Contact profiles in eight European countries and implications for modelling the spread of airborne infectious diseases.
Contact profiles in eight European countries and implications for modelling the spread of airborne infectious diseases.
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DOI：
10.1371/journal.pone.0005931
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发表时间：
2009-06-17
期刊：
影响因子：
3.7
通讯作者：
Mikolajczyk RT
中科院分区：
文献类型：
--
作者：
Kretzschmar M;Mikolajczyk RT
为了了解传染病的传播，了解人群中可传播感染的接触模式是至关重要的。除了接触率和不同年龄段之间的混合，个人在不同地点分布接触者的方式可能在决定感染如何在人群中传播方面发挥重要作用。在8个国家进行了具有代表性的调查，以评估社会接触的数量(与另一个人近距离交谈，无论是否有身体接触)，使用日记的方法，参与者记录个人接触。总体样本量为7290名受访者。我们分析了六个不同环境(家庭、工作、学校、休闲、交通和其他)每个受访者报告的联系人数量，以定义不同的联系人配置文件。使用SPSS中实现的两步聚类分析算法来识别概况并根据这些概况对答复者进行分类。我们确定了七种不同的联系方式：受访者有：(1)混合：主要在学校、交通工具和休闲时间接触，(2)休闲时间接触，(3)主要在家庭(大家庭)接触，(4)工作接触，(5)仅在学校接触，(6)在其他地方接触，以及(7)在任何环境下接触人数较少的受访者。在参与这项研究的所有八个欧洲国家都可以找到类似的联系方式。受访者在所有国家的概况分布都是相似的。这些个人资料主要是工作、学校和家庭联系人。而且，休闲活动中的联系在很大一部分人的日常生活中也发挥着重要作用。令人惊讶的是，在所有地点都只有很少联系人的人数量惊人。人口在接触者分布上具有明显的年龄依赖性。与早期专注于不同年龄段对传染病传播的贡献的研究不同，我们的结果打开了分析感染如何在地点之间传播以及工作或学校等地点如何通过家庭接触相互联系的机会。考虑到这些当地接触模式的数学模型可以用来评估学校关闭和取消休闲活动等干预措施对流感传播的影响。
For understanding the spread of infectious diseases it is crucial to have knowledge of the patterns of contacts in a population during which the infection can be transmitted. Besides contact rates and mixing between age groups, the way individuals distribute their contacts across different locations may play an important role in determining how infections spread through a population. Representative surveys were performed in eight countries to assess the number of social contacts (talking to another person at close distance either with or without physical contact), using a diary approach in which participants recorded individual contacts. The overall sample size was 7290 respondents. We analyzed the reported numbers of contacts per respondent in six different settings (household, work, school, leisure, transportation and others) to define different contact profiles. The identification of the profiles and classification of respondents according to these profiles was conducted using a two-step cluster analysis algorithm as implemented in SPSS. We identified seven distinct contact profiles: respondents having (1) mixed: contacts predominantly at school, during transportation and leisure time, (2) contacts during leisure time, (3) contacts mainly in the household (large family), (4) contacts at work, (5) contacts solely at school, (6) contacts in other places and finally (7) respondents having a low number of contacts in any setting. Similar contact profiles can be found in all eight European countries which participated in the study. The distributions of respondents across the profiles were similar in all countries. The profiles are dominated by work, school and household contacts. But also contacts during leisure activities play an important role in the daily lives of a large fraction of individuals. A surprisingly large number of individuals has only few contacts in all locations. There was a distinct age-dependence in the distribution of the population across contact profiles. In contrast with earlier studies that focussed on the contribution of different age groups to the spread of an infectious disease, our results open up the opportunity to analyze how an infection spreads between locations and how locations as work or school are interconnected via household contacts. Mathematical models that take these local contact patterns into account can be used to assess the effect of intervention measures like school closure and cancelling of leisure activities on the spread of influenza.
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影响因子：
5
作者：
Wallinga, Jacco;Teunis, Peter;Kretzschmar, Mirjam
通讯作者：
Kretzschmar, Mirjam
影响因子：
2.3
作者：
Edmunds WJ;Kafatos G;Wallinga J;Mossong JR
通讯作者：
Mossong JR
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
影响因子：
3.1
作者：
Mikolajczyk, Rafael T.;Kretzschmar, Mirjam
通讯作者：
Kretzschmar, Mirjam
DOI：
10.1073/pnas.0601266103
发表时间：
2006-04-11
影响因子：
11.1
作者：
Germann, TC;Kadau, K;Macken, CA
通讯作者：
Macken, CA