Optimal Capacity-Constrained COVID-19 Vaccination for Heterogeneous Populations.

COVID-19 and the ensuing vaccine capacity constraints have emphasized the importance of proper prioritization during vaccine rollout. This problem is complicated by heterogeneity in risk levels, contact rates, and network topology which can dramatically and unintuitively change the efficacy of vaccination and must be taken into account when allocating resources. This paper proposes a general model to capture a wide array of network heterogeneity while maintaining computational tractability and formulates vaccine prioritization as an optimal control problem. Pontryagin's Maximum Principle is used to derive properties of optimal, potentially highly dynamic, allocation policies, providing significant reductions in the set of candidate policies. Extensive numerical simulations of COVID-19 vaccination are used to corroborate these findings and further illicit optimal policy characteristics and the effects of various system, disease, and population parameters.