Ruan Zhongyuan, Hui Pakming, Lin Haiqing, Liu Zonghua
1Department of Physics, East China Normal University, Shanghai, 200062 P.R. China.
2Department of Physics, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong.
Eur Phys J B. 2013;86(1):13. doi: 10.1140/epjb/e2012-30292-x. Epub 2013 Jan 21.
In view of the huge investments into the construction of high speed rails systems in USA, Japan, and China, we present a two-layer traveling network model to study the risks that the railway network poses in case of an epidemic outbreak. The model consists of two layers with one layer representing the railway network and the other representing the local-area transportation subnetworks. To reveal the underlying mechanism, we also study a simplified model that focuses on how a major railway affects an epidemic. We assume that the individuals, when they travel, take on the shortest path to the destination and become non-travelers upon arrival. When an infection process co-evolves with the traveling dynamics, the railway serves to gather a crowd, transmit the disease, and spread infected agents to local area subnetworks. The railway leads to a faster initial increase in infected agents and a higher steady state infection, and thus poses risks; and frequent traveling leads to a more severe infection. These features revealed in simulations are in agreement with analytic results of a simplified version of the model.
鉴于美国、日本和中国在高铁系统建设方面投入巨大，我们提出了一个两层出行网络模型，以研究铁路网络在疫情爆发时所带来的风险。该模型由两层组成，一层代表铁路网络，另一层代表局部交通子网。为揭示潜在机制，我们还研究了一个简化模型，该模型重点关注一条主要铁路如何影响疫情。我们假设个体在出行时会选择前往目的地的最短路径，并在到达后成为非出行者。当感染过程与出行动态共同演变时，铁路起到聚集人群、传播疾病以及将感染源传播到局部子网的作用。铁路导致感染源的初始增长更快且稳态感染更高，从而带来风险；频繁出行会导致更严重的感染。模拟中揭示的这些特征与该模型简化版本的分析结果一致。
