引用本文:梁泽,王玥瑶,孙福月,等.我国城市新冠肺炎发病率的地理分布格局:人口迁徙与社会经济因素的影响[J].环境科学研究,2020,33(7):1571-1578.
LIANG Ze,WANG Yueyao,SUN Fuyue,et al.Geographical Pattern of COVID-19 Incidence of China's Cities: Role of Migration and Socioeconomic Status[J].Research of Environmental Sciences,2020,33(7):1571-1578.]
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我国城市新冠肺炎发病率的地理分布格局:人口迁徙与社会经济因素的影响
梁泽1,2, 王玥瑶1,2, 孙福月1,2, 梁琛瑜1,2, 李双成1,2
1. 北京大学城市与环境学院, 北京 100871;2. 北京大学地表过程分析与模拟教育部重点实验室, 北京 100871
摘要:
新型冠状病毒肺炎(COVID-19,简称“新冠肺炎”)疫情的暴发使我国城市系统面临严峻挑战.认识城市尺度新冠肺炎发病率的地理空间分布格局及影响因素,可以为面向公共卫生安全的城市发展提供参考.以我国282个城市作为基本研究单元,通过地理加权回归模型,探究了2020年1月1日—3月5日我国城市人口迁徙与社会经济因素对新冠肺炎发病率的影响.结果表明:①地理加权回归模型的解释力(整体R2=0.40)显著高于传统的普通最小二乘法线性回归模型(整体R2=0.02).②武汉迁入率较大地增加了武汉周边城市的新冠肺炎发病率,该效应随着与武汉地理距离的增加呈现空间衰减特征,东北和西南部分地区除外.③高人均地区生产总值在东南经济较发达地区对新冠肺炎发病率的控制起到了重要作用.④人均绿地面积和人均医务人员数量指标的提升仅在全国少部分地区显示出积极作用,其中不包括武汉周边城市.相反,人均公共财政支出对于武汉周边地区新冠肺炎发病率的控制起到了重要作用.研究显示,我国城市的新冠肺炎发病率及其与人口迁徙/城市社会经济指标的关系具有明显的空间依赖模式,其中来自武汉的人口流入、公共财政支出和绿化水平的影响均呈现一定的空间衰减特征,而经济发展水平的影响则呈现地域性依赖特征.
关键词:  新型冠状病毒肺炎发病率  人口迁徙  社会经济因素  地理加权回归模型  空间自相关
DOI:10.13198/j.issn.1001-6929.2020.05.45
分类号:X24
基金项目:国家自然科学基金重大项目(No.41590843)
Geographical Pattern of COVID-19 Incidence of China's Cities: Role of Migration and Socioeconomic Status
LIANG Ze1,2, WANG Yueyao1,2, SUN Fuyue1,2, LIANG Chenyu1,2, LI Shuangcheng1,2
1. College of Urban and Environmental Sciences, Peking University, Beijing 100871, China;2. Key Laboratory for Earth Surface Processes of the Ministry of Education, Peking University, Beijing 100871, China
Abstract:
The outbreak of COVID-19 challenged China's urban system. Exploring the spatial pattern and influencing factors of the incidence of COVID-19 (PRcovid) at the city level can provide insights into urban sustainable development. The purpose of this paper is to explore the spatial heterogeneity of the relationship between the incidence of COVID-19 and population migration and socioeconomic factors in Chinese cities. Based on the geographically weighted regression (GWR) model, we analyzed the impact of the migration rate of all other cities across the country (MRall), migration rate of Wuhan (MRwuhan), GDP per capita (GDPPC), green area per capita (GApc), number of medical staff per capita (NMSpc) and public expenditure per capita (PEpc) on the PRcovid in 282 cities in China. The results show that: (1) The explanatory power of GWR model on PRcovid(overall R2=0.40) was significantly higher than that of ordinary least squares linear regression model (overall R2=0.02). (2) The impact of MRwuhan decreased with increasing distance from Wuhan, except for parts of Northeast and Southwest China. (3) GDPpc played a positive role in controlling the PRcovid in the more developed southeast region. (4) The indicators of GApc and NMSpc only effected positively in small parts of the country, excluding cities around Wuhan. In contrast, PEpc played a key role in controlling the PCcovid in the surrounding areas of Wuhan. In conclusion, the incidence of COVID-19 in Chinese cities and its relationship with migration / urban socioeconomic indicators showed clear spatial patterns. The impact of migration, public investment and urban greening all followed a certain spatial attenuation pattern from Wuhan, while the impact of economic level is regional-dependent.
Key words:  incidence of COVID-19  population migration  socioeconomic factors  geographic weighted regression model  spatial autocorrelation