地球信息科学学报 ›› 2015, Vol. 17 ›› Issue (5): 614-621.doi: 10.3724/SP.J.1047.2015.00614

• 地理空间分析综合应用 • 上一篇    下一篇

2004-2013年间中国登革热疫情时空变化分析

宁文艳1,3, 鲁亮1,3, 任红艳2, 刘起勇1,3   

  1. 1. 中国疾病预防控制中心传染病预防控制所媒介生物控制室, 传染病预防控制国家重点实验室, 北京102206;
    2. 中国科学院地理科学与资源研究所, 北京100101;
    3. 感染性疾病诊治协同创新中心, 杭州310003
  • 收稿日期:2014-06-30 修回日期:2014-12-07 出版日期:2015-05-10 发布日期:2015-05-10
  • 通讯作者: 鲁亮(1970-),男,江苏无锡人,博士,研究员,主要从事病媒生物学和控制研究。E-mail:luliang@icdc.cn E-mail:luliang@icdc.cn
  • 作者简介:宁文艳(1990-),女,河南驻马店人,硕士生,主要从事气候变化对登革热影响研究。E-mail:ningjing0423@163.com
  • 基金资助:

    国家重大科学研究计划"973"项目(2012CB955501、2012CB955504)。

Spatial and Temporal Variations of Dengue Fever Epidemics in China from 2004 to 2013

NING Wenyan1,3, LU Liang1,3, REN Hongyan2, LIU Qiyong1,3   

  1. 1. State Key Laboratory for Infectious Disease Prevention and Control, Department of Vector Biology and Control, National Institute for Communicable Disease Control and prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China;
    2. Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;
    3. Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou 310003, China
  • Received:2014-06-30 Revised:2014-12-07 Online:2015-05-10 Published:2015-05-10

摘要:

通过对登革热疫情分布及时空变化的分析,发现该病的分布和流行规律,将有助于登革热防控工作的开展。本文以2004-2013年间传染病网络直报系统的全国地市级登革热逐月发病率资料为基础,就发病率、涉及地市以及与输入性病例之间的关系,进行空间统计学分析。结果表明:中国登革热发病率的对数值与国外输入性病例数呈显著相关(r=0.669,p<0.05);登革热输入性病例地市(有输入性病例的地市)数量与登革热本地病例地市(有登革热本地病例的地市)数量呈显著线性相关(r=0.939,p<0.05);疫情整体呈稳步递增的趋势,且发病率重心不稳定,从东南沿海(广东、福建)逐步向内陆和西南地区(云南边界)迁移,显示登革热可能流行范围正在扩大;中国登革热疫情呈现波动性非随机空间分布,其高聚集区主要分布在广东的珠江三角洲、韩江三角洲,以及西南边境的云南德宏傣族景颇族自治州和西双版纳傣族自治州。中国登革热疫情是由输入性病例引起的本地流行,因此,加强入境人员(特别是来自东南亚疫区)的健康教育,尤其在输入性病例输入高风险时间段(7-10月),对控制登革热疫情有重要意义。

关键词: 时空变化, 空间分析, 中国, 登革热

Abstract:

Dengue fever is an acute insect-borne disease transmitted by the Aedes mosquito, which is a class B infectious disease in China. Understanding the variations occurred in the spatial and temporal distribution of dengue fever epidemics will bring improvements to dengue fever prevention and control. In this study, monthly incidence data for dengue fever at municipality level across China were analyzed for the period from 2004 to 2013. The relationships between the incidence rates of dengue fever, the involved municipalities, and the imported cases were determined. The geographic pattern of dengue fever incidence rates was examined by GIS, spatial autocorrelation analysis and from the tracks of the centre of mass. Results showed that: (i) annually, the incidence rates for indigenous dengue fever cases exhibited the highest values between August and October, while the imported cases peaked between July and October. (ii) The logarithmic values of indigenous dengue fever cases was significantly correlated with the numbers of imported cases (r=0.669, p<0.05), while the number of municipalities with imported cases was linearly correlated to the number of all municipalities that have dengue fever cases (r=0.939, p<0.05). (iii) In addition to the increasing incidence rate, the dengue fever epidemic was affecting an increasing number of municipalities. The range of the epidemic was steadily increasing and gradually spreading toward inland area from the southeastern coast. (iv) Dengue fever cases did not distributed randomly with respect to time and geographical space. The highest density occurred in areas of Pearl River Delta, Hanjiang River Delta, Dehong prefecture, and Xishuangbanba prefecture. The centre of mass of dengue fever incidence rates was not stable and moved from the southeast coast (Fujian and Guangdong provinces) to the southwest (border of Yunnan province), which revealed the changes of the dengue fever distribution pattern. Our results indicate that the dengue fever epidemic in China is driven by imported cases from other countries. According to the temporal and spatial characteristics of the increasing incidence rates at municipality level and the expanding range of dengue fever in China, a stronger border inspection for people entering from abroad, especially from Southeast Asia and during the peak epidemic months between July and October, may be effective in preventing the spread of this rising epidemic.

Key words: spatial analysis, China, dengue fever, spatial and temporal variation