Epidemic reemergence in adaptive complex networks

TL;DR

This paper investigates how epidemic reemergence occurs in adaptive growing networks, revealing that network growth, connection breaking, and isolation avoidance collectively lead to repeated epidemic bursts, with implications for understanding epidemic dynamics.

Contribution

The study introduces the concept of epidemic reemergence in adaptive networks and demonstrates its dependence on network growth, adaptive connection breaking, and isolation avoidance.

Findings

Epidemic reemergence involves long incubation and burst phases.

All three factors—growth, breaking, and avoidance—are necessary for reemergence.

Theoretical analysis explains the reemergence process in detail.

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.