title: Epidemics in interconnected small-world networks.
abstract: Networks can be used to describe the interconnections among individuals, which play an important role in the spread of disease. Although the small-world effect has been found to have a significant impact on epidemics in single networks, the small-world effect on epidemics in interconnected networks has rarely been considered. Here, we study the susceptible-infected-susceptible (SIS) model of epidemic spreading in a system comprising two interconnected small-world networks. We find that the epidemic threshold in such networks decreases when the rewiring probability of the component small-world networks increases. When the infection rate is low, the rewiring probability affects the global steady-state infection density, whereas when the infection rate is high, the infection density is insensitive to the rewiring probability. Moreover, epidemics in interconnected small-world networks are found to spread at different velocities that depend on the rewiring probability.
authors: School of Reliability and Systems Engineering, Beihang University, Beijing, China; Science and Technology on Reliability and Environmental Engineering Laboratory, Beijing, China.
authors: Meng
authors: M
authors: Liu
authors: School of Reliability and Systems Engineering, Beihang University, Beijing, China; Science and Technology on Reliability and Environmental Engineering Laboratory, Beijing, China.
authors: Daqing
authors: D
authors: Li
authors: School of Reliability and Systems Engineering, Beihang University, Beijing, China; Science and Technology on Reliability and Environmental Engineering Laboratory, Beijing, China.
authors: Pengju
authors: P
authors: Qin
authors: School of Reliability and Systems Engineering, Beihang University, Beijing, China; Science and Technology on Reliability and Environmental Engineering Laboratory, Beijing, China.
authors: Chaoran
authors: C
authors: Liu
authors: Faculty of Electrical Engineering, Mathematics, and Computer Science, Delft University of Technology, Delft, The Netherlands.
authors: Huijuan
authors: H
authors: Wang
authors: School of Reliability and Systems Engineering, Beihang University, Beijing, China; Science and Technology on Reliability and Environmental Engineering Laboratory, Beijing, China.
authors: Feilong
authors: F
authors: Wang
mesh_terms: D000465:Algorithms; D058872:Epidemics; D006801:Humans; D008962:Models, Theoretical; D016571:Neural Networks, Computer