Abstract
The spreading processes of many infectious diseases have comparable time scale as the network evolution. Here, we present a simple networks model with time-varying community structure, and investigate susceptible-infected-susceptible epidemic spreading processes in this model. By both theoretic analysis and numerical simulations, we show that the efficiency of epidemic spreading in this model depends intensively on the mobility rate q of the individuals among communities. We also find that there exists a mobility rate threshold qc. The epidemic will survive when q > qc and die when q < qc. These results can help understanding the impacts of human travel on the epidemic spreading in complex networks with community structure.
Highlights
INTRODUCTIONTuberculosis, foot and mouth disease among cattle, and various sexually transmitted infections
In recent years, there have been extensive research activities on time-varying networks, or called temporal networks, which evolve on a time scale comparable to the time scale of the propagation process.10–12 An additional time dimension is considered in time-varying networks
We propose a network model with time-varying community structure
Summary
Tuberculosis, foot and mouth disease among cattle, and various sexually transmitted infections.. Starnini et al have investigated the immunization strategies for epidemic processes in time-varying contact networks.. Starnini et al have investigated the immunization strategies for epidemic processes in time-varying contact networks.14 All these investigations indicate that time-varying networks play an important role in the investigation of the epidemic spreading that occurs on complex networks. The community structure in complex networks has considerable influences on the epidemic spreading processes. Despite all these efforts, the impact of time-varying community networks evolution on epidemic spreading has not been well considered. We present a simple networks model with time-varying community structure, and investigate SIS epidemic spreading processes in this model.
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