Computational decision-support tools for urban design to improve resilience against COVID-19 and other infectious diseases: A systematic review

IF 5 1区 经济学 Q1 ENVIRONMENTAL STUDIES
Liu Yang , Michiyo Iwami , Yishan Chen , Mingbo Wu , Koen H. van Dam
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引用次数: 7

Abstract

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.

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城市设计的计算决策支持工具,以提高抵御新冠肺炎和其他传染病的能力:系统综述
新冠肺炎疫情突出表明,需要决策支持工具来帮助城市增强对传染病的抵御能力。通过城市设计和规划,可以实现非药物干预,推动行为改变,促进低风险建筑和公共空间的建设。包括计算机模拟、统计模型和人工智能在内的计算工具已被用于支持应对当前的疫情以及以前传染病的传播。我们的多学科研究小组系统地回顾了最先进的文献,提出了一个工具包,该工具包将计算建模用于各种干预措施和城市设计过程。我们从数据库中检索到的8737项研究中选择了109项,并根据病原体类型、传播模式和阶段、设计干预和过程以及建模方法(方法、目标、动机、重点和城市设计指标)对其进行了分析。我们还探讨了传染病与城市设计之间的关系,以及计算建模支持,包括特定的模型和参数。拟议的工具包将帮助设计师、规划者和计算机建模者根据目标疾病、地理环境、设计阶段以及空间和时间尺度,选择相关的方法来评估设计决策。本文的研究结果可以被视为独立的工具,特别是用于抗击新冠肺炎,也可以被纳入更广泛的框架,以帮助城市增强对未来灾难的抵御能力。
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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来源期刊
CiteScore
10.70
自引率
1.60%
发文量
26
审稿时长
34 days
期刊介绍: Progress in Planning is a multidisciplinary journal of research monographs offering a convenient and rapid outlet for extended papers in the field of spatial and environmental planning. Each issue comprises a single monograph of between 25,000 and 35,000 words. The journal is fully peer reviewed, has a global readership, and has been in publication since 1972.
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