Robust oscillations in SIS epidemics on adaptive networks: Coarse graining by automated moment closure

¹  Department of Chemical Engineering, Princeton University - Princeton, NJ 08544, USA
²  Max-Planck Institute für Physik komplexer Systeme - Nöthnitzer Straße 38, 01187 Dresden, Germany, EU
³  Department of Chemical Engineering and PACM, Princeton University - Princeton, NJ 08544, USA

Corresponding authors: thilo.gross@physics.org yannis@princeton.edu

Received: 4 January 2008
Accepted: 19 March 2008

Abstract

We investigate the dynamics of an epidemiological susceptible-infected-susceptible (SIS) model on an adaptive network. This model combines epidemic spreading (dynamics on the network) with rewiring of network connections (topological evolution of the network). We propose and implement a computational approach that enables us to study the dynamics of the network directly on an emergent, coarse-grained level. The approach sidesteps the derivation of closed low-dimensional approximations. Our investigations reveal that global coupling, which enters through the awareness of the population to the disease, can result in robust large-amplitude oscillations of the state and topology of the network.