The Uncertainty of Models

And why they are still important!

A good article exploring the uncertainty of all the models out there… and how to act in the face of that uncertainty. The title might make you think that the author is dismissing models — they are not.

The problem is that there are many unknown factors, and that our actions (thankfully!) can change the outcome. The conundrum inherent in that is “When an epidemiological model is believed and acted on, it can look like it was false.” That is to say it can look like our draconian action was for nothing — similar to when a hurricane bears down on some coast but then fizzles to nothing… why all the drama.

But here in this moment we can clearly see the costs of actions.

Despite starting from very similar points, Lombardy is now tragically overrun with the disease, having experienced roughly 7,000 deaths and counting, while Veneto has managed to mostly contain the epidemic to a few hundred fatalities. Similarly, South Korea and the United States had their first case diagnosed on the same day, but South Korea undertook massive tracing and testing, and the United States did not. Now South Korea has only 162 deaths, and an outbreak that seems to have leveled off, while the U.S. is approaching 4,000 deaths as the virus’s spread accelerates.

So what do these uncertain models provide us? “Epidemiology gives us something more important: agency to identify and calibrate our actions with the goal of shaping our future.”

Don’t Believe the COVID-19 Models — That’s not what they’re for.