论文标题
模拟中国在多层运输网络上的流行病的传播：武汉冠状病毒超越
Simulating the Spread of Epidemics in China on the Multi-layer Transportation Network: Beyond the Coronavirus in Wuhan
论文作者
论文摘要
基于SEIR模型和城市运输网络的建模，建立了一种用于流行病在中国城市中传播的通用模拟器。中国公共交通系统在340多个县级城市之间被建模为多层双方网络，其层代表不同的运输方式（航空公司，铁路，帆路线和公共汽车），而节点分为两类（中央城市，外围城市）。在每个城市，一个开放系统SEIR模型跟踪疾病的局部传播，人口与上覆的运输网络交换。该模型解释了（1）在不同的运输媒体上流行的不同传播性，（2）城市的入站流量过渡，（3）由于路径重叠而引起的公共交通工具的交叉感染，以及（4）感染人群未进入公共交通和（5）恢复的人群的恢复人群是重复的感染。该模型可用于模拟城市级别在中国（以及可能其他国家）的任意流行病，其特征是其基本的繁殖数量，孵化期，感染期和人畜共患武力，源自任何中国县局局部城市，始于实施有效政府干预之前。流量示意图输入系统以触发城市间动力学，假设在节点的两点划分之间/之间的经验观察确定不同的流动强度，则将其触发。该模型用于模拟武汉的2019年冠状病毒流行。它表明该框架是强大而可靠的，模拟的结果在很大程度上与公共城市级数据集匹配。
Based on the SEIR model and the modeling of urban transportation networks, a general-purpose simulator for the spread of epidemics in Chinese cities is built. The Chinese public transportation system between over 340 prefectural-level cities is modeled as a multi-layer bi-partite network, with layers representing different means of transportation (airlines, railways, sail routes and buses), and nodes divided into two categories (central cities, peripheral cities). At each city, an open-system SEIR model tracks the local spread of the disease, with population in- and out-flow exchanging with the overlying transportation network. The model accounts for (1) different transmissivities of the epidemic on different transportation media, (2) the transit of inbound flow at cities, (3) cross-infection on public transportation vehicles due to path overlap, and the realistic considerations that (4) the infected population are not entering public transportation and (5) the recovered population are not subject to repeated infections. The model could be used to simulate the city-level spread in China (and potentially other countries) of an arbitrary epidemic, characterized by its basic reproduction number, incubation period, infection period and zoonotic force, originated from any Chinese prefectural-level city(s), during the period before effective government interventions are implemented. Flowmaps are input into the system to trigger inter-city dynamics, assuming different flow strength, determined from empirical observation, within/between the bi-partite divisions of nodes. The model is used to simulate the 2019 Coronavirus epidemic in Wuhan; it shows that the framework is robust and reliable, and simulated results match public city-level datasets to an extraordinary extent.
