地球信息科学学报 ›› 2020, Vol. 22 ›› Issue (12): 2371-2382.doi: 10.12082/dqxxkx.2020.190511

• 地理空间分析综合应用 • 上一篇    下一篇

森林脑炎时空分布特征和环境影响因素分析

宋海慧1,2(), 余卓渊1,2,*(), 丁晓彤1,2, 谢云鹏1,2, 吕可晶1,2   

  1. 1.中国科学院地理科学与资源研究所 资源与环境信息系统国家重点实验室,北京 100101
    2.中国科学院大学,北京 100049
  • 收稿日期:2019-09-10 修回日期:2019-12-20 出版日期:2020-12-25 发布日期:2021-02-25
  • 通讯作者: 余卓渊 E-mail:songhh.17s@igsnrr.ac.cn;yuzy@igsnrr.ac.cn
  • 作者简介:宋海慧(1994— ),女,甘肃武威人,硕士生,主要从事地理信息系统技术应用研究。E-mail: songhh.17s@igsnrr.ac.cn
  • 基金资助:
    国家重点研发计划项目课题(2018YFC1508805)

Spatial-temporal Distribution Characteristics and Environmental Impact Factors of Tick-borne Encephalitis

SONG Haihui1,2(), YU Zhuoyuan1,2,*(), DING Xiaotong1,2, XIE Yunpeng1,2, LV Kejing1,2   

  1. 1. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    2. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2019-09-10 Revised:2019-12-20 Online:2020-12-25 Published:2021-02-25
  • Contact: YU Zhuoyuan E-mail:songhh.17s@igsnrr.ac.cn;yuzy@igsnrr.ac.cn
  • Supported by:
    National Key Research and Development Program(2018YFC1508805)

摘要:

森林脑炎作为一种蜱传自然疫源性疾病,其空间分布与环境关系密切,探索其时空分布模式与环境因子对其影响机制对于掌握和预测森林脑炎的发病风险区域具有重要意义。本文以我国东北疫源区(黑龙江省、吉林省和内蒙古自治区)为研究区,通过统计分析和空间自相关分析探究了2005—2015年森林脑炎时空分布特征,进而运用地理探测器模型探讨森林脑炎空间分布影响因素及其指示作用。结果表明:① 研究区内森林脑炎发病率在2005—2015年有明显的增长趋势和季节性发病特征,且其发病率具有较强的空间集聚模式,主要有2个大的热点集聚区;② 从整个研究区来看,植被类型、土地利用、年均气温、土壤类型、5—8月均气温、坡度、高程和年均降雨量是森林脑炎发病率空间流行的主要环境影响因素;③ 对于所筛选的环境指示因子而言,各指示因子对森林脑炎发病风险的影响程度存在差异,即各因子的各类型(范围)内,森林脑炎发病率不同;各指示因子两两之间的相互作用对森林脑炎的发病风险具有显著增强效应。研究结果可为研究区及全国森林脑炎疫情的有效控制提供科学依据和决策支持。

关键词: 森林脑炎, 时空分布, 影响因素, 自然因素, 社会因素, 空间自相关, 地理探测器, 东北疫源区

Abstract:

Tick Borne Encephalitis (TBE) is an acute infectious disease involving central neuropathy caused by the bite of a Tick borne Encephalitis Virus (TBEV) infected tick, which is a typical zoonotic disease. TBE occurs in areas with a wide distribution of tick and its distribution is related to the environment. Besides, it is also a typically natural focus disease in a special ecosystem composed of pathogens, vectors, and host animals. As a natural focus disease, TBE threatens human health and impedes socioeconomic development in northeastern China. Therefore, analyzing the spatial-temporal distribution of TBE and its influencing factors are of vital importance for TBE control. This paper selected Heilongjiang Province, Jilin Province, and the Inner Mongolia Autonomous Region in northeastern China, which are typical TBE endemic areas, to study the spatial-temporal distribution of TBE and its influencing factors. Firstly, we explored the spatial-temporal distribution of TBE in the study area from 2005 to 2015 through statistical analysis and spatial autocorrelation, Secondly, we used Geo-Detector to investigate the factors that influence the spatial distribution of TBE and its indicative role. Our results show that: (1) the incidence of TBE in the endemic areas of Northeastern China had an obvious growth trend and seasonal incidence characteristics from 2005 to 2015. The incidence of TBE in the study area had a strong spatial clustering pattern with two main hot spots, Hulunbuir city in the Inner Mongolia autonomous region and the Greater Khingan Range region in Heilongjiang province; (2) vegetation type, land use, average annual temperature, soil type, average temperature from May to August, slope, elevation, and annual rainfall were the main influencing factors of spatial prevalence of TBE. In general, the influence of natural environment was stronger than that of social environmental; (3) for the whole study area, the relationship between each risk factor and TBE was different, and the incidence of TBE was different with each factor. Besides, the interaction between various factors was significantly enhanced, that is, the impact of two factors was stronger than that of a single factor. The common interaction between some factors exceeded 0.5, and most factors exceeded 0.3. Particularly, the main interaction enhancement effect was manifested in the interaction of each factor with land use and elevation. Our results provide scientific basis and decision support for the effective control of TBE in the study area and the whole country.

Key words: Tick-borne encephalitis, spatial-temporal distribution, environmental factor, natural factors, social factors, spatial autocorrelation analysis, geographical detector, northeast epidemic area