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Effective Epidemic Control and Source Tracing Through Mobile Social Sensing over WBANs

机译:通过WBANS移动社会传感的有效疫情控制和源追踪

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Accurate and real-time tracing of epidemic sources is critical for epidemic origin analyses and control when out-breaks of epidemic diseases occur. Such tracing requires the simultaneous availability of information about social interactions among people as well as their body vital signs. Existing epidemic control methods are limited due to their inability to collect the above two types of information at the same time. In this paper, for the first time, we propose integrating wireless body area networks (WBANs) for body vital signs collection with mobile phones for social interaction sensing to achieve the desired epidemic source tracing. In particular, we design a mobile phone capability driven hierarchical social interaction detection framework integrated with WBANs. With this framework, we further propose a set of epidemic source tracing and control algorithms including genetic algorithm based search and dominating set identification algorithms to effectively identify epidemic sources and inhibit epidemic spread. We have also conducted extensive simulations, analyses, and case studies based on real data sets, which demonstrate the accuracy and effectiveness of our proposed solutions.
机译:当发生流行病疾病的脱落时,对疫情来源的准确性和实时追踪对于疫情来分析和控制至关重要。这种追踪需要同时可用于人们之间的社会互动以及他们的身体生命体征。由于无法在同一时间收集上述两种类型的信息,因此存在于现有的疫情控制方法。在本文中,我们第一次提出将无线体积网络(WBANS)集成在一起与移动电话的身体生命体征收集,以便进行社交相互作用感测,以实现所需的流行病源跟踪。特别是,我们设计了与WBANS集成的移动电话能力驱动的分层社交交互检测框架。利用本框架,我们进一步提出了一组流行病源跟踪和控制算法,包括基于遗传算法的搜索和主导集合识别算法,以有效地识别疫情来源并抑制流行病。我们还基于真实数据集进行了广泛的模拟,分析和案例研究,展示了我们提出的解决方案的准确性和有效性。

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