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Epidemic versus economic performances of the COVID-19 lockdown: A big data driven analysis
Lockdown measures have been a “panacea” for pandemic control but also a violent “poison” for economies. Lockdown policies strongly restrict human mobility but mobility reduce does harm to economics. Governments meet a thorny problem in balancing the pros and cons of lockdown policies, but lack compr...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Published by Elsevier Ltd.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8531026/ https://www.ncbi.nlm.nih.gov/pubmed/34703071 http://dx.doi.org/10.1016/j.cities.2021.103502 |
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author | Zhang, Haoran Li, Peiran Zhang, Zhiwen Li, Wenjing Chen, Jinyu Song, Xuan Shibasaki, Ryosuke Yan, Jinyue |
author_facet | Zhang, Haoran Li, Peiran Zhang, Zhiwen Li, Wenjing Chen, Jinyu Song, Xuan Shibasaki, Ryosuke Yan, Jinyue |
author_sort | Zhang, Haoran |
collection | PubMed |
description | Lockdown measures have been a “panacea” for pandemic control but also a violent “poison” for economies. Lockdown policies strongly restrict human mobility but mobility reduce does harm to economics. Governments meet a thorny problem in balancing the pros and cons of lockdown policies, but lack comprehensive and quantified guides. Based on millions of financial transaction records, and billions of mobility data, we tracked spatio-temporal business networks and human daily mobility, then proposed a high-resolution two-sided framework to assess the epidemiological performance and economic damage of different lockdown policies. We found that the pandemic duration under the strictest lockdown is less about two months than that under the lightest lockdown, which makes the strictest lockdown characterize both epidemiologically and economically efficient. Moreover, based on the two-sided model, we explored the spatial lockdown strategy. We argue that cutting off intercity commuting is significant in both epidemiological and economical aspects, and finally helped governments figure out the Pareto optimal solution set of lockdown strategy. |
format | Online Article Text |
id | pubmed-8531026 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Published by Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-85310262021-10-22 Epidemic versus economic performances of the COVID-19 lockdown: A big data driven analysis Zhang, Haoran Li, Peiran Zhang, Zhiwen Li, Wenjing Chen, Jinyu Song, Xuan Shibasaki, Ryosuke Yan, Jinyue Cities Article Lockdown measures have been a “panacea” for pandemic control but also a violent “poison” for economies. Lockdown policies strongly restrict human mobility but mobility reduce does harm to economics. Governments meet a thorny problem in balancing the pros and cons of lockdown policies, but lack comprehensive and quantified guides. Based on millions of financial transaction records, and billions of mobility data, we tracked spatio-temporal business networks and human daily mobility, then proposed a high-resolution two-sided framework to assess the epidemiological performance and economic damage of different lockdown policies. We found that the pandemic duration under the strictest lockdown is less about two months than that under the lightest lockdown, which makes the strictest lockdown characterize both epidemiologically and economically efficient. Moreover, based on the two-sided model, we explored the spatial lockdown strategy. We argue that cutting off intercity commuting is significant in both epidemiological and economical aspects, and finally helped governments figure out the Pareto optimal solution set of lockdown strategy. Published by Elsevier Ltd. 2022-01 2021-10-22 /pmc/articles/PMC8531026/ /pubmed/34703071 http://dx.doi.org/10.1016/j.cities.2021.103502 Text en © 2021 Published by Elsevier Ltd. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Zhang, Haoran Li, Peiran Zhang, Zhiwen Li, Wenjing Chen, Jinyu Song, Xuan Shibasaki, Ryosuke Yan, Jinyue Epidemic versus economic performances of the COVID-19 lockdown: A big data driven analysis |
title | Epidemic versus economic performances of the COVID-19 lockdown: A big data driven analysis |
title_full | Epidemic versus economic performances of the COVID-19 lockdown: A big data driven analysis |
title_fullStr | Epidemic versus economic performances of the COVID-19 lockdown: A big data driven analysis |
title_full_unstemmed | Epidemic versus economic performances of the COVID-19 lockdown: A big data driven analysis |
title_short | Epidemic versus economic performances of the COVID-19 lockdown: A big data driven analysis |
title_sort | epidemic versus economic performances of the covid-19 lockdown: a big data driven analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8531026/ https://www.ncbi.nlm.nih.gov/pubmed/34703071 http://dx.doi.org/10.1016/j.cities.2021.103502 |
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