The summer in America’s South was somewhat incredible. People were refusing to wear masks, refusing to socially distance, and COVID-19 cases were increasing tremendously. Many hospitals were stressed and sending patients to other hospitals, then to other states. As the problem grew, with some version of it appearing in Texas, Arizona, Mississippi, Louisiana, Alabama, Florida and hints of the problem in Arkansas, Georgia, and the Carolinas, the obvious question was, “Where will we send overflow patients now?” This is the biggest concern with COVID-19. Not its raw death rate, but its ability to infect widely and quickly. If hospital services run out, the death rate would certainly increase, possibly catastrophically. Yet, again, something somewhat incredible happened.
Almost everywhere, just as hospitals hit capacity, the rate of new cases began to decrease. It was a peak everywhere. Many theories have been created to explain this, and many of them aren’t very good. There are people out there who claim that once around 20% of a population gets infected with COVID, the number of new cases begins to die off. Some people claim, rather assert, that herd immunity explains this phenomenon. Those advocating this theory want to also assert that this a protective herd immunity which will prevent additional crises in the future. The reality is that this theory has no evidence to back it up. In measurable, isolated settings the virus does seem to quickly spread to the known herd immunity threshold of 80-90%. There’s only circumstantial evidence that protective immunity has anything to do with the declining cases that appear at this vaunted 20% mark. In addition, in Japan where I live, for example, peaks have occurred nowhere near the 20% mark. It can’t be herd immunity.
In spite of the lack of evidence for herd immunity occurring, it is very interesting that there are examples of places around the world with vastly different government policies and local socio-economic conditions where the same phenomenon occurs. A spike of cases hits around the 20% threshold, then rather than becoming an exponentially steep explosion of new cases requiring field hospitals and the like, the cases start to taper off. Sometimes this happens quickly, sometimes it’s more of a long plateau. Although the evidence isn’t clear yet, there could be a profoundly interesting story about human behavior explaining some of these examples.
One premise of libertarian thought is that the effects of human action, of society’s behavior, are always much greater than whatever direct influence the government has. It is sometimes said that laws are changed post-facto, reflecting the consensus which has already emerged in society. That people break laws willfully, or engage in behavior voluntarily, before laws are repealed or made. There’s probably a lot more nuance to that and also reasons why the government does what it does (in terms of incentives). However, the idea that society’s private behavior is regulated by what’s on the law books is absurd.
With COVID case increases and declines, there appears to be a story of people changing their behavior. I will propose, in a speculative manner, that voluntary behavioral changes have had the greatest effect on COVID outcomes. There seems to be an information mechanism which most greatly affects these behavioral changes. Therefore, attentiveness to the amount and quality of information could be the most impactful way to address the pandemic, no matter the country. The same principle could also apply to other issues that involve trust and public commons. It could be that we don’t need laws or rules to govern most of these commons, but we do need information. Creating, providing, and promoting information and data could be a constructive and productive action for libertarians seeking to find non-coercive ways to better manage public commons.
Social Distancing Makes The Difference In Pandemics
I hypothesize that the greatest impact on outcomes with the virus during this current pandemic comes from voluntary behavioral changes (as opposed to government policies or surprise immunity conditions). I also hypothesize that information and perceptions have the greatest impact on these behavioral changes.
Although completely intuitive, there is now clinical evidence from Johns Hopkins that confirms that people who practice stricter social distancing spread SARS-CoV-2 less. SARS-CoV-2 is a respiratory illness. You catch it by breathing the same air as people who have it. If people are not going to places where they share the same air with other people, the virus simply won’t spread. What is less intuitive is the direct breakdown of the degree to which we are mixing socially with other people, on a country-by-country basis, even among different professions and cultures within the same city. Some cultures have large, multi-generational households. Some cultures throw large house parties or gatherings frequently. Other cultures, such as in Sweden or Japan, have an extraordinarily high rate of single-person households. In Sweden’s case, business have accommodated work from home to a tremendous degree.
