a simple model of prevention, one that assumes a constant elasticity (= power law) between harm and prevention effort. An elasticity of 1 means that 1% more effort cuts harm by 1%. For an elasticity of 2, then 1% more effort cuts harm by 2%, while for an elasticity of 0.5, 1% more effort cuts harm by 0.5%.

Such simple “reduced form” models are common in many fields, including economics. Yes of course the real situation is far more complex than this. Even so, reduced forms are typically decent approximations for at least small variations around a reference policy. As with all models, they are wrong, but can be useful.

Each line in the following graph shows how total loss, i.e., the sum of harm and prevention effort, varies with the fraction of that loss coming from prevention. The different lines are for different elasticities, and the big dots which match the color of their lines show the optimum choice on each line to min total loss. (The lines all intersect at prevention = 1/20, harm = 20.)

As you can see, for min total loss you want to be on a line with higher elasticity, where prevention effort is more effective at cutting harm. And the more effective is prevention effort, then the more effort you want to put in, which will result in a larger fraction of the total harm coming from prevention effort.

So if locks are very effective at preventing theft, you may well pay a lot more for locks on than you ever suffer on average in theft. And in the US today, the elasticity of crime with respect to spending on police is ~0.3, explaining why we suffer ~3x more losses from crime than we spend on police to prevent crime.

Recently, I asked a few polls on using lockdown duration as a way to prevent pandemic deaths. In these polls, I asked directly for estimates of elasticity, and in this poll, I asked for estimates of the ratio of prevention to health harm loss. And here I asked if if the ratio is above one.

In the above graph there is a red dot on the 0.5 elasticity line. In the polls, 56% estimate that our position will be somewhere to the right of the red dot on the graph, while 58% estimate that we will be somewhere above that grey 0.5% elasticity line (with less elasticity). Which means they expect us to do too much lockdown.

Fortunately, the loss at that red dot is “only” 26% higher than at the min of the grey line. So if this pandemic hurts the US by ~$4T, the median poll respondent expects “only” an extra $1T lost due to extra lockdown. Whew.

Added 26May: Follow surveys on US find (via lognormal fit) median effort to harm ratio of 3.6, median elasticity of 0.23. For optimum these should be equal – so far more than optimal lockdown!

 

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2 Lockdown Cost-Benefit Analyses

Back on Mar. 21 I complained that I hadn’t seen any cost-benefit analyses of the lockdown policies that had just been applied where I live. Some have been posted since, but I’ve finally bothered to make my own. Here are two.

ANALYSIS #1: One the one side are costs of economic disruption. Let us estimate that a typical strong lockdown cuts ~1/3 of income of econ/social value gained per unit time. (It would be more due to harm from time needed to recover afterward, and to due to for stress and mental health harms.) If one adds 9 weeks of lockdown, perhaps on and off spread out over a longer period, that’s a total of 3 week’s income lost.

On the other side are losses due to infection. I estimate an average infection fatality rate (IFR) of 0.5%, and half as much additional harm to those who don’t die, due to other infection harms. (E.g., 3% have severe symptoms, and 40% of those get 20% disabled.) I estimate that eventually half would get infected, and assume the recovered are immune. Because most victims are old, the average number of life years lost seems to be about 12. But time discounting, quality-of-life adjustment, and the fact that they are poorer, sicker, and wouldn’t live as long as others their age, together arguably cuts that figure by 1/3. And a standard health-econ estimate is that a life-year is worth about twice annual income. Multiply these together and you get an expected loss of 3 week’s income..

As these equal the same amount, it seems a convenient reference point for analysis. Thus, if we believed these estimates, we should be indifferent between doing nothing and a policy of spending 9 added weeks of lockdown (beyond the perhaps 4-8 weeks that might happen without government rules) to prevent all deaths, perhaps because a vaccine would come by then. Or, if death rates would actually be double this estimate due to an overloaded medical system, we should be indifferent between doing nothing and spending 9 added weeks of lockdown to avoid that overloading. Or we should be indifferent between doing nothing and 4 added weeks of lockdown which somehow cuts the above estimated death rate in half.

Unfortunately, the usual “aspirational” estimate for a time till vaccine is far longer, or over 18 months. And a doubling of death rates seems a high estimate for medical system overload effects, perhaps valid sometimes but not usually. It seems hard to use that to argue for longer lockdown periods when medical systems are not nearly overwhelmed. Especially in places like the US with far more medical capacity.

