M
Matthew C. Vernon
Researcher at University of Warwick
Publications - 12
Citations - 1348
Matthew C. Vernon is an academic researcher from University of Warwick. The author has contributed to research in topics: Network theory & Dynamic network analysis. The author has an hindex of 9, co-authored 12 publications receiving 1204 citations. Previous affiliations of Matthew C. Vernon include University of Cambridge & Wellcome Trust/Cancer Research UK Gurdon Institute.
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Journal ArticleDOI
Networks and the epidemiology of infectious disease.
Leon Danon,Ashley P. Ford,Thomas House,Chris P. Jewell,Matthew James Keeling,Gareth O. Roberts,Joshua V. Ross,Matthew C. Vernon +7 more
TL;DR: A review of network epidemiology can be found in this article, where the authors focus on the interplay between network theory and epidemiology, focusing on the types of network relevant to epidemiology and statistical methods that can be applied to infer the epidemiological parameters on a realized network.
Journal ArticleDOI
Networks and the Epidemiology of Infectious Disease
Leon Danon,Ashley P. Ford,Thomas House,Chris P. Jewell,Matthew James Keeling,Gareth O. Roberts,Joshua V. Ross,Matthew C. Vernon +7 more
TL;DR: A personalised overview into the areas of network epidemiology that have seen the greatest progress in recent years or have the greatest potential to provide novel insights is provided, focusing on the interplay between network theory and epidemiology.
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Individual identity and movement networks for disease metapopulations.
TL;DR: It is shown that the identity of individuals responsible for making network connections can have a significant impact on the infection dynamics, with clear implications for detailed public health and veterinary applications.
Journal ArticleDOI
Representing the UK's cattle herd as static and dynamic networks
TL;DR: Using stochastic disease simulations, a wide range of network representations of the UK cattle herd are compared and it is found that the simpler static network representations are often deficient when compared with a fully dynamic representation, and should therefore be used only with caution in epidemiological modelling.
Journal ArticleDOI
Social encounter networks: characterizing Great Britain
Leon Danon,Jonathan M. Read,Thomas House,Matthew C. Vernon,Matthew C. Vernon,Matthew James Keeling +5 more
TL;DR: This study describes individual-level contact patterns, focusing on the range of heterogeneity observed, and quantifies the transitive connections made between an individual's contacts (or clustering), a key structural characteristic of social networks with important implications for disease transmission and control efficacy.