An immunologically naïve population can be compared to a dry field of grass during wildfire season. Some fields are all grass, all dry. Some places have patches of water, or trees and rocks. Some places are suited for the fire to spread evenly, but many places aren’t. The places where people are breathing the same air—that’s where the dry grass is. Some situations are like California, in that respect. Others are more like Kentucky (where a lightning strike might burn a few trees before it’s over). Understanding why COVID is spreading or not in certain places first and foremost requires us to ask, “What’s the terrain like?” Lockdown policies, hand sanitizing, and temperature checks, even masks don’t really matter as much as simply who is meeting with other people, how much, and how often.
This is an unprecedented global event in the sense that people are not socializing. They’re staying home, not breathing the same air as each other to a degree that has never happened before in history. For every doubter who scoffs at COVID restrictions and fears, and ostensibly lives an approximation of normal life, there are certainly that many more people—rationally or not—simply staying home far more than they did in 2019. Sure, lots of people are saying, “I’m over it,” and going to movies. Yet, go to the theater, I dare you. You won’t find a lot of people there, not compared to before. Yes, it may be low risk, buts that’s partly because of how many people still refuse to go out—keeping the rate of spread low.
Sweden is upheld as an example of why we should not be social distancing, by some. They claim that some version of herd immunity has occurred. The reality is, while Sweden might be praised for not having repressive lockdowns, the country has produced declining case numbers through social distancing and summer weather. Sweden is a fairly socially distanced society; just listen to what they have to say about it.
Widespread behavioral changes are greatly impacting outcomes, but small, manageable behavioral changes can matter too. A CDC study has linked dining at restaurants with increased COVID-19 transmission. This study doesn’t say that eating at restaurants will make you sick, but it is saying that there’s a correlation between certain behavioral patterns and outcomes. I’m not pointing this out to be judgmental. Think of a throttle or gas peddle. There are daily choices that can be made, and if enough people make certain small choices, the virus will spread more. This is part of my hypothesis.
A final piece of evidence that social distancing really makes a difference is that the flu seems almost unable to spread in the socially distanced environment we’ve created for COVID. Numerous examples from the Southern Hemisphere, which experiences a winter flu season in the middle of the year, show that social distancing has had a huge impact on the spread of the flu. That is, it hasn’t spread. Some authors, perhaps overzealous in arguing against lockdowns, have tried to claim that social distancing itself is a waste of time. Distancing’s impact on the flu shows that it’s quite effective. SARS-CoV-2 is just that bad, that it still spreads when many people are social distancing.
The importance of social distancing in explaining outcomes with COVID-19 leads me to a conclusion about how the crisis can be managed without relying on coercive policies. I have a hypothesis which explains why exponential case growth in places like Arizona didn’t happen this summer.
I believe that as hospitals became full in places like Arizona, that even people who were formerly defiant with their personal behavioral choices finally decided to play it safe. I also concede that within specific communities and even neighborhoods it is possible that some level of herd immunity was reached. In other words, lack of social distancing led to a near hospital collapse, but then public fears inspired social distancing which finally reduced new cases. Social distancing would have been the main causal variable, even if herd immunity helped a little at the margins among persistently defiant communities, or essential workers unable to distance. Even though folks were behaving rather inconsistently, the outcome remains remarkable.
When presented with clear information that risk levels were rising meaningfully, the people of Arizona probably changed their behavior voluntarily. Enough to change the outcome. This raises the question: how much more could the outcome be improved if the quality of information had been better from the beginning?
Red Light, Green Light
It’s a story heard around the world. Governments gave conflicting information about this pandemic. This is true in spite of country, party, political orientation, expert, non-expert—all of the above. Many in the libertarian sphere would complain that COVID is overly hyped by elements of the government as some sort of scam. However, it’s also true that governments have downplayed the severity of the crisis in many circumstances, to avoid negative scrutiny. This downplaying has certainly contributed to negative outcomes. Is it now okay for the government to lie to us to the detriment of our health? I suppose it depends on what you believe is best for your health. The fact that we all believe different things matters profoundly in this discussion, but the government has no business lying or obfuscating data.