During the 1918 flu epidemic, duration variations around the typical one month lockdown had no noticeable effect on overall deaths. In the US lately we’ve also so far seen no correlation between earlier lockdowns and deaths. And people consistently overestimate the value of medical treatment. Also, as death rates for patients on the oft-celebrated ventilators is 85%, they can’t cut deaths by more than 15%.

We’ve had about 6 weeks of lockdown so far where I live. A short added lockdown seems likely to just delay deaths by a few months, not to cut them much, while a long one seems likely to do more damage than could possibly be saved by cutting deaths.

Of course you don’t have to agree with my reference estimates above. But ask yourself how you’d change them, and what indifferences your new estimates imply. Yes, there are places in the world that seem to have done the right sort of lockdown early enough in the process to get big gains, at least so far. But if your place didn’t start that early nor is doing that right sort of lockdown, can you really expect similar benefits now?

ANALYSIS #2: Consider the related question: how much should we pay to prevent crime?

Assume a simple power-law (= constant elasticity) relation between the cost H of the harm resulting directly from the crimes committed, and the cost P of efforts to prevent crime:

H = k*Pa,  or  dln/ dlnP = –a ,

where a is the (positive) elasticity of harm H with respect to prevention P. To minimize total loss L = H + P, you set P = (k*a)1/(1+a), at which point we have a nice simple expression for the cost ratio, namely P/H = a.

So, when you do it right, the more effective is prevention at stopping harm, then the larger is the fraction of total loss due to prevention. If 1% more prevention effort cuts 1% of crime, you should lose about the same amounts from harm and prevention. If 1% more prevention cuts 2% of crime, then you should lose twice as much in prevention as you do in harm. And if it takes 2% more prevention effort to cut 1% of crime, you should lose about twice as much in harm as you do in prevention.

This model roughly fits two facts about US crime spending: the elasticity is less than one, and most loss comes from the crimes themselves, rather than prevention efforts. Typical estimates of elasticity are around 0.3 (ranging 0.1-0.7). US governments spend $280B a year on police, courts, and jails, and private security spends <$34B. Estimates of the total costs of crime range $690-3410B.

Now consider Covid19 prevention efforts. In this poll respondents said 3.44 to 1 that more harm will come from econ disruption than from direct health harms. And in this poll, 56% say that more than twice the loss will come from econ disruption. For that to be optimal in this constant elasticity model, a 10% increase in lockdown, say adding 12 days to a 4 month lockdown, must cut total eventual deaths (and other illness harm) by over 20%. That seems very hard to achieve, and in this poll 42% said they expect us to see too much econ disruption, while only 29% thought we’d see too little.

(More on Analysis #2 in the next post.)

In this post I’ve outlined two simple analyses of lockdown tradeoffs. Both suggest that we are at serious risk of doing too much lockdown.

10am: On reflection, I changed my estimate of the lockdown from 25% to 27% of income, and my estimate of non-death harm from as-much-as to half-as-much-as the death harm. So my reference added shutdown duration is now 4 months instead of 6.

12pm: Even if recovery gave immunity for only a limited period, then as long as you were considering lockdown durations less than that period, the above calculation still applies, but now it applies to each such period. For example, if immunity only lasts a year, then these are annual costs, not eventual costs. And that’s only if infection chances are independent each period. If, more likely, it is the same people who at more at risk each year, then in later years gains from lockdowns decline.

29Apr, 3am: We are now at 73 comments, and so far all of them are about analysis #1, and none about analysis #2. Also, tweet on #1 got 18 retweets, tweet on #2 got none.

29Apr, 1pm: In two more polls. over half estimate a 10% increase in lockdown duration gives <5% decrease in deaths, for both world and US. Instead of the >20% that would be required to justify allowing twice the damage of lockdowns as health harms.

28May:  I’ve updated the numbers a bit.

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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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Subpoena Futures

A subpoena … is a writ issued by a government agency, most often a court, to compel testimony by a witness or production of evidence under a penalty for failure. … party being subpoenaed has the right to object to the issuance of the subpoena, if it is for an improper purpose, such as subpoenaing records that have no relevance to the proceedings, or subpoenaing persons who would have no evidence to present, or subpoenaing records or testimony that is confidential or privileged. (More)

Parties may obtain discovery regarding any nonprivileged matter that is relevant to any party’s claim or defense and proportional to the needs of the case, considering the importance of the issues at stake in the action, the amount in controversy, the parties’ relative access to relevant information, the parties’ resources, the importance of the discovery in resolving the issues, and whether the burden or expense of the proposed discovery outweighs its likely benefit. (More)

Exceptions are quite limited: self-incrimination, illegally-obtained info, and privileges of spouses, priests, doctors, diplomats, and lawyers. The remarkable fact is that the law has little general respect for privacy. Unless you can invoke one of these specific privileges, you must publicly report to the court any info that it thinks sufficiently relevant to a current court case. You simply have no general right to or expectation of privacy re stuff a court wants to know. Courts don’t even compensate you for your costs to collect evidence or appear to testify.

