An epidemic is not just a virus: it's millions of personal decisions. One person keeps riding the subway; another locks themselves at home. Classical models describe the average behavior of a crowd but don't ask why each individual acts that way. The new work adds game theory to epidemiology: each participant is a player who chooses how many contacts to allow, keeping an eye on their own protection and on what's happening around them.
The main challenge is invisible immunity. A person may retain protection after an illness, but it fades over time. Or it vanishes in an instant, like a light switching off, and the person becomes vulnerable again without even realizing it. The model accounts for this: each player knows their current level of protection if it's visible, or acts blindly if it's not. To compute such scenarios, the authors reduced complex equations to a system solvable on an ordinary computer, and showed that the method works even with an uncertain planning horizon.
This approach isn't just for epidemics. It applies to any situation where people make decisions that affect collective risk, from financial bubbles to traffic. When everyone acts rationally but in their own way, the collective picture can surprise you.
If immunity vanishes instantly and silently, a person may think they're protected when they're actually vulnerable, like a driver whose brakes have failed but the dashboard warning light doesn't come on.
This model echoes storylines where characters must make decisions during an epidemic without knowing for sure who's infected, like in the film Contagion or the series The Walking Dead.