One example of an information problem created by a government comes from Texas. The public data concerning COVID cases in Texas has been presented in a very inconsistent and difficult to interpret way. Even now, in the United kingdom, the government with its vaunted national health system simply cannot scale up testing. Although this stands as commentary about government, the point is that even outside of lockdowns and distancing policies, governments can’t even get the basic information flow right.
Somewhere beyond the political debate around this virus are normal people seeking one way or another to evaluate their personal risk. Knowing whether the virus is spreading in your particular community or neighborhood would be one way to evaluate risk. Yet it seems that we are not producing information that is useful for this purpose.
I would like to present another hypothesis, or rather, more of an proposed axiom of behavioral economics. I don’t believe that people are using data to evaluate the risks of the virus itself. I think that people are calculating risk as it pertains to the behavior of other humans around them. That is, before going out to eat, people don’t add up case fatality percentages in their head. Instead, they consider the loose probability of whether other people around them are behaving in risky ways. It’s the unpredictability of other people that’s the true stumbling block in evaluating risk, not the unpredictability of the virus.
There are two risk evaluation problems associated with this pandemic, not just one. The first problem, of course, are the risks to health associated with catching the disease. However, the other problem is that, absent clear information which can help evaluate risk adequately, people will take a conservative approach and assume the worst. Businesses whose services are, in theory, not incredibly risky depending on the circumstances, are losing customers and going out of business.
There isn’t just a health problem, there’s a risk evaluation problem. We don’t have good information that helps us evaluate risks generated by the behavior of other people. We are unable to accurately predict their behavior.
When the virus is spreading a lot, we don’t have the right information to convince us to social distance early. There are times when social distancing is just unnecessary from the perspective of personal health risks. However, when the virus begins to spread in a community, quick and strict distancing can stop the spread before it grows to eventually lead to real health risks. In this case, the social distancing is tied to a selfish motive, but the effectiveness of the practice depends on the choices of other people in the community and an assurance that they are as community minded as you are. We can’t necessarily create this situation every time, but in many cases a community might already possess the intelligence and values to do something like this. What they would lack is clear information to establish trust. Clear information would tell people that if they are choosing to distance early, maybe others are as well.
On the other side of things, once new cases have peaked in a community, there’s a question of when it would be appropriate to start taking risks again. This is also a trust problem. Everyone starts off knowing that it’s a risky time, but when do we decide that the social distancing isn’t needed? There have been many examples of distancing that ended too quickly, leading to large new outbreaks. On the other hand, there’s everyone thinking that they don’t know what’s going on, so they’re just going to stay home in the long-run. Both situations are bad. Ultimately, even a perfectly coordinated society following expert advice could screw this up. Perfection isn’t the goal, just outcomes tomorrow that are better than today.
For situations where outbreaks have recently begun, and in situations where the peak has already passed, there will be different groups of people with different opinions and behavioral patterns. We should expect that there will never be perfect consensus and coordination. What is needed is clear information that allows us to make predictions and risk calculations about all these other groups of people and whether or not we trust them. We don’t need to trust them, we only need to trust that we can predict what they’re doing.
There’s a perfect metaphor which explains how risk evaluation in the public trust commons can affect behavior, and how information can improve the situation.
Consider the traffic light. Red means stop, green means go.
Have you ever been stopped in the middle of the night at a red? No one’s around, so why not go? It is said that, “There are two kinds of people in the world.” Perhaps there are people who would run the red, and those who wouldn’t.
Probably, the strongest emotional response would come from the red light runners. “Why wouldn’t someone go, if no one’s around? Scaredy-cats!” they might say.
Here’s why I’m not a red-light runner. If red doesn’t mean stop, green can’t mean go. Green means go. If I see green, I don’t slow down or double check if someone’s running a red. I just go (unless I’m on a motorcycle, in which case I try to keep track of the traffic in every intersection no matter what). When people run reds, they ruin that.
