The effect of clumped population structure on the variability of spreading dynamics

JOURNAL OF THEORETICAL BIOLOGY

卷:359

Article

Black, Andrew J.¹  House, Thomas^2,3  Keeling, Matt J.^2,3,4  Ross, Joshua V.¹ 

[1] Univ Adelaide, Sch Math Sci, Adelaide, SA 5005, Australia

[2] Univ Warwick, Math Inst, Coventry CV4 7AL, W Midlands, England

[3] Univ Warwick, Warwick Infect Dis Epidemiol Res WIDER Ctr, Coventry CV4 7AL, W Midlands, England

[4] Univ Warwick, Sch Life Sci, Coventry CV4 7AL, W Midlands, England

关键词: Epidemics;    Continuous-time Markov chain;    Offspring distribution;    Diffusion approximation;   

DOI  :  10.1016/j.jtbi.2014.05.042

来源: Elsevier

【 摘 要 】

Processes that spread through local contact, including outbreaks of infectious diseases, are inherently noisy, and are frequently observed to be far noisier than predicted by standard stochastic models that assume homogeneous mixing. One way to reproduce the observed levels of noise is to introduce significant individual-level heterogeneity with respect to infection processes, such that some individuals are expected to generate more secondary cases than others. Here we consider a population where individuals can be naturally aggregated into clumps (subpopulations) with stronger interaction within clumps than between them. This clumped structure induces significant increases in the noisiness of a spreading process, such as the transmission of infection, despite complete homogeneity at the individual level. Given the ubiquity of such clumped aggregations (such as homes, schools and workplaces for humans or farms for livestock) we suggest this as a plausible explanation for noisiness of many epidemic time series. (C) 2014 Elsevier Ltd. All rights reserved.

【 授权许可】

Free