自然科学版
陕西师范大学学报(自然科学版)
新型冠状病毒肺炎研究专题
深圳市新型冠状病毒肺炎(COVID-19)疫情时空演化与防控对策
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金安楠1,李钢1,2,3*,王皎贝1,徐婷婷1,于悦1,胡志恒1,杨佳辰1
(1 西北大学 城市与环境学院,陕西 西安 710127;2 陕西省地表系统与环境承载力重点实验室,陕西 西安 710127;3 西北大学 地表系统与灾害研究院,陕西 西安 710127)
李钢,男,教授,博士生导师,主要研究方向为人地关系与空间安全、灾害地理与犯罪地理。E-mail:lig@nwu.edu.cn
摘要:
开展个体人群水平的新型冠状病毒肺炎(COVID-19)疫情时空扩散研究,有助于疫情防控和资源配置。以距离中国疫情始发地武汉较远但疫情高发的深圳市为研究区,基于官方公布的确诊病例数据、人工判读采集的病例详情及城市内部相关POI数据等,综合运用文本分析、数理统计、空间分析等方法,解析深圳市COVID-19确诊病例的流行病学特征和疫情的时空演化过程,综合探索疫情防控对策。结果表明:(1)确诊病例总体覆盖全年龄段,主要集中于青壮年,多源于外地感染和2代感染,以家庭集聚型传播居多,以跨省市的“线形”迁移扩散模式为主。(2)疫情时间演变经历“低发期—增长期—减缓期—尾声期”4个发展阶段;治愈病例数呈现“由缓增到快增”的演变过程;确诊病例自发病至入院时间间隔多为0~2 d,入院至确诊时间间隔集中为1~3 d。(3)空间分布上,确诊病例主要表现为“由湖北直达”与“经湖北停留”的空间迁移类型,出行目的以春节探亲为主;疫情小区空间布局呈“东北-西南”走向,主要围绕“两核”集聚于西南片区。(4)市域风险总体呈现“两核三片”分布,高风险地区位于南山区南部和福田区中心。最后结合疫情所处阶段特点、复工复产需要和境外输入等新风险,提出了基于“实时、日常、常态”“社区、片区、市域”“个体、家庭、社会”的“时-空-人”互馈协同精准防控对策体系。
关键词:
COVID-19;重大疫情;时空演化;防控对策;深圳市
收稿日期:
2020-04-01
中图分类号:
R181.8;K901
文献标识码:
A
文章编号:
1672-4291(2020)03-0018-15
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重点项目(2020);西北大学“仲英青年学者”支持计划(2016);西北大学特色优势科研团队建设项目(2019)
Doi:
Spatio-temporal evolution and control strategies of COVID-19 epidemic in Shenzhen, China
JIN Annan1, LI Gang1, 2, 3 *, WANG Jiaobei1, XU Tingting1, YU Yue1, HU Zhiheng1, YANG Jiachen1
(1 College of Urban and Environmental Sciences, Northwest University, Xi′an 710127, Shaanxi, China; 2 Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, Xi′an 710127, Shaanxi, China; 3 Institute of Earth Surface System and Hazards, Northwest University, Xi′an 710127, Shaanxi, China)
Abstract:
The outbreak of COVID-19 at the end of 2019 is spreading around the world, causing serious impact on socio-economic development and human health and safety. Clarification of the spatial-temporal spread of COVID-19 at individual and population levels is necessary for epidemic prevention and control as well as resource allocation. This study targeted on Shenzhen city which locates far away from the COVID-19 origin city of Wuhan but experienced high incidence of COVID-19. Based on the officially published and confirmed cases, manually collected case details and the related POI data of Shenzhen, the epidemiological characteristics, spatio-temporal evolution and prevention and control measures regarding COVID-19 in Shenzhen were analyzed through text analysis, mathematical statistics, spatial analysis and other methods. The results showed that: (1)the confirmed COVID-19 cases covered all age levels, mainly concentrated in the young adults. Most of them were the second generation of infection originating from the places out of Shenzhen, and they were mainly from family cluster transmission with “linear” migration and diffusion mode between cities. (2)The time evolution of epidemic experienced 4 stages: low incidence period, growing period, deceleration period and ending period. The number of cured cases presented the evolution process from slow growth to rapid growth. The time interval from onset to admission was mostly within 0~2 days, and the time interval from admission to diagnosis was about 1~3 days. (3)In terms of spatial distribution, the confirmed cases moved out mainly through two types: “directly from Hubei” and “stop by Hubei”, with the main purpose of visiting relatives during the Spring Festival. The spatial distribution of COVID-19 affected communities demonstrated “northeast to southwest” trend, mainly gathered in the southwest part around the “two cores”.(4)The overall risk distribution of the city was “two cores and three areas”. The high-risk areas were located in the south of Nanshan District and in the center of Futian District. Finally, combined with the situation of COVID-19, requirement of work recovery and the new risk from overseas, this study put forward an accurate prevention and control measure system based on the dimensions of “real-time, daily, normal”, “community, district, city” and “individual,family,society” from the perspective of “time-space-human” mutual feedback and integration.
KeyWords:
COVID-19; major epidemic disease; spatio-temporal evolution; control measures; Shenzhen