Sure, someone stops in the middle of the night at a red. No one’s around, so they go. Except, oops, they didn’t see that one tall bush in the dark and didn’t realize the road curved as much as it did. Maybe this person, by happenstance, is also just kind of an idiot. Maybe they’re tired and stressed from work, more than usual. More than they realize. They have decided, unilaterally, that they are qualified to make a risk judgment.
Then, along comes someone cruising past the green. It’s green, so they didn’t slow to check behind the bush. Green means go. The red light runner never asked Mr. Green Light if he was okay with Mr. Red Light’s ability to unilaterally judge risk at that moment. Crash!
This might be hard to hear for many in the libertarian community frustrated by the change in the social environment caused by the pandemic, but if you make a risk tolerance decision for yourself, but your actions also increase risks for other people, that’s an act of aggression. In the case of COVID-19, certainly unenforceable. Even so, libertarian ethics is pretty clear that we have a duty to consider the negative rights of others in proportion to our desire to have them respect our rights. This is the basis of the non-aggression principle. It is not adequate, ethically, to declare that you are willing to tolerate the risk of an infectious disease, when your behavior increases risks for other people whom you didn’t ask. Still, this is libertarianism. There are a lot of things that are the, “Right thing to do,” which can’t be coerced.
Returning to the allegory, imagine what happens if a group in society suddenly decided to run red lights, even during the day. Even if there is traffic. These people would decide that they are qualified to know when there’s enough space in the flow traffic to safely run the red. Imagine now that, even if rare, many accidents do occur because of this. From time to time, some people make bad judgments about when it’s safe to go. How long until people start slowing down as they approach green lights. Have you ever been driving behind someone as they slow down before a green? Isn’t it frustrating?
In this situation, the red light runners may not be increasing the risks of accidents by that much. In proportion to total traffic, the number of accidents might be very low. A libertarian could argue that coercive fines for running red lights is an aggression, considering how little damage is actually done by red light runners. Even so, let’s consider what changes once red no longer means stop.
What the red-light runners have done is made calculating risk much more difficult. Previously, green light goers would know that the chances of someone running a red was so low that they didn’t have to worry about it. Now, you never know who’s sitting at that red. The consequence is a massive shift in behavior that makes driving significantly more frustrating. Accident risk isn’t much higher, but predictability is significantly lower, therefore behavior changes significantly. It changes out of proportion to the risk. The reason is that now you have stressful split-second maneuvers at green lights preventing a lot of accidents, which, if they didn’t occur, would lead to many more accidents. The red light runners haven’t greatly increased actual accident risk, they’ve just made driving profoundly more stressful.
Traffic light designers seem to have solved the information and trust problem associated with situations where running red lights is common. This is the blinking yellow and blinking red light. The blinking red light does require a full stop before proceeding, but unlike a red it does not require drivers to sit and wait at an intersection. This means that if you judge that no one’s around, you can go. Consequently, green no longer means go. The blinking yellow means you don’t have to stop, but there could still be people crossing the intersection, so slowing down a little and checking is merited.
The blinking yellow and blinking red lights are profound. In one sense, it’s almost like a 4-way stop sign. There’s one key difference. By providing information to the public commons about how one direction of traffic is required to stop, and the other direction of traffic is not required to stop, then a relatively high rate of flow can be maintained. This is much more convenient than stop signs at every intersection, but it also is a situation where everyone knows the risks are a bit higher at the intersection, so a little extra caution is merited.
In other words, the blinking yellow and red lights provide a single piece of clear information that takes a chaotic free-for-all and transforms it into a much more convenient situation by creating a clear picture of risk around which people can modify their behavior. The setup better allows drivers to predict each others’ behavior.
