Modelling disease outbreaks in realistic urban social networks
Modelling disease outbreaks in realistic urban social networks
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DOI：
10.1038/nature02541
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发表时间：
2004-05-13
期刊：
影响因子：
64.8
通讯作者：
Wang, N
中科院分区：
文献类型：
--
作者：
Eubank, S;Guclu, H;Wang, N
大多数疾病传播的数学模型都使用基于均匀混合假设 (1) 的微分方程或接触过程的临时模型 (2-4)。在这里，我们探索使用动态二分图来模拟因个人在特定位置之间的移动而产生的物理接触模式。这些图表是根据实际人口普查、土地使用和人口流动数据进行的大规模基于个人的城市交通模拟生成的。我们发现人与人之间的联系网络是一个强连接的类小世界（5）图，具有明确定义的度分布尺度。然而，位置图是无标度的(6)，通过将传感器放置在位置网络的中心，可以实现高效的疫情检测。在这个大规模模拟框架内，我们分析了几种提出的天花传播缓解策略的相对优点。我们的结果表明，可以通过有针对性的疫苗接种与早期发现相结合的策略来控制疫情的爆发，而无需对人群进行大规模疫苗接种。
Most mathematical models for the spread of disease use differential equations based on uniformmixing assumptions(1) or ad hoc models for the contact process(2-4). Here we explore the use of dynamic bipartite graphs to model the physical contact patterns that result from movements of individuals between specific locations. The graphs are generated by large-scale individual-based urban traffic simulations built on actual census, land-use and population-mobility data. We find that the contact network among people is a strongly connected small-world-like(5) graph with a well-defined scale for the degree distribution. However, the locations graph is scale-free(6), which allows highly efficient outbreak detection by placing sensors in the hubs of the locations network. Within this large-scale simulation framework, we then analyse the relative merits of several proposed mitigation strategies for smallpox spread. Our results suggest that outbreaks can be contained by a strategy of targeted vaccination combined with early detection without resorting to mass vaccination of a population.