Home > Research > Publications & Outputs > Network epidemic models with two levels of mixing

Associated organisational unit

View graph of relations

Network epidemic models with two levels of mixing

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Published

Standard

Network epidemic models with two levels of mixing. / Ball, Frank; Neal, Peter.
In: Mathematical Biosciences, Vol. 212, No. 1, 03.2008, p. 69-87.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Ball, F & Neal, P 2008, 'Network epidemic models with two levels of mixing', Mathematical Biosciences, vol. 212, no. 1, pp. 69-87. https://doi.org/10.1016/j.mbs.2008.01.001

APA

Vancouver

Ball F, Neal P. Network epidemic models with two levels of mixing. Mathematical Biosciences. 2008 Mar;212(1):69-87. doi: 10.1016/j.mbs.2008.01.001

Author

Ball, Frank ; Neal, Peter. / Network epidemic models with two levels of mixing. In: Mathematical Biosciences. 2008 ; Vol. 212, No. 1. pp. 69-87.

Bibtex

@article{a614b554382542f0af911f335b85544a,
title = "Network epidemic models with two levels of mixing",
abstract = "The study of epidemics on social networks has attracted considerable attention recently. In this paper, we consider a stochastic SIR (susceptible → infective → removed) model for the spread of an epidemic on a finite network, having an arbitrary but specified degree distribution, in which individuals also make casual contacts, i.e. with people chosen uniformly from the population. The behaviour of the model as the network size tends to infinity is investigated. In particular, the basic reproduction number R0, that governs whether or not an epidemic with few initial infectives can become established is determined, as are the probability that an epidemic becomes established and the proportion of the population who are ultimately infected by such an epidemic. For the case when the infectious period is constant and all individuals in the network have the same degree, the asymptotic variance and a central limit theorem for the size of an epidemic that becomes established are obtained. Letting the rate at which individuals make casual contacts decrease to zero yields, heuristically, corresponding results for the model without casual contacts, i.e. for the standard SIR network epidemic model. A deterministic model that approximates the spread of an epidemic that becomes established in a large population is also derived. The theory is illustrated by numerical studies, which demonstrate that the asymptotic approximations work well, even for only moderately sized networks, and that the degree distribution and the inclusion of casual contacts can each have a major impact on the outcome of an epidemic.",
keywords = "SIR epidemics, Networks , Local and global contacts , Threshold behaviour , Global epidemic outbreaks , Final outcome of epidemic",
author = "Frank Ball and Peter Neal",
year = "2008",
month = mar,
doi = "10.1016/j.mbs.2008.01.001",
language = "English",
volume = "212",
pages = "69--87",
journal = "Mathematical Biosciences",
issn = "0025-5564",
publisher = "Elsevier Inc.",
number = "1",

}

RIS

TY - JOUR

T1 - Network epidemic models with two levels of mixing

AU - Ball, Frank

AU - Neal, Peter

PY - 2008/3

Y1 - 2008/3

N2 - The study of epidemics on social networks has attracted considerable attention recently. In this paper, we consider a stochastic SIR (susceptible → infective → removed) model for the spread of an epidemic on a finite network, having an arbitrary but specified degree distribution, in which individuals also make casual contacts, i.e. with people chosen uniformly from the population. The behaviour of the model as the network size tends to infinity is investigated. In particular, the basic reproduction number R0, that governs whether or not an epidemic with few initial infectives can become established is determined, as are the probability that an epidemic becomes established and the proportion of the population who are ultimately infected by such an epidemic. For the case when the infectious period is constant and all individuals in the network have the same degree, the asymptotic variance and a central limit theorem for the size of an epidemic that becomes established are obtained. Letting the rate at which individuals make casual contacts decrease to zero yields, heuristically, corresponding results for the model without casual contacts, i.e. for the standard SIR network epidemic model. A deterministic model that approximates the spread of an epidemic that becomes established in a large population is also derived. The theory is illustrated by numerical studies, which demonstrate that the asymptotic approximations work well, even for only moderately sized networks, and that the degree distribution and the inclusion of casual contacts can each have a major impact on the outcome of an epidemic.

AB - The study of epidemics on social networks has attracted considerable attention recently. In this paper, we consider a stochastic SIR (susceptible → infective → removed) model for the spread of an epidemic on a finite network, having an arbitrary but specified degree distribution, in which individuals also make casual contacts, i.e. with people chosen uniformly from the population. The behaviour of the model as the network size tends to infinity is investigated. In particular, the basic reproduction number R0, that governs whether or not an epidemic with few initial infectives can become established is determined, as are the probability that an epidemic becomes established and the proportion of the population who are ultimately infected by such an epidemic. For the case when the infectious period is constant and all individuals in the network have the same degree, the asymptotic variance and a central limit theorem for the size of an epidemic that becomes established are obtained. Letting the rate at which individuals make casual contacts decrease to zero yields, heuristically, corresponding results for the model without casual contacts, i.e. for the standard SIR network epidemic model. A deterministic model that approximates the spread of an epidemic that becomes established in a large population is also derived. The theory is illustrated by numerical studies, which demonstrate that the asymptotic approximations work well, even for only moderately sized networks, and that the degree distribution and the inclusion of casual contacts can each have a major impact on the outcome of an epidemic.

KW - SIR epidemics

KW - Networks

KW - Local and global contacts

KW - Threshold behaviour

KW - Global epidemic outbreaks

KW - Final outcome of epidemic

U2 - 10.1016/j.mbs.2008.01.001

DO - 10.1016/j.mbs.2008.01.001

M3 - Journal article

VL - 212

SP - 69

EP - 87

JO - Mathematical Biosciences

JF - Mathematical Biosciences

SN - 0025-5564

IS - 1

ER -