Abstract for: Optimal Vaccination Policy in the Presence of Behavioral Response

Vaccination policy is often evaluated with epidemic models that assume fixed contact rates. That simplification can mislead policy design because people adjust mobility and social interaction in response to perceived risk. The key question is whether accounting for endogenous behavioral response changes the vaccination coverage, speed, and prioritization needed for effective epidemic control. We compare a conventional SEIRV model with constant contacts to a behavioral SEIRbV model in which recent mortality increases perceived risk and reduces contacts with a delay. Study 1 examines vaccination coverage, rollout speed, and start time in a homogeneous population. Study 2 adds two age groups and makes dose allocation a policy variable. Behavioral feedback changes both threshold estimates and policy rankings. Relative to the fixed-contact model, the behavioral model requires higher coverage and faster rollout to suppress the epidemic. In the age-structured analysis, prioritization still matters, but increasing rollout capacity generally saves more lives than switching between young-first and old-first allocation rules. The findings show that vaccination policy should be evaluated within a feedback-rich behavioral framework rather than with fixed-contact assumptions alone. Endogenous risk response can change both the effort required for epidemic control and the relative value of prioritization versus speed. For policy design, improving rollout capacity may be more important than reallocating limited doses across age groups.