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. 2014 Dec 15;416:208-218. doi: 10.1016/j.physa.2014.08.056. Epub 2014 Sep 1.
In this paper, we study epidemic spreading in metapopulation networks wherein each node represents a subpopulation symbolizing a city or an urban area and links connecting nodes correspond to the human traveling routes among cities. Differently from previous studies, we introduce a heterogeneous infection rate to characterize the effect of nodes' local properties, such as population density, individual health habits, and social conditions, on epidemic infectivity. By means of a mean-field approach and Monte Carlo simulations, we explore how the heterogeneity of the infection rate affects the epidemic dynamics, and find that large fluctuations of the infection rate have a profound impact on the epidemic threshold as well as the temporal behavior of the prevalence above the epidemic threshold. This work can refine our understanding of epidemic spreading in metapopulation networks with the effect of nodes' local properties.
在本文中，我们研究了异质种群网络中的疫情传播，其中每个节点代表一个象征着城市或城区的子种群，连接节点的边对应城市间的人员流动路线。与先前的研究不同，我们引入了异质感染率来表征节点的局部属性（如人口密度、个人健康习惯和社会状况）对疫情传染性的影响。通过平均场方法和蒙特卡罗模拟，我们探究了感染率的异质性如何影响疫情动态，并发现感染率的大幅波动对疫情阈值以及高于疫情阈值时流行率的时间行为有深远影响。这项工作能够加深我们对具有节点局部属性影响的异质种群网络中疫情传播的理解。
