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.
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Notes
- 1.
In 2 × 2 game s, a defector who is harmful to cooperators is called a first-order free-rider . When a costly punishment scheme for defectors exists, there can be defined a strategy of the masked good guy, who cooperates with others but never punishes defectors; such an individual is called a second-order free-rider . There is much literature on the second-order freerider problem. For example, Olson (1965), Axelrod (1986), Yamagishi (1986).
- 2.
The SIR model is widely applied to infectious diseases, such as influenza and measles. An example can be found in Keeling and Eames (2005).
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Tanimoto, J. (2015). Pandemic Analysis and Evolutionary Games. In: Fundamentals of Evolutionary Game Theory and its Applications. Evolutionary Economics and Social Complexity Science, vol 6. Springer, Tokyo. https://doi.org/10.1007/978-4-431-54962-8_6
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