Unifying the spatial epidemiology and molecular evolution of emerging epidemics
Unifying the spatial epidemiology and molecular evolution of emerging epidemics
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DOI：
10.1073/pnas.1206598109
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发表时间：
2012-09-11
影响因子：
11.1
通讯作者：
Delwart, Eric L.
中科院分区：
文献类型：
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作者：
Pybus, Oliver G.;Suchard, Marc A.;Delwart, Eric L.
我们在系统发育学和数学空间生态学之间引入了一座概念桥梁，这使得能够从采样的病原体基因组序列直接估计新出现的流行病的空间参数。通过使用系统发育史来校正空间自相关性，我们说明了如何使用稳健的非参数统计来估计基本的空间变量-扩散系数，以及如何容易地量化扩散中的异质性。我们将这个框架应用于西尼罗河病毒在北美的传播，这是最近一种新出现的传染病入侵空间的重要例子。我们证明，西尼罗河病毒的传播比以前测量的更大，也更不稳定，以至于它的传播是由罕见的远程运动决定的，而这些运动在现场观察中不太可能被察觉。我们的结果表明，通过忽略这种异质性，以前的流行病模型大大高估了它的基本繁殖数量。更广泛地说，我们的方法表明，可以使用容易获得的遗传数据来衡量自然种群的空间动态，否则这些空间动态很难量化或成本高昂。
We introduce a conceptual bridge between the previously unlinked fields of phylogenetics and mathematical spatial ecology, which enables the spatial parameters of an emerging epidemic to be directly estimated from sampled pathogen genome sequences. By using phylogenetic history to correct for spatial autocorrelation, we illustrate how a fundamental spatial variable, the diffusion coefficient, can be estimated using robust nonparametric statistics, and how heterogeneity in dispersal can be readily quantified. We apply this framework to the spread of the West Nile virus across North America, an important recent instance of spatial invasion by an emerging infectious disease. We demonstrate that the dispersal of West Nile virus is greater and far more variable than previously measured, such that its dissemination was critically determined by rare, long-range movements that are unlikely to be discerned during field observations. Our results indicate that, by ignoring this heterogeneity, previous models of the epidemic have substantially overestimated its basic reproductive number. More generally, our approach demonstrates that easily obtainable genetic data can be used to measure the spatial dynamics of natural populations that are otherwise difficult or costly to quantify.