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

机译:通过大都会社交网络对传染病信息和预防行为的三重扩散进行建模-基于代理的模拟

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摘要

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.
机译:典型的流行病通常涉及疾病的传播,有关疾病的信息流以及人类对疾病的预防行为的传播。这三个过程通过人类社交网络同时扩散,并相互影响,在复杂的人类疾病系统中形成了负面和正面的反馈回路。然而,很少有研究致力于将所有三个扩散耦合在一起并代表它们的相互作用。为了填补知识空白,本文提出了一种基于空间显式主体的模型,以模拟在百万人口大都市中的三次扩散过程。基于个人的方法,网络模型,行为理论和随机过程被用来制定三种扩散并将它们整合在一起。与观察到的事实相比,该模型的结果合理地复制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。除了对公共卫生有影响外,研究结果还有助于网络建模,系统科学和医学地理。

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