Justified Stories with Agent-Based Modelling for Local COVID-19 Planning

被引:9
|
作者
Badham, Jennifer [1 ]
Barbrook-Johnson, Pete [2 ,4 ]
Caiado, Camila [3 ]
Castellani, Brian [1 ]
机构
[1] Univ Durham, Dept Sociol, 29-32 Old Elvet, Durham DH1 3HN, England
[2] Univ Surrey, Ctr Res Social Simulat, Dept Sociol, Guildford GU2 7XH, Surrey, England
[3] Univ Durham, Dept Math Sci, Upper Mountjoy Campus,Stockton Rd, Durham DH1 3LE, England
[4] Univ Oxford, Inst New Econ Thinking, Manor Rd, Oxford OX1 3UQ, England
来源
JASSS-THE JOURNAL OF ARTIFICIAL SOCIETIES AND SOCIAL SIMULATION | 2021年 / 24卷 / 01期
基金
英国经济与社会研究理事会; 英国医学研究理事会;
关键词
Agent-Based Modelling; Epidemic; COVID-19; Descriptive Model; Social Distancing; Justified Stories;
D O I
10.18564/jasss.4532
中图分类号
C [社会科学总论];
学科分类号
03 ; 0303 ;
摘要
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.
引用
收藏
页码:1 / 18
页数:18
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