Gong Yong-Wang, Song Yu-Rong, Jiang Guo-Ping
College of Automation, Nanjing University of Posts and Telecommunications, Nanjing 210003, China.
School of Information Engineering, Yancheng Institute of Technology, Yancheng 224051, China.
Physica A. 2013 Oct 1;392(19):4242-4251. doi: 10.1016/j.physa.2013.05.028. Epub 2013 May 25.
In this paper, explicitly considering the influences of an epidemic outbreak on human travel, a time-varying human mobility pattern is introduced to model the time variation of global human travel. The impacts of the pattern on epidemic dynamics in heterogeneous metapopulation networks, wherein each node represents a subpopulation with any number of individuals, are investigated by using a mean-field approach. The results show that the pattern does not alter the epidemic threshold, but can slightly lower the final average density of infected individuals as a whole. More importantly, we also find that the pattern produces different impacts on nodes with different degree, and that there exists a critical degree . For nodes with degree smaller than , the pattern produces a positive impact on epidemic mitigation; conversely, for nodes with degree larger than , the pattern produces a negative impact on epidemic mitigation.
在本文中，明确考虑了疫情爆发对人类出行的影响，引入了一种随时间变化的人类流动模式来模拟全球人类出行的时间变化。通过平均场方法研究了这种模式对异质集合种群网络中疫情动态的影响，其中每个节点代表一个具有任意数量个体的亚种群。结果表明，这种模式不会改变疫情阈值，但总体上可以略微降低最终感染个体的平均密度。更重要的是，我们还发现这种模式对不同度的节点产生不同的影响，并且存在一个临界度 。对于度小于 的节点，这种模式对疫情缓解产生积极影响；相反，对于度大于 的节点，这种模式对疫情缓解产生负面影响。
