Heterogeneous edge weights promote epidemic diffusion in weighted evolving networks
The impact that the heterogeneities of links’ weights have on epidemic diffusion in weighted networks has received much attention. Investigating how heterogeneous edge weights affect epidemic spread is helpful for disease control. In this paper, we study a Reed–Frost epidemic model in weighted evolving networks. Our results indicate that a higher heterogeneity of edge weights leads to higher epidemic prevalence and epidemic incidence at earlier stage of epidemic diffusion in weighted evolving networks. In addition, weighted evolving scale-free networks come with a higher epidemic prevalence and epidemic incidence than unweighted scale-free networks.
Abstract The paper is concerned with a reduced SIR model for migrant workers. By using differential inequality technique and a novel argument, we derive a set of conditions to ensure that the endemic equilibrium of the model is globally exponentially stable. The obtained results complement with some existing ones. We also use numerical simulations to demonstrate the theoretical results.