Consistent approximation of epidemic dynamics on degree-heterogeneous clustered networks

Bishop, A, Kiss, I Z and House, T (2019) Consistent approximation of epidemic dynamics on degree-heterogeneous clustered networks. COMPLEX NETWORKS 2018 The 7th International Conference on Complex Networks and Their Applications, Cambridge, United Kingdom, December 11-13, 2018. Published in: Complex Networks and Their Applications VII. 812 376-391. Springer ISSN 1860-949X ISBN 9783030054106

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Realistic human contact networks capable of spreading infectious disease, for example studied in social contact surveys, exhibit both significant degree heterogeneity and clustering, both of which greatly affect epidemic dynamics. To understand the joint effects of these two network properties on epidemic dynamics, the effective degree model of Lindquist et al. [28] is reformulated with a new moment closure to apply to highly clustered networks. A simulation study comparing alternative ODE models and stochastic simulations is performed for SIR (Susceptible–Infected–Removed) epidemic dynamics, including a test for the conjectured error behaviour in [40], providing evidence that this novel model can be a more accurate approximation to epidemic dynamics on complex networks than existing approaches.

Item Type: Conference Proceedings
Schools and Departments: School of Mathematical and Physical Sciences > Mathematics
Research Centres and Groups: Mathematics Applied to Biology Research Group
Depositing User: Alice Jackson
Date Deposited: 19 Nov 2018 14:31
Last Modified: 19 Feb 2021 11:39

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