Mental Models For a Pandemic

Mental models help us understand the world better, something which is especially valuable during times of confusion, like a pandemic. Here’s how to apply mental models to gain a more accurate picture of reality and keep a cool head.

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It feels overwhelming when the world changes rapidly, abruptly, and extensively. The changes come so fast it can be hard to keep up—and the future, which a few months ago seemed reliable, now has so many unknown dimensions. In the face of such uncertainty, mental models are valuable tools for helping you think through significant disruptions such as a pandemic.

A mental model is simply a representation of how something works. They are how we simplify complexity, why we consider some things more relevant than others, and how we reason. Using them increases your clarity of understanding, providing direction for the choices you need to make and the options you want to keep open.

Models for ourselves

During a pandemic, a useful model is “the map is not the territory.” In rapidly changing situations like a global health crisis, any reporting is an incomplete snapshot in time. Our maps are going to be inaccurate for many reasons: limited testing availability, poor reporting, ineffective information sharing, lack of expertise in analyzing the available information. The list goes on.

If past reporting hasn’t been completely accurate, then why would you assume current reporting is? You have to be careful when interpreting the information you receive, using it as a marker to scope out a range of what is happening in the territory.

In our current pandemic, we can easily spot our map issues. There aren’t enough tests available in most countries. Because COVID-19 isn’t fatal for the majority of people who contract it, there are likely many people who get it but don’t meet the testing criteria. Therefore, we don’t know how many people have it.

When we look at country-level reporting, we can also see not all countries are reporting to the same standard. Sometimes this isn’t a matter of “better” or “worse”; there are just different ways of collating the numbers. Some countries don’t have the infrastructure for widespread data collection and sharing. Different countries also have different standards for what counts as a death caused by COVID-19.

In other nations, incentives affect reporting. Some countries downplay their infection rate so as to not create panic. Some governments avoid reporting because it undermines their political interests. Others are more worried about the information on the economic map than the health one.

Although it is important to be realistic about our maps, it doesn’t mean we shouldn’t seek to improve their quality. Paying attention to information from experts and ignoring unverified soundbites is one step to increasing the accuracy of our maps. The more accurate we can get them, the more likely it is that we’ll be able to unlock new possibilities that help us deal with the crisis and plan for the future.

There are two models that we can use to improve the effectiveness of the maps we do have: “compounding” and “probabilistic thinking.”

Compounding is exponential growth, something a lot of us tend to have a poor intuitive grasp on. We see the immediate linear relationships in the situation, like how one test diagnoses one person, while not understanding the compounding effects of that relationship. Increased testing can lead to an exponential decrease in virus transmission because each infected person usually passes the virus onto more than just one other person.

One of the clearest stories to illustrate exponential growth is the story of the man who asked to be paid in rice. In this story, a servant is to be rewarded for his service. When asked how he wanted to be paid, he asks to be paid in rice, using a chessboard to determine the final amount. Starting with one grain, the amount of rice is to be doubled for each square. One grain on the first square looks pathetic. But halfway through the chessboard, the servant is making a good yearly living. And after doubling the rice sixty-four times, the servant is owed more rice than the whole world can produce.

Improving our ability to think exponentially helps us understand how more testing can lead to both an exponential decrease in testing prices and an exponential increase in the production of those tests. It also makes clear just how far-reaching the impact of our actions can be if we don’t take precautions with the assumption that we could be infected.

Probabilistic thinking is also invaluable in helping us make decisions based on the incomplete information we have. In the absence of enough testing, for example, we need to use probabilistic thinking to make decisions on what actions to pursue. We ask ourselves questions like: Do I have COVID-19? If there’s a 1% chance I have it, is it worth visiting my grandparents?

Being able to evaluate reasonable probability has huge impacts on how we approach physical distancing. Combining the models of probabilistic thinking and map is not the territory suggests our actions need to be guided by infection numbers much higher than the ones we have. We are likely to make significantly different social decisions if we estimate the probability of infection as being three people out of ten instead of one person out of one thousand.

Bayesian updating can also help clarify the physical distancing actions you should take. There’s a small probability of being part of a horrendous chain of events that might not just have poor direct consequences but also follow you for the rest of your life. Evaluating how responsible you are being in terms of limiting transmission, would you bet a loved one’s life on it?

Which leads us to Hanlon’s Razor. It’s hard not to get angry at reports of beach parties during spring break or at the guy four doors down who has his friends over to hang out every night. For your own sanity, try using Hanlon’s Razor to evaluate their behavior. They are not being malicious and trying to kill people. They are just exceptionally and tragically ignorant.

