Stabilizing the return to normal behavior in an epidemic

Predicting the interplay between infectious disease and behavior has been an intractable problem because behavioral response is so varied. We introduce a general framework for feedback between incidence and behavior for an infectious disease. By identifying stable equilibria, we provide policy end-states that are self-managing and self-maintaining. We prove mathematically the existence of two new endemic equilibria depending on the vaccination rate: one in the presence of low vaccination but with reduced societal activity (the “new normal”), and one with return to normal activity but with vaccination rate below that required for disease elimination. This framework allows us to anticipate the long-term consequence of an emerging disease and design a vaccination response that optimizes public health and limits societal consequences. Significance Statement The experience of the COVID-19 pandemic has revealed that behavior can change dramatically in response to the spread of a disease. This behavioral response impacts disease transmission. Predicting future outcomes requires accounting for the feedback between behavior and transmission. We show that accounting for these feedbacks generates long-term predictions about disease burden and behavior that can guide policy.