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Pandemic Analysis and Evolutionary Games

  • Jun Tanimoto
Part of the Evolutionary Economics and Social Complexity Science book series (EESCS, volume 6)

Abstract

Human social networks are a central theme to which evolutionary game theory has been applied because the complexity of the underlying network serves as the key factor in determining game equilibrium. The spread of an epidemic throughout such a network is mathematically described by percolation theory, which is an archetype of the physics of diffusion processes. Vaccination, which is driven by individual decision making, inhibits the spread of infectious diseases. In addition, if the so-called herd immunity is established, a free-rider, who pays no cost for vaccination, can escape infection. Obviously, there is a conflict between individual and social benefits; in short, a conflict between individual rational choices: trying to avoid vaccination, or everyone taking the vaccine achieving the fair Pareto optimum. This conflict is why we introduce evolutionary game theory into epidemiology; vaccination can be viewed as a game in a complex social network. In this chapter, we examine pandemic analysis as another application to which evolutionary game theory can be applied.

Keywords

Nash Equilibrium Vaccination Coverage Vaccination Rate Cooperative Strategy Average Path Length 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Japan 2015

Authors and Affiliations

  • Jun Tanimoto
    • 1
  1. 1.Graduate School of Engineering SciencesKyushu University InterdisciplinaryFukuokaJapan

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