Measured dynamic social contact patterns explain the spread of H1N1v influenza.
Measured dynamic social contact patterns explain the spread of H1N1v influenza.
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DOI：
10.1371/journal.pcbi.1002425
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发表时间：
2012
影响因子：
4.3
通讯作者：
Edmunds WJ
中科院分区：
文献类型：
--
作者：
Eames KT;Tilston NL;Brooks-Pollock E;Edmunds WJ
社会混合模式是流行病传播的关键决定因素。在这里，我们提出了一个基于互联网的社会接触调查的结果完成了一个队列的参与者在2009年7月至2010年3月，在2009年H1N1 v流感流行期间超过9,000次。我们量化了社会接触模式随时间的变化，发现学生在假期期间的接触比学期期间少40%。我们使用这些动态变化的接触模式参数化的年龄结构模型的流感传播，捕捉到的发病率模式，不断变化的接触模式导致在假期期间的流感再现数量下降约35%。这项工作说明了在流行病模型中包括不断变化的混合模式的重要性。我们的结论是，接触模式的变化解释了疾病发病率的变化，以及学校学期的时间驱动了2009年H1N1 v在英国的流行。通过简单的互联网调查，可以有效地衡量社会混合模式的变化。社会混合模式的变化可能导致流行病行为的变化;这在2009年流感大流行期间观察到，其中流行病在学校假期期间下降，在学期期间上升。到目前为止，很少有信息可以量化人们的混合模式如何随时间变化。在这里，我们提出了一个基于互联网的调查结果的社会混合模式，在英国进行了整个2009年的大流行。我们发现，学校假期导致每天的社会接触数量大幅下降，特别是儿童之间。为了测试这些测量到的社会混合模式是否可以解释观察到的流行病，我们将混合数据用于一个简单的流感传播数学模型。我们发现，不断变化的社会接触行为可以解释社区中的感染水平，并得出结论，学校学期的时间是流感流行的形状。
Patterns of social mixing are key determinants of epidemic spread. Here we present the results of an internet-based social contact survey completed by a cohort of participants over 9,000 times between July 2009 and March 2010, during the 2009 H1N1v influenza epidemic. We quantify the changes in social contact patterns over time, finding that school children make 40% fewer contacts during holiday periods than during term time. We use these dynamically varying contact patterns to parameterise an age-structured model of influenza spread, capturing well the observed patterns of incidence; the changing contact patterns resulted in a fall of approximately 35% in the reproduction number of influenza during the holidays. This work illustrates the importance of including changing mixing patterns in epidemic models. We conclude that changes in contact patterns explain changes in disease incidence, and that the timing of school terms drove the 2009 H1N1v epidemic in the UK. Changes in social mixing patterns can be usefully measured through simple internet-based surveys. Changes in patterns of social mixing can result in changes in epidemic behaviour; this was observed during the 2009 influenza pandemic, in which the epidemic declined during school holidays and grew during term time. Until now, little information has been available to quantify how people's mixing patterns change over time. Here, we present the results of an internet-based survey of social mixing patterns that was carried out in the UK throughout the 2009 pandemic. We show that school holidays resulted in a substantial drop in the number of social contacts made each day, particularly between children. To test whether these measured patterns of social mixing could explain the observed epidemic, we used our mixing data in a simple mathematical model of influenza spread. We found that changing social contact behaviour could explain levels of infection in the community, and conclude that the timing of school terms was responsible for the shape of the influenza epidemic.
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影响因子：
3.7
作者：
Brooks-Pollock E;Tilston N;Edmunds WJ;Eames KT
通讯作者：
Eames KT
DOI：
10.1098/rspb.2006.0030
发表时间：
2007-05-07
期刊：
Proceedings. Biological sciences
影响因子：
--
作者：
Conlan AJ;Grenfell BT
通讯作者：
Grenfell BT
影响因子：
3.8
作者：
Melegaro, Alessia;Jit, Mark;Edmunds, W. John
通讯作者：
Edmunds, W. John
影响因子：
3.7
作者：
McCaw, James M.;Forbes, Kristian;McVernon, Jodie
通讯作者：
McVernon, Jodie
影响因子：
3.8
作者：
Eames, Ken T. D.;Tilston, Natasha L.;Edmunds, W. John
通讯作者：
Edmunds, W. John