Multiscale mobility networks and the spatial spreading of infectious diseases
Multiscale mobility networks and the spatial spreading of infectious diseases
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DOI：
10.1073/pnas.0906910106
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发表时间：
2009-12-22
影响因子：
11.1
通讯作者：
Vespignani, Alessandro
中科院分区：
文献类型：
--
作者：
Balcan, Duygu;Colizza, Vittoria;Vespignani, Alessandro
在传染病的计算建模中要考虑的现实因素中，人员流动性在理论方面和经验数据的有限性方面都是一个关键的挑战。为了研究短期通勤流和远程航空交通在塑造全球流行病时空模式方面的相互作用，我们（i）分析了来自世界各地29个国家的流动数据，并找到了一个重力模型，该模型能够提供高达300公里的通勤模式的全球描述，（ii）在全球结构的集合种群流行病模型中集成了一个时间尺度-分离技术，用于评估由于疾病动力学中的多尺度移动过程而导致的感染力。平均而言，通勤流量比航空流量大一个数量级。然而，将它们引入全球模型表明，模拟流行病的大规模模式与只考虑航空交通的基线情况相比只有很小的变化。然而，短距离流动的存在增加了近距离亚群体的同步性，并影响了航空运输基础设施周边的流行病行为。本方法概述了分层计算方法的定义的可能性，不同的建模假设和粒度可以始终使用在一个统一的多尺度框架。
Among the realistic ingredients to be considered in the computational modeling of infectious diseases, human mobility represents a crucial challenge both on the theoretical side and in view of the limited availability of empirical data. To study the interplay between short-scale commuting flows and long-range airline traffic in shaping the spatiotemporal pattern of a global epidemic we (i) analyze mobility data from 29 countries around the world and find a gravity model able to provide a global description of commuting patterns up to 300 kms and (ii) integrate in a worldwide-structured metapopulation epidemic model a timescale-separation technique for evaluating the force of infection due to multiscale mobility processes in the disease dynamics. Commuting flows are found, on average, to be one order of magnitude larger than airline flows. However, their introduction into the worldwide model shows that the large-scale pattern of the simulated epidemic exhibits only small variations with respect to the baseline case where only airline traffic is considered. The presence of short-range mobility increases, however, the synchronization of sub-populations in close proximity and affects the epidemic behavior at the periphery of the airline transportation infrastructure. The present approach outlines the possibility for the definition of layered computational approaches where different modeling assumptions and granularities can be used consistently in a unifying multiscale framework.