Inferring epidemic contact structure from phylogenetic trees.
Inferring epidemic contact structure from phylogenetic trees.
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DOI：
10.1371/journal.pcbi.1002413
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发表时间：
2012
影响因子：
4.3
通讯作者：
Bonhoeffer S
中科院分区：
文献类型：
--
作者：
Leventhal GE;Kouyos R;Stadler T;Wyl Vv;Yerly S;Böni J;Cellerai C;Klimkait T;Günthard HF;Bonhoeffer S
接触结构被认为对流行病传播有很大的影响，因此使用网络来建模这种接触结构继续获得流行病学的兴趣。然而，对真实的流行病背后的确切接触结构的详细了解是有限的。在这里，我们解决的问题是否接触网络的结构留下了可检测的遗传指纹的病原体人口。为此，我们比较了不同类型的接触网络的模拟人群中的疾病暴发所产生的传染性。我们发现，这些hologenies的形状强烈依赖于接触结构。特别是，树的不平衡的措施，使我们能够量化到什么程度的接触结构的流行病偏离一个空模型的接触网络，并说明这在随机混合的情况下。使用从瑞士艾滋病毒流行病的一个genigeny，我们表明，这种流行病有一个显着更不平衡的树比随机混合的预期。传染病流行病学最近的一个关键创新是将明确的接触结构（即谁可以感染谁）纳入流行病学模型。理论研究已经在该领域产生了广泛的共识，即接触网络的知识可能有助于大大改善对流行病传播的控制。然而，这一领域的关键问题是，我们缺乏关于真实的流行病背后的实际接触结构的知识。许多研究都集中在试图以各种方式重建实际的联系网络（移动的电话使用数据，测量物理接近度的电子设备，患者访谈等）。所有这些方法都是高度劳动密集型的，并且充满了许多困难。在这里，我们提出了一种新的方法，这是基于现成的序列数据。以瑞士艾滋病流行为例，我们表明，它显示出强烈的迹象，一个潜在的接触结构，强烈不同于随机相互作用，从而削弱了随机混合的假设，这是流行病学模型中常见的。
Contact structure is believed to have a large impact on epidemic spreading and consequently using networks to model such contact structure continues to gain interest in epidemiology. However, detailed knowledge of the exact contact structure underlying real epidemics is limited. Here we address the question whether the structure of the contact network leaves a detectable genetic fingerprint in the pathogen population. To this end we compare phylogenies generated by disease outbreaks in simulated populations with different types of contact networks. We find that the shape of these phylogenies strongly depends on contact structure. In particular, measures of tree imbalance allow us to quantify to what extent the contact structure underlying an epidemic deviates from a null model contact network and illustrate this in the case of random mixing. Using a phylogeny from the Swiss HIV epidemic, we show that this epidemic has a significantly more unbalanced tree than would be expected from random mixing. One of the recent key innovations in the epidemiology of infectious diseases was the incorporation of explicit contact structure (i.e. who can infect whom) into epidemiological models. Theoretical studies have generated a broad consensus in the field that knowledge of the contact network may help to greatly improve the control of the spread of epidemics. The key problem in the field, however, is that we lack knowledge regarding the actual contact structure underlying real epidemics. Much research is focused on trying to reconstruct actual contact networks in various ways (mobile phone usage data, electronic devices that measure physical proximity, patient interviews, etc). All of these approaches are highly labour intensive and are fraught with many difficulties. Here, we present a new approach which is based on readily available sequence data. Using the Swiss HIV epidemic as an example, we show that it displays strong indications of a underlying contact structure that strongly differs from random interactions, thus undercutting the assumption of random mixing which is commonly made in epidemiological models.
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影响因子：
1.4
作者：
Keeling, M
通讯作者：
Keeling, M
影响因子：
2.4
作者：
Moore, C;Newman, MEJ
通讯作者：
Newman, MEJ
影响因子：
56.9
作者：
Barabási, AL;Albert, R
通讯作者：
Albert, R
影响因子：
9.8
作者：
Drummond AJ;Ho SY;Phillips MJ;Rambaut A
通讯作者：
Rambaut A
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