江西省新型冠状病毒肺炎疫情时空演化与影响因素

高兴; 李钢; 王皎贝; 徐婷婷; 张晓涵; 宁乾

doi:10.16462/j.cnki.zhjbkz.2021.04.008

江西省新型冠状病毒肺炎疫情时空演化与影响因素

doi: 10.16462/j.cnki.zhjbkz.2021.04.008

710127 西安，西北大学城市与环境学院经济地理与规划系，陕西省地表系统与环境承载力重点实验室

基金项目:

西北大学防治新型冠状病毒肺炎紧急科研专项引导基金 2020

西北大学"仲英青年学者"支持计划 2016

详细信息

通讯作者:
李钢，E-mail: lig@nwu.edu.cn

中图分类号: K901
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出版历程
- 收稿日期: 2020-06-26
- 修回日期: 2020-11-28
- 网络出版日期: 2021-05-11
- 刊出日期: 2021-04-10

Spatiotemporal evolution and influencing factors of coronavirus disease 2019 in Jiangxi Province

College of Urban and Environmental Sciences, Northwest University, Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, Xi′an 710127, China

Funds:

Key Project of the Special Guidance Fund for Emergency Study on the Prevention and Treatment of COVID-19 by Northwest University 2020

Tang Scholar Program of Northwest University 2016

More Information

Corresponding author: LI Gang, E-mail: lig@nwu.edu.cn

摘要

摘要: 目的分析江西省COVID-19疫情的流行病学特征、时空演化及影响因素。方法采用文本分析法提取流行病学信息，使用ArcGIS 10.3软件绘制疫情演化图谱、空间分析方法探讨疫情时空分布特征、偏最小二乘法(partial least square, PLS)分析疫情分布的影响因素。结果江西累计确诊930例，中青年(31~55岁)最多，占总数的60.40%，主要从事于服务业、务工及职工；依据活动轨迹与接触史可划分为输入型、混合型和扩散型3个感染群体，扩散型感染者占总体的85.48%；疫情发展可划分为外源输入型增长期、省内扩散型增长期和内外控制型稳定期3个阶段，疫情空间分布呈“西南-东北”走向和“赣北重于赣中赣南、南昌-新余两极突出”的格局；人口聚集程度、同外界交流互通的强度、与疫情重灾区的距离是影响疫情分布的主要因素。结论江西省COVID-19确诊病例性别分布均衡，中青年、服务业从事人员为主要群体；时间上“先快后慢”，空间上异质性显著；人口聚集程度、流动强度及总体疫情格局是影响疫情分布的关键。
- 新型冠状病毒肺炎 /
- 流行病学特征 /
- 时空演化 /
- 影响因素 /
- 江西省
Abstract: Objective To analyze the epidemiological characteristics, spatiotemporal evolution and influencing factors of coronavirus disease 2019 (COVID-19) in Jiangxi Province. Methods Text analysis was used to extract epidemiological information, ArcGIS 10.3 was performed to capture the evolution, spatial analysis method was applied to explore the spatiotemporal characteristics, and Partial Least Square (PLS) estimation was used to analyze the influencing factors of the epidemic distribution. Results In Jiangxi Province, 930 cases have been confirmed in total, with young and middle-aged people accounting for the most (60.40%), and the service industry, migrant workers and labors accounted for the largest proportion. According to the activity track and contact history, the cases can be divided into three types: imported, mixed and diffuse. The diffuse cases account for 85.48% of the total. The development of the epidemic can be divided into three stages: import period, diffusion period and control period. The spatial distribution of the epidemic showed the pattern of "southwest-northeast" and "the northern part of Jiangxi was more heavily affected than the southern and middle part of Jiangxi, with high primary ratio in Nanchang-Xinyu". Population concentration, the intensity of communication and the distance from the worst-hit area were the main factors affecting the distribution of the epidemic. Conclusions The gender distribution of confirmed cases was balanced, with young and middle-aged people as the main group. The epidemic had great influence on service industry. The epidemic developed with the pattern of "rapid increase followed by slow decrease", and with significant spatial heterogeneity. Population concentration and mobility as well as the overall epidemic pattern were the key factors affecting the epidemic distribution.
- COVID-19 /
- Epidemiological characteristics /
- Spatiotemporal evolution /
- Influencing factors /
- Jiangxi Province

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图 1 2020年江西省确诊病例性别年龄特征

Figure 1. Gender and age structure of confirmed cases in Jiangxi Province in 2020

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图 2 2020年江西省确诊病例职业特征(a职业分工；b服务行业类型)

Figure 2. Occupation characteristics of confirmed cases in Jiangxi Province in 2020 (a: professional division of labor; b: type of service industry)

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图 3 2020年江西省确诊病例时空演化

Figure 3. Spatial evolution of confirmed cases in Jiangxi Province in 2020

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图 4 2020年江西省疫情分布空间分析

Figure 4. Spatial analysis of epidemic distribution in Jiangxi Province in 2020

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表 1 2020年江西省确诊病例的感染群体类型及感染途径[n(%)]

Table 1. Classification of infection population and infection patterns of confirmed cases in Jiangxi Province in 2020 [n(%)]

感染群体类型及感染途径	例数
输入型	98(10.54)
工作感染	69(7.42)
生活感染	12(1.29)
服务感染	9(0.97)
亲属感染	3(0.32)
过渡型	37(3.98)
接触武汉返乡人员	3(0.32)
短期前往武汉	13(1.40)
亲属从武汉返乡	6(0.65)
途经武汉	3(0.32)
扩散型	795(85.48)
接触确诊病例	117(12.58)
医护人员	9(2.04)
接触医护人员	18(1.94)
聚集性活动	8(0.86)
接触外省返乡人员	6(0.64)
不能确定	627(67.42)

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表 2 2020年江西省COVID-19疫情空间分布的影响因素选取

Table 2. Influencing factors selection of COVID-19 spatial distribution in Jiangxi Province in 2020

类别	影响因素	作用	与确诊病例数Pearson相关系数	P值
人口	人口密度(人·km^-2)	人口密度	0.599	0.051
	男性占比(%)	性别结构	0.228	0.500
	城镇人口比(%)	城乡结构	0.257	0.445
	15~64岁占比(%)	年龄结构	0.590	0.056
经济	一般公共预算收入(万元)	收入水平	0.810	0.003
	第三产业占比(%)	产业结构	0.380	0.301
	个体劳动者(人)	职业分工	0.391	0.235
交通	公共交通客运总量(万人)	通达性	0.757	0.007
与武汉距离	铁路里程(km)	近邻性	-0.527	0.096

下载: 导出CSV

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