Epidemic reemergence in adaptive complex networks

Abstract

The dynamic nature of system gives rise to dynamical features of epidemic spreading, such as oscillation and bistability. In this paper, by studying the epidemic spreading in growing networks, in which susceptible nodes may adaptively break the connections with infected ones yet avoid getting isolated, we reveal a new phenomenon - \emph{epidemic reemergence}, where the number of infected nodes is incubated at a low level for a long time and then bursts up for a short time. The process may repeat several times before the infection finally vanishes. Simulation results show that all the three factors, namely the network growth, the connection breaking and the isolation avoidance, are necessary for epidemic reemergence to happen. We present a simple theoretical analysis to explain the process of reemergence in detail. Our study may offer some useful insights helping explain the phenomenon of repeated epidemic explosions.

8 pages, 10 figures

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• Link-based formalism for time evolution of adaptive networks
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• Oscillating epidemics in a dynamic network model: stochastic and mean-field analysis