| 中国人口流动管控应对COVID-19疫情效应评估 |
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| 引用本文： | 赵梓渝,韩钟辉,魏冶,王士君.中国人口流动管控应对COVID-19疫情效应评估[J].地理学报,2022,77(2):426-442. |
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| 作者姓名： | 赵梓渝 韩钟辉 魏冶 王士君 |
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| 作者单位： | 1.青岛大学旅游与地理科学学院,青岛 2660712.中国海洋大学管理学院,青岛 2661003.东北师范大学地理科学学院,长春 130024 |
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| 基金项目： | 国家自然科学基金项目(41630749,42001176)；;教育部人文社会科学研究青年基金(20YJCZH241)；;山东省自然科学基金青年项目(ZR2020QD009)~~； |
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| 摘 要： | 中国政府通过历史罕见的人口流动管控遏制新型冠状病毒肺炎（COVID-19）疫情爆发。人口流动管控措施对于疫情防控起到何种作用?又如何影响中国人口流动和短期分布的地理特征?本文通过SEIR病毒传播动力学模型评估管控措施的有效性,利用移动定位数据追踪中国人口流动时空变化,以回顾COVID-19重大疫情人口流动管控的正负效应：① 人口流动管控使COVID-19疫情日新增感染曲线显著平稳化,成为中国应对COVID-19疫情重大突发性公共卫生事件时非药物干预措施的重要组成部分。人口流动管控使中国日新增感染者波峰日推迟1.9倍到达,当日感染人数下降63.4%。在选取的5个省份、5个湖北省城市、6个湖北外城市中,波峰日分别推迟1.4~8倍、5.6~16.7倍和2.3~7.2倍到达,当日感染人数分别下降56.9%~85.5%、62.2%~89.2%和67.1%~86.2%。因此,人口流动管控为疫情防控准备争取了宝贵的缓冲时间,极大降低了疫情集中爆发对于医疗设施的冲击;② 人口流动管控限制人口地级流动。2020年1—4月中国人口地级行政区划之间流动强度较2019年同期日均下降40.18%,其中,2020年“春运”节后返工流（1月25日—2月18日）平均下降66.4%,对社会运行与经济发展产生重大影响;③ 人口流动管控与人们对于疫情的恐惧导致2020年中国农历春节的返乡流受到显著影响,并短期改变中国人口时空分布的动态趋势。本文有助于理解重大突发性公共卫生事件下政府人口流动管控策略及其对人口流动与分布地理特征的影响。
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| 关 键 词： | COVID-19 交通管制 人口流动 SEIR模型 人口地理学 中国 |
| 收稿时间： | 2020-10-09 |
| 修稿时间： | 2021-06-09 |
Effect of population flow control in restraining COVID-19 in China |
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| ZHAO Ziyu,HAN Zhonghui,WEI Ye,WANG Shijun.Effect of population flow control in restraining COVID-19 in China[J].Acta Geographica Sinica,2022,77(2):426-442. |
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| Authors: | ZHAO Ziyu HAN Zhonghui WEI Ye WANG Shijun |
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| Institution: | 1. School of Tourism and Geography Science, Qingdao University, Qingdao 266071, Shandong, China2. School of Management, Ocean University of China, Qingdao 266100, Shandong, China3. School of Geographical Sciences, Northeast Normal University, Changchun 130024, China |
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| Abstract: | The Chinese government has curbed the rapid transmission of COVID-19 through a population flow control rarely seen in history. What is the effect of population flow control on pandemic prevention and control? How does it affect China's population mobility and short-term population distribution? In this paper, an SEIR model of virus transmission dynamics is used to evaluate the effectiveness of the control measures, and mobile location data are employed to track the temporal and spatial changes of population mobility in China, in order to review the positive and negative effects of population flow control during the major outbreaks of COVID-19: (1) Population flow control has significantly stabilized the daily new infection, serving as an essential part of China's non-pharmacological intervention measures in response to major public emergencies of COVID-19. Population flow control postponed the arrival of the peak day of daily new infections in China by 1.9 times, and reduced the number of newly infected people on that day by 63.4%. In the selected 5 provinces, 5 cities in Hubei, and 6 cities outside Hubei, the peak days were postponed by 1.4-8 times, 5.6-16.7 times, and 2.3-7.2 times, respectively, and the number of newly infected people on that day was reduced by 56.9%-85.5%, 62.2%-89.2%, and 67.1%-86.2%, respectively. Therefore, population flow control bought valuable buffer time for the prevention and control of the pandemic, and greatly weakened the impact of concentrated transmissions on medical facilities. (2) Population flow control limited intercity population flow. From January to April 2020, the average daily population flow intensity in China decreased by 40.18% compared with the same period in 2019. In particular, the coming-back-to-work flow after the Spring Festival travel rush in 2020 (from January 25 to February 18) decreased by 66.4% on average. (3) Population flow control and people's fear of the pandemic greatly affected the Spring Festival travel rush in 2020, and the spatial and temporal and distribution of China's population was changed for a short period. This paper helps the understanding of the impact of the population flow control strategy introduced by the government on major public emergencies, as well as the influences of geographical characteristics upon on the population flow and distribution. |
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| Keywords: | COVID-19 traffic control population flow SEIR model population geography China |
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