| 新冠肺炎疫情扩散与人口流动的空间关系及对中国城市公共卫生分类治理启示 |
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| 引用本文： | 向云波,王圣云.新冠肺炎疫情扩散与人口流动的空间关系及对中国城市公共卫生分类治理启示[J].热带地理,2020,40(3):408-421. |
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| 作者姓名： | 向云波 王圣云 |
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| 作者单位： | 1.湖南科技大学 建筑与艺术设计学院，湖南 湘潭 411201;2.南昌大学 中国中部经济社会发展研究中心，南昌 330047 |
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| 基金项目： | 教育部人文社会科学研究项目(20YJA790071);国家自然科学基金(41861025);江西省高校人文社会科学研究规划项目(JJ19118) |
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| 摘 要： | 人口流动影响新冠肺炎疫情传播与风险扩散。基于百度迁徙大数据和各省市区卫生健康委员会数据,结合地理信息技术,研究了2020年1月1日至3月5日136个城市新冠肺炎疫情扩散与武汉市人口流出的空间关系及其对我国城市公共卫生治理启示。研究表明:1)中国新冠肺炎疫情扩散过程具有阶段性特征,经历了疫情发生与隐性扩散、快速扩散与暴发、扩散遏制和扩散衰减4个阶段。2)研究时间段武汉市人口主要流向湖北省境内以及周边省市和北京、上海、广州、深圳等一线城市,具有地理邻近性和倾向区域中心城市的人口流入特征。受地理距离、时间成本、社会经济联系、境外输入等因素的影响,新冠肺炎疫情空间分布的不平衡性明显,长江中游城市群、京津冀城市群、长三角城市群、粤港澳大湾区和成渝城市群成为新冠肺炎疫情集中分布的重点区域,一些重点出入境口岸城市的新冠疫情扩散风险较大。3)新冠肺炎疫情扩散与人口流出之间具有较强的正向等级相关性。两者之间的空间关系可以分为8种调控类型,近90%的城市具有人口流入多、确诊病例数高或人口流入少、确诊病例数低的特征。其中,人口流入多、确诊病例数高的城市主要集中分布在湖北省境内以及中国重点城市群的中心城市,其防控压力来自人口流入多、确诊病例数高带来的疫情扩散风险;而人口流入少、确诊病例数低的城市分布较为分散,其防控的难点在于提高防控对策的精准性。我国疫情防控取得了显著成效,但随着时间的演进全球疫情形势反弹的不确定性仍然存在,外防输入、内防反弹的压力依然很重,现阶段乃至未来一段时期,疫情防控将伴随中国经济社会发展成为新常态。建议针对8种调控类型,从人口流动、交通和资源等引导与管控方面分类提出精细化的疫情防控策略,提升城市公共卫生治理能力。
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| 关 键 词： | 新冠肺炎疫情 人口流出 时间距离 空间关系 武汉市 |
| 收稿时间： | 2020-04-07 |
Spatial Relationship between Epidemic Spread and Population Outflow of the Corona Virus Disease 2019 (COVID-19) That Impacted Chinese Urban Public Health Classification |
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| Xiang Yunbo,Wang Shengyun.Spatial Relationship between Epidemic Spread and Population Outflow of the Corona Virus Disease 2019 (COVID-19) That Impacted Chinese Urban Public Health Classification[J].Tropical Geography,2020,40(3):408-421. |
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| Authors: | Xiang Yunbo Wang Shengyun |
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| Institution: | 1.School of Architecture and Art Design, Hunan University of Science and Technology, Xiangtan 411201, China;2.Center for Economic and Social Development in Central China of Nanchang University, Nanchang 330047, China |
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| Abstract: | Population mobility affects the spread of the new coronavirus and of risk. Based on Baidu migration big data and provinces and municipalities’ health committee data, combined with geographic information technology, this paper studies the spatial relationship between the spread of Corona Virus Disease 2019(COVID-19) in 136 cities from January 1st to March 5th, 2020, and the outflow of population in Wuhan, which impacted urban public health management in China. The following results were obtained. The spread of COVID-19 in China has the following stages and characteristics: occurrence and recessive spread, rapid spread and outbreak, diffusion containment, and diffusion attenuation. From January 1st to March 5th, 2020, it was observed that the population flow of Wuhan City mainly extends to the Hubei Province and its surrounding provinces and cities, as well as Beijing, Shanghai, Guangzhou, Shenzhen and other first-tier cities, with geographical proximity and characteristics similar to regional central city population inflow. Influenced by geographical distance, time cost, social and economic connection, overseas input, and so on, the spatial distribution of COVID-19 is evidently unbalanced. The urban agglomeration in the middle reaches of the Yangtze River, the Beijing-Tianjin-Hebei urban agglomeration, the Yangtze River Delta urban agglomeration, Guangdong-Hong Kong-Macau Greater Bay Area, and the Chengdu-Chongqing urban agglomeration have become key areas for the concentrated distribution of COVID-19. Additionally, some key entry and exit port cities present a higher risk of spreading. A strong positive grade correlation between epidemic spread and population outflow is observed with COVID-19. The spatial relationship between the two can be divided into eight regulation types. Nearly 90% of cities have the characteristics of large population inflow, high numbers of confirmed cases or small population inflow, and low numbers of confirmed cases. Among these, cities with large population inflow and high numbers of confirmed cases are mainly concentrated in the Hubei Province and central cities of key urban agglomerations in China. The pressure of prevention and control stems from the risk of epidemic spread, caused by a large population inflow and high number of confirmed cases. The urban distribution, with a small population inflow and low number of confirmed cases, is scattered, and the difficulty involved in prevention and control is the improvement of the precision of such countermeasures. Although China’s strategies for epidemic prevention and control have achieved remarkable results, considering the evolution of the global epidemic situation, rebound uncertainty still exists, and external defense input as well as internal defense rebound pressure are still very heavy. Currently, and in the future, the prevention and control of the epidemic situation will become the “new normal” with the economic and social development of our country. Improving the capacity for urban public health management is necessary for the prevention and control of the epidemic situation in China, especially in the future. Chinese epidemic prevention and control should still consider local conditions and formulate targeted prevention and control strategies. In particular, it is necessary to consider the relationship between the spread of COVID-19 and population flow, economic ties, transportation costs, international exchanges and other factors, and set specific classifications and control plans. To facilitate the joint prevention and control strategy to formulate full coverage, and “Not One Less,” we should not only approach the current epidemic prevention and control it from a dynamic perspective, but also consider epidemic prevention and control work in specific types of cities. Urban agglomeration areas and port cities often have a large population inflow, frequent economic ties, high economic development pressure, and high-risk epidemic prevention and control. They bear the dual responsibility of economic and social development, stability, epidemic prevention, and control and management. In the context of resuming production, work, and economic and social recovery, special attention should be paid to the regular prevention and control of the epidemic situation as well as the improvement of urban public health management capacities. |
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| Keywords: | Corona Virus Disease 2019(COVID-19) epidemic population outflow time distance spatial relationship Wuhan city |
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