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Pandemic Dynamics with Social Effects:Rapid Model Prototyping with Fuzzy Logic

机译:具有社会影响的大流行动力学:基于模糊逻辑的快速模型原型

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The human behavior aspect of pandemic prevention and mitigation involve uncertainties manifested as a range of responses, from the extreme to the indifferent. Relationships between variables influencing human behavior are usually described qualitatively, and as such do not suffice for stock and flow models. These uncertainties can slow down the modelling process considerably, thus limiting the effectiveness of a model-based approach in time-critical studies such as an impending pandemic outbreak. Our proposed approach utilizes fuzzy modelling concepts integrated within the system dynamics modelling framework to create a rapid model prototyping process of developing a pandemic dynamics model. This can facilitate quantitative analysis for policy making in pandemic mitigation interventions. We use the recent H1N1 pandemic in Singapore as a case example to demonstrate the practical usefulness of our approach.
机译:大流行预防和缓解的人类行为方面涉及不确定性,这些不确定性表现为从极端到冷漠的一系列响应。通常定性地描述影响人类行为的变量之间的关系,因此,它们不足以用于库存和流量模型。这些不确定性可能会大大减慢建模过程的速度,从而限制了基于时间的关键研究(如即将爆发的大流行)中基于模型的方法的有效性。我们提出的方法利用集成在系统动力学建模框架中的模糊建模概念来创建开发大流行动力学模型的快速模型原型制作过程。这可以促进对大流行减缓干预措施中的政策制定进行定量分析。我们以新加坡最近的H1N1大流行为例,以证明我们的方法的实用性。

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