title: Effects of behavioral response and vaccination policy on epidemic spreading--an approach based on evolutionary-game dynamics.
abstract: How effective are governmental incentives to achieve widespread vaccination coverage so as to prevent epidemic outbreak? The answer largely depends on the complex interplay among the type of incentive, individual behavioral responses, and the intrinsic epidemic dynamics. By incorporating evolutionary games into epidemic dynamics, we investigate the effects of two types of incentives strategies: partial-subsidy policy in which certain fraction of the cost of vaccination is offset, and free-subsidy policy in which donees are randomly selected and vaccinated at no cost. Through mean-field analysis and computations, we find that, under the partial-subsidy policy, the vaccination coverage depends monotonically on the sensitivity of individuals to payoff difference, but the dependence is non-monotonous for the free-subsidy policy. Due to the role models of the donees for relatively irrational individuals and the unchanged strategies of the donees for rational individuals, the free-subsidy policy can in general lead to higher vaccination coverage. Our findings indicate that any disease-control policy should be exercised with extreme care: its success depends on the complex interplay among the intrinsic mathematical rules of epidemic spreading, governmental policies, and behavioral responses of individuals.
authors.affiliation: 1] School of Mathematical Science, Anhui University, Hefei 230039, P. R. China [2] School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, Arizona 85287, USA [3] Department of Communication Engineering, North University of China, Taiyuan, Shan'xi 030051, P. R. China.
authors.forename: Hai-Feng
authors.initials: HF
authors.lastname: Zhang
authors.affiliation: Institute of Computational Physics and Complex Systems, Lanzhou University, Lanzhou 730000, China.
authors.forename: Zhi-Xi
authors.initials: ZX
authors.lastname: Wu
authors.affiliation: Web Sciences Center, University of Electronic Science and Technology of China, Chengdu 611731, China.
authors.forename: Ming
authors.initials: M
authors.lastname: Tang
authors.affiliation: School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, Arizona 85287, USA.
authors.forename: Ying-Cheng
authors.initials: YC
authors.lastname: Lai
mesh_terms: D004196:Disease Outbreaks / Q000517:prevention & control; D058872:Epidemics / Q000517:prevention & control*; D005716:Game Theory; D006801:Humans; D008962:Models, Theoretical; D014611:Vaccination / Q000331:legislation & jurisprudence*