I propose that this principle represents the most effective path for mitigating the COVID-19 situation. This solution doesn’t get rid of COVID. It doesn’t address whether or not COVID is “just the flu.” Simply put, all else being equal, whatever happens, the best available option for producing the most constructive and impactful outcome is clear public information.
A System Of Testing; Consistent, Accurate, Precise
Social distancing behavior affects the rate of spread of COVID-19. Perception affects distancing choices (one example here). Information, when inconsistent, devalues future information. If clear information is going to make the pandemic situation better, it has to be consistent.
One of my hypotheses is that public behavior when influenced by risk evaluation considers predictions about the behavior of others more than it considers the discrete, scientific risk of a situation. That is, people want to feel that they know how others will act. Based on their perceptions of others’ behavior, people will change their behavior accordingly. Therefore, if public information is going to change behavior, people won’t only think about the information itself and how they feel about it. People will also think about who in the community around them is receiving and reacting to the same information. People need to observe the information, then observe the reaction of others, in order to learn a full pattern of risk. If the information is not presented to the public in an incredibly consistent way, then people will not be able to build a system of risk evaluation.
The information has to be accurate. It has to be credible. It shouldn’t be used to provoke behavioral changes. It should simply exist, and then society gets to settle upon a tapestry of reactions which in turn will lead to second-order behavioral changes. It’s game theory. People don’t only react to situation, they also react to each other. If the government tries to tailor information to provoke outcomes, they’ll only disequilibrate the game. Optimal outcomes in games occur when there is predictability.
There are many kinds of COVID tests. There are tests which test for antigens—the active presence of the virus or even dead virus particles in your body. There are antibody tests, which indicate whether your body might have been exposed to the virus in the past and has a memory of it. Many of these tests are inaccurate. Some produce false positives but not as many false negatives. Some produce false negatives more than false positives. Some are very sensitive and can pick up small amounts of what they’re testing for. Some take time to process, others are rapid. Even within the same category of tests, there are older, slower machines, and newer machines. There are private labs, government labs, contracted labs, university labs and so forth. It’s all a mess. Unless some version of this can be sorted out into a neat and tidy pattern, the information won’t be useful. Here’s a discussion on some of the issues with testing. Even so, it can be sorted out.
The right mix of testing, presented consistently in an information platform, can provide precise insights. There are sewage tests which are excellent at detecting the beginnings of an outbreak in a small community, and do so at lower cost with no disruption to our lives and routines. Rapid testing isn’t as accurate, but it’s cheap and fast. It’s not appropriate for proving that everyone coming into a house party isn’t infected. However, it is appropriate for catching early signs of an outbreak. It is appropriate for realizing there might be a cluster at an office or school, and that more precise tests are needed. Having a testing algorithm, or system, is needed for any of this information to be helpful.
This is the solution: an information platform that publishes testing data. It must publish location, occasion and time. Maybe also details about the person (demographics, job, health background—if available, anonymously of course). It must be paired with a rubric, a kind of industry standard testing protocol. A recommend mix of testing, and information about whether different localities are conforming to that mix or not (that is, the degree to which they are conforming). The platform isn’t government. There are no policies or lockdowns associated with it. There are no mandates about who must or must not be tested, etc. It’s a publishing platform, and a testing rubric. As more organizations combine to join compatible platforms and meet the same standards, then information consistency, accuracy, and precision can be achieved.
Rather than waiting until thousands die and hospitals nearly collapse to start social distancing (great job Texas, Florida, New York etc.), we can know when to start doing it a little earlier. We can know this on a neighborhood by neighborhood basis so we don’t socially distance for no reason, when it’s not necessary yet. When outbreaks die down, or before they arrive in our neighborhoods, we can trust that the risks of not social distancing are low. We can live more normally.
Undoubtedly, there would be red light runners in this situation. But with a blinking yellow light, we can maintain a decent flow of traffic anyway.
