Computational decision-support tools for urban design to improve resilience against COVID-19 and other infectious diseases: A systematic review
文献类型：期刊论文
| 作者 | Yang, Liu1,6; Iwami, Michiyo4; Chen, Yishan3; Wu, Mingbo2,8; van Dam, Koen H. |
| 刊名 | PROGRESS IN PLANNING
 |
| 出版日期 | 2023-02-01 |
| 卷号 | 168页码:100657 |
| 关键词 | Urban design Urban planning Decision -support tool COVID-19 Infectious disease Computer modelling Resilience |
| DOI | 10.1016/j.progress.2022.100657 |
| 文献子类 | Review |
| 英文摘要 | The COVID-19 pandemic highlighted the need for decision-support tools to help cities become more resilient to infectious diseases. Through urban design and planning, non-pharmaceutical interventions can be enabled, impelling behaviour change and facilitating the construction of lower risk buildings and public spaces. Computational tools, including computer simulation, statistical models, and artificial intelligence, have been used to support responses to the current pandemic as well as to the spread of previous infectious diseases. Our multidisciplinary research group systematically reviewed state-of-the-art literature to propose a toolkit that employs computational modelling for various interventions and urban design processes. We selected 109 out of 8,737 studies retrieved from databases and analysed them based on the pathogen type, transmission mode and phase, design intervention and process, as well as modelling methodology (method, goal, motivation, focus, and indication to urban design). We also explored the relationship between infectious disease and urban design, as well as computational modelling support, including specific models and parameters. The proposed toolkit will help designers, planners, and computer modellers to select relevant approaches for evaluating design decisions depending on the target disease, geographic context, design stages, and spatial and temporal scales. The findings herein can be regarded as stand-alone tools, particularly for fighting against COVID-19, or be incorporated into broader frameworks to help cities become more resilient to future disasters. |
| WOS关键词 | VIRUS TRANSMISSION ; EPIDEMIC ; NETWORK ; CITIES ; FLATS ; MODEL |
| WOS研究方向 | Environmental Sciences & Ecology ; Public Administration |
| WOS记录号 | WOS:000931227300001 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/200759]  |
| 专题 | 资源与环境信息系统国家重点实验室_外文论文 |
| 作者单位 | 1.Southeast Univ, Sch Architecture, Nanjing, Peoples R China 2.China IPPR Int Engn CO LTD, Architecture & Urban Design Res Ctr, Beijing, Peoples R China 3.Imperial Coll London, Fac Med, Dept Infect Dis, London, England 4.Southeast Univ, Res Ctr Urban Design, Nanjing, Peoples R China 5.Southeast Univ, Sch Architecture, Si Pai Lou 2, Nanjing 210096, Jiangsu, Peoples R China 6.van Dam, Koen H.] Imperial Coll London, Ctr Proc Syst Engn, Dept Chem Engn, London, England 7.Univ Chinese Acad Sci, Beijing, Peoples R China 8.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Yang, Liu,Iwami, Michiyo,Chen, Yishan,et al. Computational decision-support tools for urban design to improve resilience against COVID-19 and other infectious diseases: A systematic review[J]. PROGRESS IN PLANNING,2023,168:100657. |
| APA | Yang, Liu,Iwami, Michiyo,Chen, Yishan,Wu, Mingbo,&van Dam, Koen H..(2023).Computational decision-support tools for urban design to improve resilience against COVID-19 and other infectious diseases: A systematic review.PROGRESS IN PLANNING,168,100657. |
| MLA | Yang, Liu,et al."Computational decision-support tools for urban design to improve resilience against COVID-19 and other infectious diseases: A systematic review".PROGRESS IN PLANNING 168(2023):100657. |
入库方式： OAI收割
来源：地理科学与资源研究所
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