A new prediction model of infectious diseases with vaccination strategies based on evolutionary game theory. (November 2017) - Li, Qiu; Li, MingChu; Lv, Lin; Guo, Cheng; Lu, Kun
Highlights: We propose a new prediction model of infectious disease with new vaccination strategy based on network structures and dynamic replicator. We consider not only the subsidies of vaccine failure but also the incentive strategy for medical treatment to promote that individuals take the initiative to vaccinate. We consider a new mechanism that we randomly choose an individual from her neighbors and get her strategy, calculate the weighted average value of the benefits of all participants. We use mathematical analysis and Jacobian matrix to show the stability of dynamic equilibrium for our model. Abstract: Infectious diseases have proven to be remarkably resilient foes of human health and so the prevention and control of infectious diseases have been attracting the attention of all countries over the world. Vaccination is an effective way to prevent the spread of infectious diseases. However, vaccination is a long-standing social dilemmas due to the vaccine's risk by itself and the spread of infectious diseases in the population depends on not only the pathogen itself, but also the impact of social network structures. In this paper, we propose a new prediction model of infectious diseases with new vaccination strategies based on network structures and dynamic replicator. In our model, we consider not only the subsidies of vaccine failure but also the incentive strategy for medical treatment to promote individuals to take the initiative to vaccinate. At the same time, in decision-making phase, we use weighted average benefits of all participants to update their strategies due to individual difference. Simulation experiments show that the our proposed model is much effective and better than other existing models. We also use Jacobian matrix to prove the stability of dynamic equilibrium for our proposed model.