Decision Support for Infection Outbreak Analysis: the case of the Diamond Princess cruise ship

H. C. R. Oliveira, V. Shmerko, S. Yanushkevich
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引用次数: 2

Abstract

This paper focuses on designing a CI decision support to address rare events such as disease outbreaks in a ‘closed’ environment such as a cruise ship. We focus on a case study of the COVID-19 outbreak that happened on board the Diamond Princess cruise ship in 2020. It considers a graphical probabilistic model such as Bayesian Network. We consider this causal model to be a core of an intelligent decision support tool to help in emergency management. To prove this hypothesis, the prototype of a decision support tool was implemented and used to evaluate different scenarios. The results show that such system equipped with a reasoning engine is capable of evaluating the pandemic scenario risks, thus helping assess the impacts of certain preventive measures, and damages.
感染爆发分析的决策支持:以钻石公主号游轮为例
这篇论文的重点是设计一个CI决策支持来处理罕见事件,比如在游轮这样的“封闭”环境中疾病爆发。我们重点研究了2020年在钻石公主号游轮上发生的COVID-19疫情的案例。它考虑了一种图形概率模型,如贝叶斯网络。我们认为这一因果模型是智能决策支持工具的核心,有助于应急管理。为了证明这一假设,实现了决策支持工具的原型,并用于评估不同的场景。结果表明,该系统配备了推理引擎,能够评估大流行情景风险,从而有助于评估某些预防措施的影响和损害。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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