Structural Changes in Human Mobility Under the Zero-COVID Strategy in China

城市化 TRIPS体系结构 中国 人口经济学 2019年冠状病毒病(COVID-19) 大流行 爆发 人均 人口 地理 业务 人口学 社会经济学 发展经济学 经济增长 经济 医学 环境卫生 运输工程 工程类 内科学 社会学 疾病 考古 病毒学 传染病(医学专业)
作者
Xiaoyan Mu,Xiaohu Zhang,Ago Yeh,Yu Yang,Jiejing Wang
出处
期刊:Environment And Planning B: Urban Analytics And City Science [SAGE]
卷期号:50 (9): 2527-2542 被引量:1
标识
DOI:10.1177/23998083231159397
摘要

Over the past two years, China has wrested domestic control of the COVID-19 pandemic through non-pharmaceutical interventions. However, the extent to which the pandemic has changed people’s travel behavior in the new normal under the zero-COVID policy is not yet clear. This study investigates the profound effects of the zero-COVID strategy on human mobility in 365 Chinese cities over time. Our results suggest the following: (1) Even between city pairs with no local cases, intercity mobility decreased by an average of 16%, whereas intra-city mobility increased by 9% compared with the pre-pandemic baseline. Long-distance travel decreased substantially, while trips below 100 km increased slightly. These new trends indicate a localized pattern which is presumably caused by the wide adoption of teleworking and virtual classes, as well as concerns about the safety and availability of public transportation. (2) Containment measures caused a considerably acute decline in intercity short-distance trips but exerted a markedly lasting effect on long-distance trips. (3) Cities with lower levels of urbanization, smaller population sizes, less labor force, and lower GDP and GDP per capita experienced greater reductions in mobility, which may be due to their insufficient management capabilities. (4) The Chinese government has adopted adaptive measures to contain outbreaks. Stricter and more timely responses led to faster recoveries in the second half of 2021 compared with the first half. Inter- and intra-city mobility decreased by 41% and 26%, respectively, within the first 2 weeks of an outbreak, and it took 6-7 weeks to return to pre-outbreak levels.
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