title: Interplay between the local information based behavioral responses and the epidemic spreading in complex networks.
abstract: The spreading of an infectious disease can trigger human behavior responses to the disease, which in turn plays a crucial role on the spreading of epidemic. In this study, to illustrate the impacts of the human behavioral responses, a new class of individuals, S(F), is introduced to the classical susceptible-infected-recovered model. In the model, S(F) state represents that susceptible individuals who take self-initiate protective measures to lower the probability of being infected, and a susceptible individual may go to S(F) state with a response rate when contacting an infectious neighbor. Via the percolation method, the theoretical formulas for the epidemic threshold as well as the prevalence of epidemic are derived. Our finding indicates that, with the increasing of the response rate, the epidemic threshold is enhanced and the prevalence of epidemic is reduced. The analytical results are also verified by the numerical simulations. In addition, we demonstrate that, because the mean field method neglects the dynamic correlations, a wrong result based on the mean field method is obtained-the epidemic threshold is not related to the response rate, i.e., the additional S(F) state has no impact on the epidemic threshold.
authors.affiliation: School of Mathematical Science, Anhui University, Hefei 230601, People's Republic of China.
authors.forename: Can
authors.initials: C
authors.lastname: Liu
authors.affiliation: Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China.
authors.forename: Jia-Rong
authors.initials: JR
authors.lastname: Xie
authors.affiliation: School of Physics and Material Science, Anhui University, Hefei 230601, China.
authors.forename: Han-Shuang
authors.initials: HS
authors.lastname: Chen
authors.affiliation: School of Mathematical Science, Anhui University, Hefei 230601, People's Republic of China.
authors.forename: Hai-Feng
authors.initials: HF
authors.lastname: Zhang
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
mesh_terms: D003141:Communicable Diseases / Q000453:epidemiology* / Q000635:transmission*; D058872:Epidemics; D006801:Humans; D008954:Models, Biological; D012919:Social Behavior