Which COVID-19 models are right, and which are wrong? We don’t know, that’s fine. Because as Zeynep Tufekci writes in The Atlantic today, “right answers are not what epidemiological models are for”.
Tufekci, an associate professor at the University of North Carolina and faculty associate at the Harvard Berkman Klein Center for Internet and Society, writes in The Atlantic:
The Trump administration has just released the model for the trajectory of the COVID-19 pandemic in America. We can expect a lot of back-and-forth about whether its mortality estimates are too high or low. And its wide range of possible outcomes is certainly confusing: What’s the right number? The answer is both difficult and simple. Here’s the difficult part: There is no right answer. But here’s the simple part: Right answers are not what epidemiological models are for.
With this novel coronavirus, there are a lot of things we don’t know because we’ve never tested our models, and we have no way to do so.
So if epidemiological models don’t give us certainty—and asking them to do so would be a big mistake—what good are they? Epidemiology gives us something more important: agency to identify and calibrate our actions with the goal of shaping our future. We can do this by pruning catastrophic branches of a tree of possibilities that lies before us.
Epidemiological models have “tails”—the extreme ends of the probability spectrum. They’re called tails because, visually, they are the parts of the graph that taper into the distance. Think of those tails as branches in a decision tree. In most scenarios, we end up somewhere in the middle of the tree—the big bulge of highly probable outcomes—but there are a few branches on the far right and the far left that represent fairly optimistic and fairly pessimistic, but less likely, outcomes.
The most important function of epidemiological models is as a simulation, a way to see our potential futures ahead of time, and how that interacts with the choices we make today. With COVID-19 models, we have one simple, urgent goal: to ignore all the optimistic branches and that thick trunk in the middle representing the most likely outcomes. Instead, we need to focus on the branches representing the worst outcomes, and prune them with all our might. Social isolation reduces transmission, and slows the spread of the disease. In doing so, it chops off branches that represent some of the worst futures. Contact tracing catches people before they infect others, pruning more branches that represent unchecked catastrophes.