2021
Zhang, Junyi; Feng, Tao; Kang, Jing; Li, Shuangjin; Liu, Rui; Ma, Shuang; Zhai, Baoxin; Zhang, Runsen; Ding, Hongxiang; Zhu, Taoxing
“What should be computed” for supporting post-pandemic recovery policy making? A life-oriented perspective Journal Article
In: Computational Urban Science , vol. 1, no. 24, pp. 1-16, 2021.
Abstract | Links | BibTeX | Tags: Computation, COVID-19 pandemic
@article{@ZHANG2021URBANCOMPUTATION,
title = {“What should be computed” for supporting post-pandemic recovery policy making? A life-oriented perspective},
author = {Junyi Zhang and Tao Feng and Jing Kang and Shuangjin Li and Rui Liu and Shuang Ma and Baoxin Zhai and Runsen Zhang and Hongxiang Ding and Taoxing Zhu },
url = {https://link.springer.com/content/pdf/10.1007/s43762-021-00025-8.pdf},
doi = {doi.org/10.1007/s43762-021-00025-8},
year = {2021},
date = {2021-11-19},
urldate = {2021-11-19},
journal = {Computational Urban Science },
volume = {1},
number = {24},
pages = {1-16},
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.},
keywords = {Computation, COVID-19 pandemic},
pubstate = {published},
tppubtype = {article}
}
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.