Social encounter networks: characterizing Great Britain.
Social encounter networks: characterizing Great Britain.
复制标题
DOI：
10.1098/rspb.2013.1037
复制
发表时间：
2013-08-22
期刊：
影响因子：
--
通讯作者：
Keeling MJ
中科院分区：
文献类型：
--
作者：
Danon L;Read JM;House TA;Vernon MC;Keeling MJ
传染病流行病学的一个主要目标是了解和预测人群中感染的传播，以便更好地告知有关控制和干预的决策。但是，完全机械传播模型的发展需要对社交互动和社交网络的集体特性进行定量理解。我们通过邮政和在线调查方法在给定的天数中对给定数天的5000多名受访者进行了对社会联系的横断面研究。该调查旨在引起与感染传播相关的参与者的直接社交网络的详细和以前未报告的衡量标准。在这里，我们描述了个人级别的接触模式，重点是观察到的异质性范围，并讨论接触模式与其他社会人口统计学因素之间的相关性。我们发现，接触数的分布近似于幂律分布，但是假设总的接触时间（尾部分布较短）在流行病学上更相关。我们观察到儿童，公共部门和医疗保健工作者的总接触时间数量最多，因此最有可能捕获和传播传染病。我们的研究还量化了个人接触（或聚类）之间建立的传递连接；这是社交网络的关键结构特征，对疾病传播和控制功效具有重要意义。受访者的网络表现出高水平的聚类，随着社交环境的变化，随着持续时间，接触频率和距离家的距离而增加。最后，我们讨论了这些发现对病原体传播和控制病原体通过密切接触传播的含义。
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.
登录
查看更多内容
DOI：
10.1098/rspb.1997.0131
发表时间：
1997-07-22
影响因子：
4.7
作者：
Edmunds, WJ;OCallaghan, CJ;Nokes, DJ
通讯作者：
Nokes, DJ
影响因子：
64.8
作者：
Lloyd-Smith JO;Schreiber SJ;Kopp PE;Getz WM
通讯作者：
Getz WM
影响因子：
4.2
作者：
Smieszek, T.;Burri, E. U.;Scholz, R. W.
通讯作者：
Scholz, R. W.
影响因子：
4.3
作者：
House T;Keeling MJ
通讯作者：
Keeling MJ
与传染病的传播相关的社会接触和混合模式。
影响因子：
15.8
作者：
Mossong, Joeel;Hens, Niel;Jit, Mark;Beutels, Philippe;Auranen, Kari;Mikolajczyk, Rafael;Massari, Marco;Salmaso, Stefania;Tomba, Gianpaolo Scalia;Wallinga, Jacco;Heijne, Janneke;Sadkowska-Todys, Malgorzata;Rosinska, Magdalena;Edmunds, W. John
通讯作者：
Edmunds, W. John