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  • 标题:“What should be computed” for supporting post-pandemic recovery policymaking? A life-oriented perspective
  • 本地全文:下载
  • 作者:Junyi Zhang ; Tao Feng ; Jing Kang
  • 期刊名称:Computational Urban Science
  • 电子版ISSN:2730-6852
  • 出版年度:2021
  • 卷号:1
  • 期号:1
  • 页码:1-16
  • DOI:10.1007/s43762-021-00025-8
  • 语种:English
  • 出版社:Springer
  • 摘要:Abstract The COVID-19 pandemic has caused various impacts on people’s lives, while changes in people’s lives have shown mixed effects on mitigating the spread of the SARS-CoV-2 virus. Understanding how to capture such two-way interactions is crucial, not only to control the pandemic but also to support post-pandemic urban recovery policies. As suggested by the life-oriented approach, the above interactions exist with respect to a variety of life domains, which form a complex behavior system. Through a review of the literature, this paper first points out inconsistent evidence about behavioral factors affecting the spread of COVID-19, and then argues that existing studies on the impacts of COVID-19 on people’s lives have ignored behavioral co-changes in multiple life domains. Furthermore, selected uncertain trends of people’s lives for the post-pandemic recovery are described. Finally, this paper concludes with a summary about “what should be computed?” in Computational Urban Science with respect to how to catch up with delays in the SDGs caused by the COVID-19 pandemic, how to address digital divides and dilemmas of e-society, how to capture behavioral co-changes during the post-pandemic recovery process, and how to better manage post-pandemic recovery policymaking processes.
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