Finally, on a day-to-day basis, trying to make small decisions with incomplete information, you can use inversion. You can look at the problem backwards. When the best way forward is far from clear, you ask yourself what you could do to make things worse, and then avoid doing those things.

Models for society

Applying mental models aids in the understanding the dynamics of the large-scale social response.

Currently we are seeing the counterintuitive measures with first-order negatives (closing businesses) but second- and third-order positives (reduced transmission, less stress on the healthcare system). Second-order thinking is an invaluable tool at all times, including during a pandemic. It’s so important that we encourage the thinking, analysis, and decision-making that factors in the effects of the effects of the decisions we make.

In order to improve the maps that our leaders have to make decisions, we need to sort through the feedback loops providing the content. If we can improve not only the feedback but also the pace of iterations, we have a better chance of making good decisions.

For example, if we improve the rate of testing and the speed of the results, it would be a major game-changer. Imagine if knowing whether you had the virus or not was a $0.01 test that gave you a result in less than a minute. In that case, we could make different decisions about social openness, even in the absence of a vaccine (however, this may have invasive privacy implications, as tracking this would be quite difficult otherwise).

As we watch the pandemic and its consequences unfold, it becomes clear that leadership and authority are not the same thing. Our hierarchical instincts emerge strongly in times of crisis. Leadership vacuums, then, are devastating, and disasters expose the cracks in our hierarchies. However, we also see that people can display strong leadership without needing any authority. A pandemic provides opportunities for such leadership to emerge at community and local levels, providing alternate pathways for meeting the needs of many.

One critical model we can use to look at society during a pandemic is Ecosystems. When we think about ecosystems, we might imagine a variety of organisms interacting in a forest or the ocean. But our cities are also ecosystems, as is the earth as a whole. Understanding system dynamics can give us a lot of insight into what is happening in our societies, both at the micro and macro level.

One property of ecosystems that is useful to contemplate in situations like a pandemic is resilience—the speed at which an ecosystem recovers after a disturbance. There are many factors that contribute to resilience, such as diversity and adaptability. Looking at our global situation, one factor threatening to undermine our collective resilience is that our economy has rewarded razor-thin efficiency in the recent past. The problem with thin margins is they offer no buffer in the face of disruption. Therefore, ecosystems with thin margins are not at all resilient. Small disturbances can bring them down completely. And a pandemic is not a small disturbance.

Some argue that what we are facing now is a Black Swan: an unpredictable event beyond normal expectations with severe consequences. Most businesses are not ready to face one. You could argue that an economic recession is not a black swan, but the particular shape of this pandemic is testing the resiliency of our social and economic ecosystems regardless. The closing of shops and business, causing huge disruption, has exposed fragile supply chains. We just don’t see these types of events often enough, even if we know they’re theoretically possible. So we don’t prepare for them. We don’t or can’t create big enough personal and social margins of safety. Individuals and businesses don’t have enough money in the bank. We don’t have enough medical facilities and supplies. Instead, we have optimized for a narrow range of possibilities, compromising the resilience of systems we rely on.

Finally, as we look at the role national borders are playing during this pandemic, we can use the Thermodynamics model to gain insight into how to manage flows of people during and after restrictions. Insulation requires a lot of work, as we are seeing with our borders and the subsequent effect on our economies. It’s unsustainable for long periods of time. Just like how two objects of different temperatures that come into contact with each other eventually reach thermal equilibrium, people will mix with each other. All borders have openings of some sort. It’s important to extend planning to incorporate the realistic tendencies of reintegration.

Some final thoughts about the future

As we look for opportunities about how to move forward both as individuals and societies, Cooperation provides a useful lens. Possibly more critical to evolution than competition, cooperation is a powerful force. It’s rampant throughout the biological world; even bacteria cooperate. As a species, we have been cooperating with each other for a long time. All of us have given up some independence for access to resources provided by others.

Pandemics are intensified because of connection. But we can use that same connectivity to mitigate some negative effects by leveraging our community networks to create cooperative interactions that fill gaps in the government response. We can also use the cooperation lens to create more resilient connections in the future.

Finally, we need to ask ourselves how we can improve our antifragility. How can we get to a place where we grow stronger through change and challenge? It’s not about getting “back to normal.” The normal that was our world in 2019 has proven to be fragile. We shouldn’t want to get back to a time when we were unprepared and vulnerable.

Existential threats are a reality of life on earth. One of the best lessons we can learn is to open our eyes and integrate planning for massive change into how we approach our lives. This will not be the last pandemic, no matter how careful we are. The goal now should not be about assigning blame or succumbing to hindsight bias to try to implement rules designed to prevent a similar situation in the future. We will be better off if we make changes aimed at increasing our resilience and embracing the benefits of challenge.

Still curious? Learn more by reading The Great Mental Models.