Real-time growth rate for general stochastic SIR epidemics on unclustered networks
Author(s)
Pellis, L
Spencer, SEF
House, T
Type
Journal Article
Abstract
Networks have become an important tool for infectious disease epidemiology. Most previous theoretical studies of transmission network models have either considered simple Markovian dynamics at the individual level, or have focused on the invasion threshold and final outcome of the epidemic. Here, we provide a general theory for early real-time behaviour of epidemics on large configuration model networks (i.e. static and locally unclustered), in particular focusing on the computation of the Malthusian parameter that describes the early exponential epidemic growth. Analytical, numerical and Monte-Carlo methods under a wide variety of Markovian and non-Markovian assumptions about the infectivity profile are presented. Numerous examples provide explicit quantification of the impact of the network structure on the temporal dynamics of the spread of infection and provide a benchmark for validating results of large scale simulations.
Date Issued
2015-04-24
Date Acceptance
2015-04-16
Citation
Mathematical Biosciences, 2015, 265, pp.65-81
ISSN
0025-5564
Publisher
Elsevier
Start Page
65
End Page
81
Journal / Book Title
Mathematical Biosciences
Volume
265
Copyright Statement
© 2015, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/
Subjects
Epidemic
Malthusian parameter
Basic reproduction number
Configuration model
Branching process
Publication Status
Published