Winter Is Coming
I don’t think that COVID-19 is a hoax. It has the potential, in my opinion, to be genuinely catastrophic and deadly. However, this would only occur as medical care is overwhelmed. This condition has occurred, for example in La Paz, Bolivia, where people were dying who didn’t need to, because there was no more room in hospitals. Even so, a kind of exponential case growth rate never quite manifested. Thousands, not millions, died.
In my opinion, medical care will never be completely overwhelmed while exponential case growth continues indefinitely. The reason is because people are social distancing. Eventually, people socially distance, and it makes a difference. Even in skeptical states like Arizona, when things get truly bad, people seem to change their behavior. Social distancing is making a difference even in poorer nations, who may be doing it more because they’re more worried about risks to their medical system. That’s great news: maybe the virus will never become truly deadly at its full potential. However, the price for avoiding this fate are the costs associated with social distancing.
People who think COVID-19 is a hoax lament the so-called fear of people who stay home. That’s the irony. They’re right when they say risks are pretty low in some cases. The social distancing of people who are worried may play a big role in why risks get low.
We don’t have to agree with either side of the COVID debate. Some people refuse to be worried. Some people will always be worried. The key is, how do we manage our decisions in an environment where different people are making different choices? By having predictability, through clear information. Testing. That way, without having to settle the debate, we can still achieve the best possible outcome available under the circumstances.
Clear and consistent information which provides people with the ability to predict each others’ behavior can serve to order the public commons. Above and beyond the pandemic situation, this principle could be very useful for future libertarians who seek to constructively address commons problems.
In the recent heyday of the ethno-nationalist movement, an argument was put forward about trust. The alt-righters claimed that the only way to avoid a leviathan police state was to have a strong public trust commons. Supposedly, some libertarians who are opposed to strong government were swayed by the argument that only an ethnically similar population with a common tribal and familial commitment to each other could generate a public trust commons sufficient to avoid the need for a strong hand of government.
We don’t need to trust each other, nor do we need a heavy hand of government. What we need is to be able to consistently predict each others’ behaviors. This could be the great keystone of a pluralistic libertarian society. However, the predictability can only come from the lever of clear and consistent public information.
What if there was a platform that displayed data on crime and police behavior? Not the data itself, but a publishing platform. The design of the platform would matter. What particular information is presented consistently, and how the fidelity of data is handled in a decentralized environment are key problems to solve. In theory, such a platform could do more to change outcomes in policing and crime than specific policy changes.
What if you knew when it was more likely that a cop would shoot you? What if, somehow, you could identify a simple behavior you could change to avoid that outcome? What if cops realized that people are acting differently, and so now they have more room to change? What if cops know that more people are watching very specific situations much more closely?
Right now it’s chaos. TikTok videos, outraged retweets. Cops do bad things. Then again, sometimes the whole story isn’t told in a single Facebook post. People who already want to think the cops are good guys find every reason to doubt that cop killings is a real problem. We can’t change people, and in many cases, we can’t really change policy. Imagine, though, if all the same people all saw the same set of crystal clear information, and all slightly changed their behavior accordingly. It seems this is how big changes occur in a complex society. Adding up gains at the margins. You have to know where they are. Like Aikido, or Judo.
Even if testing isn’t the way out of COVID-19, and nothing comes of my observations, the value of information is still an important lesson for libertarian activism.
As for COVID itself, I know that many people are skeptical about whether it’s really a big deal or not. Common cold coronaviruses are known to be extremely seasonal (that is, they produce much more severe outcomes in the winter). Some believe that because COVID-19 has been spreading in the summer, that it isn’t seasonal. However, case outcomes have improved substantially since the beginning of the pandemic. There are many theories for this, but one possibility is that this is certainly a seasonal virus, it’s just so bad that it continues to cause problems in the summer. If you don’t believe in this thing, fine. But please, for the sake of your family, just hang on until the end of this winter. After that, maybe we can all move on.
For the sake of information precision, I’ll repeat that the months of concern seem to be December through March. Some headlines claim that fall and winter could be dangerous. If it’s still October, hey, maybe going to that movie is just fine.