Justified Stories with Agent-Based Modelling for Local COVID-19 Planning
Justified Stories with Agent-Based Modelling for Local COVID-19 Planning
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DOI：
10.18564/jasss.4532
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发表时间：
2021-01-31
影响因子：
4.2
通讯作者：
Castellani, Brian
中科院分区：
文献类型：
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作者：
Badham, Jennifer;Barbrook-Johnson, Pete;Castellani, Brian
本文提出了Just-Social，这是一个基于主体的新冠肺炎疫情模型，带有一系列潜在的社会政策干预。它的开发是为了支持英格兰东北部的地方当局，他们在一场快速变化的危机中做出决策，但获得的数据有限。Just-Social的直接目的是描述，因为该模型代表了关于新冠肺炎传播和干预效果的知识。它的最终目的是制作故事，回应当地规划者和政策制定者的问题和关切，并根据陈述的质量证明是合理的。这些合理的故事以地方一级可获得的、及时的和有用的方式组织知识，帮助决策者更好地了解他们的现状和政策替代方案的看似合理的结果。正义-社会和合理故事的概念适用于一般传染病的建模，甚至更广泛地适用于公共卫生的建模，特别是复杂系统中的政策干预。
This paper presents JuSt-Social, an agent-based model of the COVID-19 epidemic with a range of potential social policy interventions. It was developed to support local authorities in North East England who are making decisions in a fast moving crisis with limited access to data. The proximate purpose of JuSt-Social is description, as the model represents knowledge about both COVID-19 transmission and intervention effects. Its ultimate purpose is to generate stories that respond to the questions and concerns of local planners and policy makers and are justified by the quality of the representation. These justified stories organise the knowledge in way that is accessible, timely and useful at the local level, assisting the decision makers to better understand both their current situation and the plausible outcomes of policy alternatives. JuSt-Social and the concept of justified stories apply to the modelling of infectious disease in general and, even more broadly, modelling in public health, particularly for policy interventions in complex systems.