Effects of community structure on epidemic spread in an adaptive network

Abstract

When an epidemic spreads in a population, individuals may adaptively change the structure of their social contact network to reduce risk of infection. Here we study the spread of an epidemic on an adaptive network with community structure. We model two communities with different average degrees. The disease model is susceptible-infected-susceptible (SIS), and adaptation is rewiring of links between susceptibles and infectives. Locations of rewired links are selected so that the community structure will be preserved if susceptible-infective links are homogeneously distributed. The bifurcation structure is obtained, and a mean field model is developed that accurately predicts the steady-state behavior of the system. In a static network, weakly connected heterogeneous communities can have significantly different infection levels. In contrast, adaptation promotes similar infection levels and alters the network structure so that communities have more similar average degrees. We estimate the time for network restructuring to allow infection incursion from one community to another and show that it is inversely proportional to the number of cross-links between communities. In extremely heterogeneous systems, periodic oscillations in infection level can occur due to repeated infection incursions.