Effect of Small-World Networks on Epidemic Propagation and Intervention

The small-world network, characterized by special structural properties of high connectivity and clustering, is one of the highlights in recent advances in network science and has the potential to model a variety of social contact networks. In an attempt to better understand how these structural properties of small-world networks affect epidemic propagation and intervention, this article uses an agent-based approach to investigate the interplay between an epidemic process and its underlying network structure. Small-world networks are derived from a network ‘‘rewiring’’ process, which readjusts edges in a completely regular two-dimensional network by different rewiring probabilities (0–1) to produce a spectrum of modified networks on which an agent-based simulation of epidemic propagation can be conducted. A comparison of simulated epidemics discloses the effect of small-world networks on epidemic propagation as well as the effectiveness of different intervention strategies, including mass vaccination, acquaintance vaccination, targeted vaccination, and contact tracing. Epidemics taking place on small-world networks tend to reach large-scale epidemic peaks within a short time period. Among the four intervention strategies tested, only one strategy—the targeted vaccination—proves to be effective for containing epidemics, a finding supported by a simulation of the severe acute respiratory syndrome epidemic in a large-scale realistic social contact network in Portland, OR.