Vaccinating SIS epidemics under evolving perception in heterogeneous networks
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THE EUROPEAN PHYSICAL JOURNAL B
Regular Article
Vaccinating SIS epidemics under evolving perception in heterogeneous networks Xiao-Jie Li 1 and Xiang Li 1,2,3,a 1
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Adaptive Networks and Control Lab, Department of Electronic Engineering – Fudan University, Shanghai 200433, P.R. China Research Center of Smart Networks and Systems, School of Information Science and Engineering – Fudan University, Shanghai 200433, P.R. China MOE Frontiers Center for Brain Science, Institutes of Brain Science – Fudan University, Shanghai 200433, P.R. China Received 13 July 2020 / Received in final form 10 August 2020 / Accepted 20 August 2020 Published online 5 October 2020 c EDP Sciences / Societ`
a Italiana di Fisica / Springer-Verlag GmbH Germany, part of Springer Nature, 2020 Abstract. Vaccination is an effective intervention against epidemics. Previous work has demonstrated that psychological cognition affects individual behavior. However, perceptual differences between individuals, as well as the dynamics of perceptual evolution, are not taken into account. In order to explore how these realistic characteristics of psychological cognition influence collective vaccination behavior, we propose a prospect theory based evolutionary vaccination game model, where the evolution of reference points is used to characterize changes in perception. We compare the fractions of vaccinated individuals and infected individuals under variable reference points with those under the expected utility theory and the fixed reference point, and highlight the role of evolving perception in promoting vaccination and contributing to epidemic control. We find that the epidemic size under variable reference point is always less than that under the expected utility theory. Finding that there exists a vaccination cost threshold for the cognitive effect, we develop a novel mixed-reference-point mechanism by combining individual psychological characteristics with network topological feature. The effectiveness of this mechanism in controlling the network epidemics is verified with numerical simulations. Compared with pure reference points, the mixed-reference-point mechanism can effectively reduce the final epidemic size, especially at a large vaccination cost.
1 Introduction The outbreak of the COVID-19 epidemic has not only threatened public health but also seriously influenced almost every facet of lives [1]. Developing effective vaccines is the only long-term solution to this epidemic [2]. Since a vaccinated individual can not only protect himself from being infected but also his unvaccinated neighbors, vaccination can be regarded as an altruistic cooperative behavior. However, self-interested individuals expect to benefit from the vaccination behavior of others, which leads to vaccination being a social dilemma [3,4]. Wang et al. [5] and Perc et al. [6] reviewed rich researches on studying the complex interactions between vaccination behavior and epidemic dynamics. Moreover, many studies [7–12] have explored the factors that affect individual vaccin
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