Spatial Modeling and Analysis of Human Traffic and Infectious Virus Spread in Community Networks
Spatial Modeling and Analysis of Human Traffic and Infectious Virus Spread in Community Networks
复制标题
社区网络中人流量和传染性病毒传播的空间建模与分析
DOI：
10.1109/embc46164.2021.9630798
复制
发表时间：
2021
期刊：
影响因子：
--
通讯作者：
Yang, Hui
中科院分区：
文献类型：
--
作者：
Zhang, Siqi;Yang, Hui
利用网络模型研究传染病的传播越来越受到人们的关注。它们允许将流行病系统灵活地表示为具有复杂和互连结构的组件网络。然而，以前的大多数研究都是基于作为节点的个人及其社会关系（例如，友谊、职场人脉）作为病毒传播过程中的纽带。值得注意的是，传染性病毒的传播和扩散与人类动力学更相关（例如，他们的运动和与他人的互动）在空间环境中。本文提出了一种新的基于网络的仿真模型的人流量和病毒传播的社区网络。我们将空间兴趣点（POI）表示为人类主体进行交互和执行活动的节点，而边缘连接这些POI以形成社区网络。具体来说，我们从地理信息系统（GIS）数据中获得的空间网络，提供了一个详细的表示的底层社区网络，人类主体上执行的活动，并形成交通影响的过程中的病毒传播和蔓延。该框架在大学校园社区进行了评估和验证。实验结果表明，该仿真模型能够在个体水平上描述交互式人类活动，以及捕捉传染病的传播动力学。这一框架可以扩展到各种传染病，并显示出强大的潜力，以帮助设计干预政策，流行病控制。
The use of network models to study the spread of infectious diseases is gaining increasing interests. They allow the flexibility to represent epidemic systems as networks of components with complex and interconnected structures. However, most of previous studies are based on networks of individuals as nodes and their social relationships (e.g., friendship, workplace connections) as links during the virus spread process. Notably, the transmission and spread of infectious viruses are more pertinent to human dynamics (e.g., their movements and interactions with others) in the spatial environment. This paper presents a novel network-based simulation model of human traffic and virus spread in community networks. We represent spatial points of interests (POI) as nodes where human subjects interact and perform activities, while edges connect these POIs to form a community network. Specifically, we derive the spatial network from the geographical information systems (GIS) data to provide a detailed representation of the underlying community network, on which human subjects perform activities and form traffics that impact the process of virus transmission and spread. The proposed framework is evaluated and validated in a community of university campus. Experimental results showed that the proposed simulation model is capable of describing interactive human activities at an individual level, as well as capturing the spread dynamics of infectious diseases. This framework can be extended to a wide variety of infectious diseases and shows strong potentials to aid the design of intervention policies for epidemic control.
影响因子：
4.6
作者：
Cot C;Cacciapaglia G;Sannino F
通讯作者：
Sannino F
医疗保健分析：从数据到知识到医疗保健改善：从数据到知识到医疗保健改善
DOI：
--
发表时间：
2016
期刊：
影响因子：
--
作者：
Hui Yang;Eva K. Lee
通讯作者：
Eva K. Lee