Dynamics of infectious disease in clustered networks with arbitrary degree distributions - Quantitative Biology > Quantitative MethodsReport as inadecuate




Dynamics of infectious disease in clustered networks with arbitrary degree distributions - Quantitative Biology > Quantitative Methods - Download this document for free, or read online. Document in PDF available to download.

Abstract: We investigate the effects of heterogeneous and clustered contact patterns onthe timescale and final size of infectious disease epidemics. The abundance oftransitive relationships the number of 3 cliques in a network and thevariance of the degree distribution are shown to have large effects on thenumber ultimately infected and how quickly the epidemic propagates. The networkmodel is based on a simple generalization of the configuration model, andepidemic dynamics are modeled with a low dimensional system of ordinarydifferential equations. Because of the simplicity of this model, we are able toexplore a large parameter space and characterize dynamics over a wide range ofnetwork topologies. We find that the interaction between clustering and thedegree distribution is complex, and that clustering always slows down anepidemic, but that simultaneously increasing clustering and variance of thedegree distribution can potentially increase final epidemic size. In contrastto solutions for unclustered configuration model networks, we find that bondpercolation solutions for the final epidemic size are potentially biased ifthey do not take variable infectious periods into account.



Author: Erik M Volz

Source: https://arxiv.org/







Related documents