Modeling social response to disease spread using spatial game theory

Abstract

Epidemic disease outbreaks are among the major threats to the sustenance and health of human societies. Many reports in public health show that even with the current state of prevention and treatment technologies, epidemic diseases still cause severe health issues and loss of life, and hence remain a source of large public health cost on societies. Consequently, controlling the spread of infectious diseases has become a main area of focus for public health policy makers. Modeling the dynamics of epidemic disease outbreaks and the corresponding social response is one of the techniques that can help public health policy makers to better design and evaluate relevant policies with more precise and detailed knowledge of such dynamics in social interactions and self-organization. Accordingly, we propose a modeling approach based on spatial game theory using public goods game, which is a prominent approach for capturing the behavior of individuals in response to local stimuli. The settings of public goods game enable this method to model the dilemma of not vaccinating and not paying the related costs of vaccination or vaccinating to provide a healthy living environment for the individual and other members of the community. This is the first time that a public goods game payoff function is used in modeling and capturing the behavior of populations in response to epidemics. In this dissertation, two variants of the proposed model are introduced. The first captures the behavior of individuals in response to an epidemic, in which decision making is on whether to vaccinate or not. The second model aims to capture the behavior of interacting populations to an epidemic, and the decision is on how much to change the level of vaccination in each population. Also, the impact of considering the time-delay between infection and emergence of symptoms of the disease is studied. These models demonstrate that the adoption of public goods game based payoff function in the modeling of epidemics can capture the vaccination behavior of individuals, and can lead to a better control of the epidemic spread in the population level. Moreover, this dissertation proposes two new strategy updating methods in spatial evolutionary games, which are shown to be capable of modeling the dynamics of decision making under different sensitivities to vaccination and fear of infection.