Second, there is a certain logic to the idea that you might choose to give up entirely on trying to slow or contain a virus and, instead, choose a point like E where you have the economy you had before but with much lower public health (and also fewer people surviving). The logic here is that it is really, really hard to preserve public health because the economy really has to suffer. Of course, the same logic applies to a point like H. If you want to preserve public health (save lives), you have to accept that you will harm the economy in a large way. In other words, the bite forces us into a big either/or situation—that is, a choice between H and E.
Figure 1.3a as it is drawn assumes that we can achieve the same level of economic performance even if we have low public health. That is potentially very unrealistic. If we let a pandemic run its course without mitigation, that lowers economic activity and leads to a “dark recession” as depicted in figure 1.3b. If this is the case, you can see that a point like E will be far less desirable than H.
The drift can also be represented using PPFs. This is done in figure 1.4. Figure 1.4a shows what happens if you do not hold the line on public health to keep it at its previous levels. You will see that option no longer is viable and lies outside the moving pandemic PPF. Figure 1.4b shows what happens if you try to maintain the previous economy level and delay too long on social distancing. In this case, the PPF has a cliff and it is no longer possible to control the pandemic after a time.
Figure 1.4
The drift. (a) The PPF moves. (b) The cliff.
There are two final things worth demonstrating using the pandemic PPFs. First, figure 1.5 shows what happens if you hold the line on public health but do not institute the type of macroeconomic policy “life support” mechanisms that allow you to pause the economy. As will be discussed in chapter 4, introducing those mechanisms can improve the economy along with maintaining public health as you move from a point, like B, within the PPF to the frontier itself.
The economist Eric Budish observed that it is very important to consider the correct mindset when thinking about how to reach the frontier.14 In particular, if you have a mindset that focuses solely on reducing the infection rate as quickly as possible, this will not necessarily get you to the frontier. Instead, that frontier involves targeting an infection rate that stops the pandemic15 but, otherwise, picking allowable activities that reflect both their value for the economy and their risk in terms of public health.
Figure 1.5
Supportive macroeconomic policy.
Second, there are some innovations and investments that can be made that will improve the pandemic PPF. In chapter 5, I describe the use of tests to make interacting physically safe again. This has the effect—shown in figure 1.6—of expanding the production possibilities set. This makes H more desirable. However, it is useful to note that such innovations and investments are of no value if you decide to move to a point like E. Thus, the key reason you may want to hold the line on health is to provide breathing space for the reset phase to be prepared for and then conducted.
Figure 1.6
Impact of testing.
Key Points
1. The way in which COVID-19 propagates through the population means that there is a stark choice between maintaining economic activity and public health.
2. If governments choose not to hold the line on public health, there is no going back. It is, therefore, economically sensible to prioritize public health during a pandemic in order to learn more about the ways in which the pandemic can be managed.
3. In dealing with the pandemic, because of delays in taking action, governments must first contain the outbreak in order to then put themselves in a position to reset and conduct recovery policies—such as testing and tracing and innovations in treatment and prevention—in order to bring the crisis to a resolution.
4. Attention must then turn to developing institutions and global coordinated responses to deal with future pandemics in a more timely and effective manner than is currently being done for COVID-19.
2
Predictable Surprises
It starts with a grain of rice on a chessboard. This is grain one. The craftsperson makes an offer to the monarch. “I have made this beautiful chessboard and I will give it to you for some more rice. I have placed a grain on the first square. I want you to add grains to each of the remaining squares in turn, doubling each time. Two on the next one. Four on the one after that and so on until all 64 squares have been covered.” The monarch feels they can spot a good deal and so accepts the offer.1
Suffice it to say, it was not a good deal, and accepting it would surely bankrupt the monarch’s land. The reason why it is bad is that it is very clear what is going on and only a lack of willingness to do the math would allow you to think otherwise. Put simply, the total amount of rice being asked for was not some mystery. It was the solution to this equation:
1 + 2 + 4 + … + 9,233,372,036,854,775,808 = 18,446,744,073,709,551,615
That, it turns out, is a lot of rice. If you laid the grains end to end you would go from the Earth to Alpha Centauri and back twice.2 Ultimately, there isn’t enough rice in the world, let alone the land, to pay out the contract. I’m no lawyer, so I have no idea what the outcome of this would have been had it ended up in the courts.
Obviously, this fable isn’t about contract law; it is about our ability to use mathematics to understand the world around us. If you base your decisions on what you can see with little effort, then you might miss the underlying processes at work. Alternatively, if you understand the underlying processes and see them to their ultimate conclusion, you will make a better decision. Those conclusions may be surprising, but, paradoxically, they are predictable.
The COVID-19 pandemic came as a predictable surprise to most people. While the mathematics are not as clear as the rice and the chessboard, they were present, and the same disconnect between what you could see immediately and what the math told you about where this was heading was there. The tough challenge was how to make some very costly decisions based on the mathematics alone.
The Degree of the Problem
Pandemics are better than a rice/chessboard process in a very important way: once the first grain of rice is placed, there are ways to stop the process before square 64 is reached. The key to any mitigation strategy that modifies the mathematics of that process is a willingness make that break.
Before getting to that, it is worthwhile to review the mathematics. When a person contracts an infectious virus, they can pass it to others by contact. This isn’t true of all viruses nor of all infectious diseases, but, at the time of writing, this is the most plausible infection path for the novel coronavirus. Sometime in November 2019, someone contracted the virus and began passing it on to others. The question was: How many others? The question pertains not only to that person but, more important, to any random person who might carry the virus.
In epidemiology this has a number, R0, or the basic reproduction number. R0 is the expected number of people one infectious person is likely to infect with a particular virus at the outset.3 In the past, with enough knowledge, R0 for other viruses or infectious diseases could be measured. Absent any interventions, the critical threshold number is 1. If each infected person infects at most one other person, then the total number of infections might rise initially but will progress very slowly, and, because eventually you are meeting more and more people who have had the virus and are, hopefully, immune, the infection rate will die off fairly quickly. For an R0 > 1, an epidemic is possible, with a much higher share of the population likely to become infected. This is why the number-one goal in pandemic management is to create conditions so that the basic reproduction number is moved to less than 1.