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Impact of Indirect Contacts in Emerging Infectious Disease on Social Networks

机译:新兴传染病中间接接触对社交网络的影响

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Interaction patterns among individuals play vital roles in spreading infectious diseases. Understanding these patterns and integrating their impact in modeling diffusion dynamics of infectious diseases are important for epidemiological studies. Current network-based diffusion models assume that diseases transmit through interactions where both infected and susceptible individuals are co-located at the same time. However, there are several infectious diseases that can transmit when a susceptible individual visits a location after an infected individual has left. Recently, we introduced a diffusion model called same place different time (SPDT) transmission to capture the indirect transmissions that happen when an infected individual leaves before a susceptible individual's arrival along with direct transmissions. In this paper, we demonstrate how these indirect transmission links significantly enhance the emergence of infectious diseases simulating airborne disease spreading on a synthetic social contact network. We denote individuals having indirect links but no direct links during their infectious periods as hidden spreaders. Our simulation shows that indirect links play similar roles of direct links and a single hidden spreader can cause large outbreak in the SPDT model which causes no infection in the current model based on direct link. Our work opens new direction in modeling infectious diseases.
机译:个体之间的相互作用模式在传播传染病中起着至关重要的作用。对于流行病学研究而言,了解这些模式并将其影响整合到传染病扩散动态模型中非常重要。当前基于网络的扩散模型假设疾病是通过相互作用传播的,感染者和易感者同时位于同一地点。但是,当受感染的个体离开后,当易感个体访问某个位置时,会传播几种传染病。最近,我们引入了一种扩散模型,称为同时间异时传播(SPDT)传播,以捕获当被感染的个体在易感个体到达之前离开而发生的间接传播以及直接传播。在本文中,我们演示了这些间接传播链接如何显着增强传染性疾病的出现,模拟在合成的社会联系网络上传播的空气传播的疾病。我们将个体在传染期间具有间接联系但没有直接联系的个体称为隐藏传播者。我们的仿真表明,间接链接在直接链接中起着相似的作用,单个隐藏的扩展器会导致SPDT模型中的大爆发,而在基于直接链接的当前模型中不会造成感染。我们的工作为传染病建模开辟了新的方向。

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