Social encounter networks: characterizing Great Britain

被引:73
作者
Danon, Leon [1 ,2 ]
Read, Jonathan M. [3 ]
House, Thomas A. [1 ]
Vernon, Matthew C. [2 ,4 ]
Keeling, Matt J. [1 ,2 ]
机构
[1] Univ Warwick, Inst Math, Coventry CV4 7AL, W Midlands, England
[2] Univ Warwick, Sch Life Sci, Coventry CV4 7AL, W Midlands, England
[3] Univ Liverpool, Dept Epidemiol & Populat Hlth, Inst Infect & Global Hlth, Neston CH64 7TE, England
[4] Univ Cambridge, Univ Comp Serv, Cambridge CB2 3QH, England
基金
英国医学研究理事会; 英国工程与自然科学研究理事会;
关键词
social contact; survey; epidemic; infectious disease; network; SPATIAL STRUCTURE; MIXING PATTERNS; CONTACT; INFLUENZA; SPREAD; INFECTIONS; WEB;
D O I
10.1098/rspb.2013.1037
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
A major goal of infectious disease epidemiology is to understand and predict the spread of infections within human populations, with the intention of better informing decisions regarding control and intervention. However, the development of fully mechanistic models of transmission requires a quantitative understanding of social interactions and collective properties of social networks. We performed a cross-sectional study of the social contacts on given days for more than 5000 respondents in England, Scotland and Wales, through postal and online survey methods. The survey was designed to elicit detailed and previously unreported measures of the immediate social network of participants relevant to infection spread. Here, we describe individual-level contact patterns, focusing on the range of heterogeneity observed and discuss the correlations between contact patterns and other socio-demographic factors. We find that the distribution of the number of contacts approximates a power-law distribution, but postulate that total contact time (which has a shorter-tailed distribution) is more epidemiologically relevant. We observe that children, public-sector and healthcare workers have the highest number of total contact hours and are therefore most likely to catch and transmit infectious disease. Our study also quantifies the transitive connections made between an individual's contacts (or clustering); this is a key structural characteristic of social networks with important implications for disease transmission and control efficacy. Respondents' networks exhibit high levels of clustering, which varies across social settings and increases with duration, frequency of contact and distance from home. Finally, we discuss the implications of these findings for the transmission and control of pathogens spread through close contact.
引用
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页数:10
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