作者: Frank Ball , David Sirl , Pieter Trapman
DOI: 10.1016/J.MBS.2009.12.003
关键词: Population 、 Stochastic modelling 、 Monte Carlo method 、 Communicable disease 、 Mathematics 、 Population size 、 Outbreak 、 Random graph 、 Cluster analysis 、 Statistics 、 Operations research
摘要: This paper is concerned with a stochastic SIR (susceptible → infective removed) model for the spread of an epidemic amongst population individuals, random network social contacts, that also partitioned into households. The behaviour as size tends to infinity in appropriate fashion investigated. A threshold parameter which determines whether or not few initial infectives can become established and lead major outbreak obtained, are probability occurs expected proportion ultimately infected by such outbreak, together methods calculating these quantities. Monte Carlo simulations demonstrate asymptotic quantities accurately reflect finite populations, even only moderately sized populations. compared contrasted related models previously studied literature. effects amount clustering present overall structure infectious period distribution on outcomes explored.