Optimal two-phase vaccine allocation to geographically different regions under uncertainty

• A two-phase vaccination policy is proposed and compared to the continuous vaccination policy.
• Some easy to implement heuristics for vaccine allocation are proposed and evaluated.
• Evaluation of vaccination outcome in a two-phase vaccination policy might considerably reduce vaccination cost.
• Early vaccination (as the first phase of a two-phase vaccination policy) considerably reduces the disease attack rate.
• Information about the disease progression in larger regions is more valuable than smaller regions.

In this article, we consider a decision process in which vaccination is performed in two phases to contain the outbreak of an infectious disease in a set of geographic regions. In the first phase, a limited number of vaccine doses are allocated to each region; in the second phase, additional doses may be allocated to regions in which the epidemic has not been contained. We develop a simulation model to capture the epidemic dynamics in each region for different vaccination levels. We formulate the vaccine allocation problem as a two-stage stochastic linear program (2-SLP) and use the special problem structure to reduce it to a linear program with a similar size to that of the first stage problem. We also present a Newsvendor model formulation of the problem which provides a closed form solution for the optimal allocation. We construct test cases motivated by vaccine planning for seasonal influenza in the state of North Carolina. Using the 2-SLP formulation, we estimate the value of the stochastic solution and the expected value of perfect information. We also propose and test an easy to implement heuristic for vaccine allocation. We show that our proposed two-phase vaccination policy potentially results in a lower attack rate and a considerable saving in vaccine production and administration cost.