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通过大都市社交网络对传染病、信息和预防行为的三重扩散进行建模——基于主体的模拟

Modeling triple-diffusions of infectious diseases, information, and preventive behaviors through a metropolitan social network-An agent-based simulation.

作者信息

Mao Liang

机构信息

Department of Geography, University of Florida, P.O. Box 117315, 3142 Turlington Hall, Gainesville, FL 32611, USA.

出版信息

Appl Geogr. 2014 Jun;50:31-39. doi: 10.1016/j.apgeog.2014.02.005. Epub 2014 Mar 4.

Abstract

A typical epidemic often involves the transmission of a disease, the flow of information regarding the disease, and the spread of human preventive behaviors against the disease. These three processes diffuse simultaneously through human social networks, and interact with one another, forming negative and positive feedback loops in the complex human-disease systems. Few studies, however, have been devoted to coupling all the three diffusions together and representing their interactions. To fill the knowledge gap, this article proposes a spatially explicit agent-based model to simulate a triple-diffusion process in a metropolitan area of 1 million people. The individual-based approach, network model, behavioral theories, and stochastic processes are used to formulate the three diffusions and integrate them together. Compared to the observed facts, the model results reasonably replicate the trends of influenza spread and information propagation. The model thus could be a valid and effective tool to evaluate information/behavior-based intervention strategies. Besides its implications to the public health, the research findings also contribute to network modeling, systems science, and medical geography.

摘要

一场典型的流行病通常涉及疾病的传播、有关该疾病的信息流动以及人类针对该疾病的预防行为的传播。这三个过程通过人类社会网络同时扩散,并相互作用,在复杂的人类-疾病系统中形成正负反馈回路。然而,很少有研究致力于将所有这三种扩散结合在一起并呈现它们的相互作用。为了填补这一知识空白,本文提出了一种基于空间显式主体的模型,以模拟一个拥有100万人口的大都市地区的三重扩散过程。基于个体的方法、网络模型、行为理论和随机过程被用于构建这三种扩散并将它们整合在一起。与观察到的事实相比,模型结果合理地再现了流感传播和信息传播的趋势。因此,该模型可能是评估基于信息/行为的干预策略的有效工具。除了对公共卫生的影响外,研究结果还对网络建模、系统科学和医学地理学做出了贡献。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c91/7124377/5427c58f570a/gr1.jpg

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