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新冠政策分析:劳动力结构决定封锁期间的流动行为。

COVID-19 policy analysis: labour structure dictates lockdown mobility behaviour.

机构信息

The Bartlett Centre for Advanced Spatial Analysis, University College London, London W1 4TJ, UK.

Mathematical Institute, University of Oxford, Radcliffe Observatory Quarter, Woodstock Road, Oxford OX2 6GG, UK.

出版信息

J R Soc Interface. 2021 Mar;18(176):20201035. doi: 10.1098/rsif.2020.1035. Epub 2021 Mar 31.

Abstract

Countries and cities around the world have resorted to unprecedented mobility restrictions to combat COVID-19 transmission. Here we exploit a natural experiment whereby Colombian cities implemented varied lockdown policies based on ID number and gender to analyse the impact of these policies on urban mobility. Using mobile phone data, we find that the restrictiveness of cities' mobility quotas (the share of residents allowed out daily according to policy advice) does not correlate with mobility reduction. Instead, we find that larger, wealthier cities with more formalized and complex industrial structure experienced greater reductions in mobility. Within cities, wealthier residents are more likely to reduce mobility, and commuters are especially more likely to stay at home when their work is located in wealthy or commercially/industrially formalized neighbourhoods. Hence, our results indicate that cities' employment characteristics and work-from-home capabilities are the primary determinants of mobility reduction. This finding underscores the need for mitigations aimed at lower income/informal workers, and sheds light on critical dependencies between socio-economic classes in Latin American cities.

摘要

世界各地的国家和城市都采取了前所未有的行动限制来对抗 COVID-19 的传播。在这里,我们利用了一个自然实验,即哥伦比亚城市根据身份证号码和性别实施了不同的封锁政策,以分析这些政策对城市流动性的影响。使用移动电话数据,我们发现城市流动性配额(根据政策建议允许外出的居民的比例)的严格程度与流动性减少无关。相反,我们发现规模较大、更富裕、产业结构更正式和复杂的城市流动性减少幅度更大。在城市内部,较富裕的居民更有可能减少流动性,当他们的工作位于富裕或商业/工业正式化的社区时,通勤者尤其更有可能呆在家里。因此,我们的结果表明,城市的就业特征和在家工作的能力是流动性减少的主要决定因素。这一发现强调了需要针对低收入/非正规工人采取缓解措施,并揭示了拉丁美洲城市中社会经济阶层之间的关键依存关系。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d3ae/8098708/f30c3bc16577/rsif20201035f01.jpg

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