Regular Article

Vaccinating SIS epidemics under evolving perception in heterogeneous networks

¹ Adaptive Networks and Control Lab, Department of Electronic Engineering – Fudan University, Shanghai 200433, P.R. China
² Research Center of Smart Networks and Systems, School of Information Science and Engineering – Fudan University, Shanghai 200433, P.R. China
³ MOE Frontiers Center for Brain Science, Institutes of Brain Science – Fudan University, Shanghai 200433, P.R. China

^a e-mail: lix@fudan.edu.cn

Received: 13 July 2020
Received in final form: 10 August 2020
Accepted: 20 August 2020
Published online: 5 October 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.