And yet. Consider what I wrote March 5:

The straightforward legal remedy for [pandemic] externalities is to let people sue others for infecting them. In the past this remedy has seemed inadequate for two reasons:

1. It has often been expensive and hard to learn and prove who infected who, and
2. … most folks just can’t pay large legal debts.
The vouching system directly solves (2), … And the key to (1) is ensuring that the right info is collected and saved.

First, consider some new rules that would limit people’s freedoms in some ways. Imagine people were required to keep an RFID tag (or visible QR code) on their person when not at home, and also to save a sample of their spit or skin once a week? Then phones could remember a history of the tags of people near that phone, and lawsuits could subpoena to get surveillance records of possible infection events, and to see if spit/skin samples on nearby dates contain a particular pathogen, and its genetic code if present. We might also adopt a gambled lawsuit system to make it easier to sue for small harms. (More)

Here, to help law deal with pandemics, I was tempted to propose specific rules re info that people must collect and preserve. Yet if courts can get any info they think relevant, why is there ever a problem with courts lacking info to deal with key harms, such as pandemic infection?

The answer is that current law allows a huge exception to its subpoena power. Courts can force you to reveal info that you have already collected, on paper, a computer, in your head, or in your physical objects. But you usually have no obligation to collect and save info now that the court might want later. As a result, many people and orgs go out of their way to not save incriminating info. For example, firms do key discussions verbally, not recorded, rather than via email. Thus you have no obligation to save spit samples or detailed records of where your phone goes, to help with future pandemic infection lawsuits.

This seems a huge and inconsistent loophole. I could understand if the law wanted to respect a more general right to privacy. Then the court might weigh the value of some info in helping court cases against the social harm from forcing its publication via a subpoena. As a result, it might sometimes block a subpoena even when the info collected would be relevant to a court case.

But I can’t see a reason to eagerly insist on access to info that seems relevant to a court case, and yet put no effort into inducing people to collect and preserve such info beforehand. So I propose that we create a legal process by which legal judgements are made on, if collected and saved, how likely some info would be to be subpoenaed, and how valuable it would be in that case.

When info would be valuable enough if collected and saved, then the court should require this. I don’t have a strong opinion on who exactly should bring a suit asking that such info be saved, or who should represent the many who would have to save that info. But one obvious system that occurs to me is to just have courts usually make ex post estimates of info value by the end of each court case, and then use “subpoena futures” prediction markets to make an estimate of that value ahead of time. (And make it legal and cheap to start such markets.)

So, if a subpoena futures market on a type of info estimates its expected court value to be above a standard threshold, then by law that info must be collected and saved. These prediction markets needn’t be huge in number, if they could estimate the average value of such info collect over a large group, which would then justify requiring that entire group collect the info. Such as everyone in an area who might infect others with a pandemic. If some subgroup wanted to claim that such info wasn’t less valuable regarding them, and so they should be excused, why they’d have to create different prediction markets to justify their different estimates.

For example, when a pandemic appears, if those who might infect others are likely vouched, then those who might be infected would want to require that first group to collect and save info that could be used later to prove who infected who. So they’d create prediction markets on the likely court value of spit samples and phone location records, and use market estimates to get courts to require the collection of that info.

Compared to my prior suggestion of just having the law directly require that such info be collected, this subpoena futures approach seems more flexible and general. What other harms that we do each other could be better addressed by lawsuits if we could require that relevant info be collected and saved?

(Btw, courts need not estimate info value in money terms. They might instead express the value of each piece of info in terms of its multiple of a “min info unit”, i.e., the value of info where they’d be just on the border of allowing it to be subpoenaed for a particular case.)

Added 7a: As mentioned in this comment, we now have this related legal concept:

Spoliation of evidence is the intentional, reckless, or negligent withholding, hiding, altering, fabricating, or destroying of evidence relevant to a legal proceeding …The spoliation inference is a negative evidentiary inference that a finder of fact can draw from a party’s destruction of a document or thing that is relevant to an ongoing or reasonably foreseeable civil or criminal proceeding.

My proposal can be seen as expanding this concept to allow a much weaker standard of “foreseeable”. And instead of allowing a presumption at trial, we just require the evidence to actually be collected.

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