Population-level behavioral and structural drivers of COVID-19 vaccine uptake in the US

Substantial variation in COVID-19 vaccination trends across U.S. communities raises key questions about the factors that shape vaccination uptake. We develop a dynamic simulation model that captures population-driven feedback processes, from social influence and uptake heterogeneity to fear of infection, responses to vaccine availability, and capacity constraints. To estimate behavioral parameters, we derive an ordinary differential equation (ODE)-informed Tobit regression framework and apply it to weekly vaccination data from all 50 US states and the District of Columbia during 2021-2022. The resulting estimates provide a robust empirical foundation for model calibration. The calibrated model reproduces observed regional vaccination trajectories and reveals three distinct phases of uptake: an early phase in which capacity and eligibility constraints bind on the underlying demand, a middle phase in which behavioral responses to changing COVID-19 incidence shape the fluctuations in uptake, with rising case numbers stimulating additional vaccination; and a late phase shaped by saturation dynamics. Finally, we document substantial regional heterogeneity in responsiveness to infection risk and the overall tendency to vaccinate when capacity permits.