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A stochastic SIR network epidemic model with preventive dropping of edges

Ball, Frank; Britton, Tom; Yin Leung, Ka; Sirl, David

Authors

FRANK BALL frank.ball@nottingham.ac.uk
Professor of Applied Probability

Tom Britton

Ka Yin Leung

DAVID SIRL David.Sirl@nottingham.ac.uk
Senior Research Fellow



Abstract

A Markovian SIR (Susceptible – Infectious - Recovered) model is considered for the spread of an epidemic on a configuration model network, in which susceptible individuals may take preventive measures by dropping edges to infectious neighbours. An effective degree formulation of the model is used in conjunction with the theory of density dependent population processes to obtain a law of large numbers and a functional central limit theorem for the epidemic as the population size N - ¥, assuming that the degrees of individuals are bounded. A central limit theorem is conjectured for the final size of the epidemic. The results are obtained for both the Molloy–Reed (in which the degrees of individuals are deterministic) and Newman–Strogatz–Watts (in which the degrees of individuals are independent and identically distributed) versions of the configuration model. The two versions yield the same limiting deterministic model but the asymptotic variances in the central limit theorems are greater in the Newman–Strogatz–Watts version. The basic reproduction number R0 and the process of susceptible individuals in the limiting deterministic model, for the model with dropping of edges, are the same as for a corresponding SIR model without dropping of edges but an increased recovery rate, though, when R0 > 1, the probability of a major outbreak is greater in the model with dropping of edges. The results are specialised to the model without dropping of edges to yield conjectured central limit theorems for the final size of Markovian SIR epidemics on configuration-model networks, and for the giant components of those networks. The theory is illustrated by numerical studies, which demonstrate that the asymptotic approximations are good, even for moderate N.

Citation

Ball, F., Britton, T., Yin Leung, K., & Sirl, D. (2019). A stochastic SIR network epidemic model with preventive dropping of edges. Journal of Mathematical Biology, 78(6), 1875-1951. https://doi.org/10.1007/s00285-019-01329-4

Journal Article Type Article
Acceptance Date Jan 18, 2019
Online Publication Date Mar 13, 2019
Publication Date May 1, 2019
Deposit Date Feb 6, 2019
Publicly Available Date Mar 14, 2020
Journal Journal of Mathematical Biology
Print ISSN 0303-6812
Electronic ISSN 1432-1416
Publisher Springer Verlag
Peer Reviewed Peer Reviewed
Volume 78
Issue 6
Pages 1875-1951
DOI https://doi.org/10.1007/s00285-019-01329-4
Keywords Agricultural and Biological Sciences (miscellaneous); Modelling and Simulation; Applied Mathematics
Public URL https://nottingham-repository.worktribe.com/output/1522863
Publisher URL https://link.springer.com/article/10.1007%2Fs00285-019-01329-4
Additional Information Received: 4 June 2018; Revised: 18 January 2019; First Online: 13 March 2019

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