Temporal Vaccination Games under Resource Constraints

Authors

  • Abhijin Adiga Virginia Polytechnic Institute and State University
  • Anil Vullikanti Virginia Polytechnic Institute and State University

DOI:

https://doi.org/10.1609/aaai.v30i1.10137

Keywords:

vaccination games, disease spread, social optimum, best response strategy

Abstract

The decision to take vaccinations and other protective interventions for avoiding an infection is a natural game-theoretic setting. Most of the work on vaccination games has focused on decisions at the start of an epidemic. However, a lot of people defer their vaccination decisions, in practice. For example, in the case of the seasonal flu, vaccination rates gradually increase, as the epidemic rate increases. This motivates the study of temporal vaccination games, in which vaccination decisions can be made more than once. An important issue in the context of temporal decisions is that of resource limitations, which may arise due to production and distribution constraints. While there has been some work on temporal vaccination games, resource constraints have not been considered. In this paper, we study temporal vaccination games for epidemics in the SI (susceptible-infectious) model, with resource constraints in the form of a repeated game in complex social networks, with budgets on the number of vaccines that can be taken at any time. We find that the resource constraints and the vaccination and infection costs have a significant impact on the structure of Nash equilibria (NE). In general, the budget constraints can cause NE to become very inefficient, and finding efficient NE as well as the social optimum are NP-hard problems. We develop algorithms for finding NE and approximating the social optimum. We evaluate our results using simulations on different kinds of networks.

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Published

2016-03-03

How to Cite

Adiga, A., & Vullikanti, A. (2016). Temporal Vaccination Games under Resource Constraints. Proceedings of the AAAI Conference on Artificial Intelligence, 30(1). https://doi.org/10.1609/aaai.v30i1.10137

Issue

Section

Technical Papers: Multiagent Systems