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Network-Based Modeling in Epidemiology: An Emphasis on Dynamics

机译:基于网络的流行病学建模:对动力学的重视

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The social behavior of individuals is an important factor of the transmission and the evolution of many diseases. As such, epidemic studies have attempted to integrate social aspects in dissemination modeling. Since the pioneering works of Klovdahl on AIDS in 1985, epidemiological investigations and interventions increasingly focus on social networks. Significant factors of the transmission and outbreak of many infectious diseases are the structure and nature of human interactions. Network-based modeling approaches have found various applications in epidemiology as a simple yet efficient way to represent the complexity of human relationships implicated in dissemination processes. However, most results have been obtained by considering social networks as steady stage structures. Evolving networks have not been explored. The objective is first to give an overview of network-based modeling attempts in epidemiology to analyze and understand the dissemination processes with an emphasis on dynamic networks. The authors approach is designed to understand the impact of social links dynamics on epidemic spread. The authors present the results obtained by combining network evolution patterns (link creation and deletion) and a typical epidemic model. The speed of link dynamics and the infection time strongly influence the occurrence and value of the epidemic peak.
机译:个人的社会行为是许多疾病传播和演变的重要因素。因此,流行病学研究试图将社会方面整合到传播模型中。自1985年克洛夫达尔(Klovdahl)在艾滋病方面的开创性工作以来,流行病学调查和干预措施越来越侧重于社交网络。多种传染病传播和爆发的重要因素是人类相互作用的结构和性质。基于网络的建模方法已经在流行病学中发现了多种应用,作为一种简单但有效的方式来表示传播过程中涉及的人类关系的复杂性。但是,大多数结果是通过将社交网络视为稳定的阶段结构而获得的。尚未探索不断发展的网络。目的首先是概述流行病学中基于网络的建模尝试,以分析和理解传播过程,并重点关注动态网络。作者的方法旨在了解社会联系动态对流行病传播的影响。作者介绍了通过结合网络演化模式(链接创建和删除)和典型的流行病模型获得的结果。连接动力学的速度和感染时间强烈影响流行病高峰的发生和价值。

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