Calculation of Disease Dynamics in a Population of Households

被引:36
作者
Ross, Joshua V. [1 ]
House, Thomas [2 ]
Keeling, Matt J. [2 ]
机构
[1] Univ Cambridge, Kings Coll, Cambridge, England
[2] Univ Warwick, Biol Sci & Math Inst, Coventry CV4 7AL, W Midlands, England
基金
英国惠康基金; 英国工程与自然科学研究理事会; 英国医学研究理事会;
关键词
EPIDEMIC MODELS; SIR EPIDEMICS; NETWORK; COMMUNITY; TRANSMISSION; INTEGRALS; INVASION; NUMBERS; SIZE;
D O I
10.1371/journal.pone.0009666
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Early mathematical representations of infectious disease dynamics assumed a single, large, homogeneously mixing population. Over the past decade there has been growing interest in models consisting of multiple smaller subpopulations (households, workplaces, schools, communities), with the natural assumption of strong homogeneous mixing within each subpopulation, and weaker transmission between subpopulations. Here we consider a model of SIRS (susceptible-infectious-recovered-susceptible) infection dynamics in a very large (assumed infinite) population of households, with the simplifying assumption that each household is of the same size (although all methods may be extended to a population with a heterogeneous distribution of household sizes). For this households model we present efficient methods for studying several quantities of epidemiological interest: (i) the threshold for invasion; (ii) the early growth rate; (iii) the household offspring distribution; (iv) the endemic prevalence of infection; and (v) the transient dynamics of the process. We utilize these methods to explore a wide region of parameter space appropriate for human infectious diseases. We then extend these results to consider the effects of more realistic gamma-distributed infectious periods. We discuss how all these results differ from standard homogeneous-mixing models and assess the implications for the invasion, transmission and persistence of infection. The computational efficiency of the methodology presented here will hopefully aid in the parameterisation of structured models and in the evaluation of appropriate responses for future disease outbreaks.
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页数:9
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