Dynamic vaccination games and variational inequalities on time-dependent sets

Abstract

This paper presents a model of a dynamic vaccination game in a population consisting of a collection of groups, each of which holds distinct perceptions of vaccinating versus non-vaccinating risks. Vaccination is regarded here as a game due to the fact that the payoff to each population group depends on the so-called perceived probability of getting infected given a certain level of the vaccine coverage in the population, a level that is generally obtained by the vaccinating decisions of other members of a population. The novelty of this model resides in the fact that it describes a repeated vaccination game (over a finite time horizon) of population groups whose sizes vary with time. In particular, the dynamic game is proven to have solutions using a parametric variational inequality approach often employed in optimization and network equilibrium problems. Moreover, the model does not make any assumptions upon the level of the vaccine coverage in the population, but rather computes this level as a final result. This model could then be used to compute possible vaccine coverage scenarios in a population, given information about its heterogeneity with respect to perceived vaccine risks. In support of the model, some theoretical results were advanced (presented in the appendix) to ensure that computation of optimal vaccination strategies can take place; this means, the theory states the existence, uniqueness and regularity (in our case piecewise continuity) of the solution curves representing the evolution of optimal vaccination strategies of each population group.