中国媒介生物学及控制杂志

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云南省中华按蚊、杰普尔按蚊种群与环境因素关系的地理信息系统分析

刘美德1;王学忠2;赵彤言1; 杜尊伟2; 董言德1; 李菊昇2; 朱礼华1; 陆宝麟1   

  1. 1军事医学科学院微生物流行病研究所病原微生物生物安全国家重点实验室 北京100071;2云南省寄生虫病防治所
  • 出版日期:2008-08-20 发布日期:2008-08-20

Geographic information system analysis on the relationship of populations of Anopheles sinensis and An.jeyporiensis with the environment factors in Yunnan province

LIU Mei-de*; WANG Xue-zhong; ZHAO Tong-yan; DU Zun-wei; DONGYan-de; LI Ju-sheng; ZHU Li-hua;LU Bao-lin   

  1. Beijing Institute of Microbiology of Epidemiology, State Key Laboratory of Pathogen and Biosecurity, Beijing 100071, China
  • Online:2008-08-20 Published:2008-08-20

摘要: 目的 研究云南省南部地区中华按蚊(Anopheles sinensis)和杰普尔按蚊(An.jeyporiensis)与地理环境因素的关系,探讨在云南省南部地区西部开发新村镇建设中对疟疾媒介蚊虫种群的可能影响。方法 应用地理信息系统对云南省南部勐腊县的龙塘村及东方红村的中华按蚊和杰普尔按蚊种群与环境因素之间的关系进行分析。结果 各样点中华按蚊优势度可以用线性模型拟合,线性模型为d=0.3621-3.26×10-4×DTF-8.0854×10-7×KFA(R2=0.642,F检验,P=0.000);DTF与样点中华按蚊优势度呈负相关(Person=-0.683,P=0.002),而KFA与样点中华按蚊优势度也呈负相关关系(Person=-0.735,P=0.001)。各样点杰普尔按蚊种群密度可以用线性模型拟合,线性模型为Ni=263-0.0541×KRL(R2=0.633,F检验,P=0.000),KRL与样点杰普尔按蚊种群密度呈负相关关系(Person=-0.825,P=0.000)。各样点杰普尔按蚊优势度可以用线性模型拟合,线性模型为d=7.9204×10-4×DTF-0.0232(R2=0.267,F检验,P=0.023),DTF与样点杰普尔按蚊优势度呈正相关关系(Person=0.562,P=0.012)。结论 在云南省南部地区西部开发的新村镇建设中,相关环境因素的变化有可能会引起中华按蚊和杰普尔按蚊2种媒介蚊虫种群的变化。

关键词: 疟疾, 媒介蚊虫, 地理信息系统, 环境因子

Abstract: Objective Study on relationship of the environment factors with the populations of Anopheles sinensis and An.jeyporiensis, and explore the possible influence of the new villages building which was part of the Chinese west development plan in southern part of Yunnan province on these two vector populations. Methods The relationship of populations of An.sinensis and An.jeyporiensis with the environment factors in southern part of Yunnan province were studied using geographic information system(GIS) system. Results The dominance of An.sinensis could be mimiced by linearity model with DTF and KFA [d=0.3621-3.26×10-4×DTF-8.0854×10-7×KFA (R2=0.642, F test P=0.000)]; The dominance of An.sinensis had the negative relationship with the DTF (Person=-0.683, P=0.002) and the KFA (Person=-0.735, P=0.001). The population density of An.jeyporiensis could be mimiced by linearity model with KRL [Ni=263-0.0541×KRL (R2=0.633, F test P=0.000)], and it had the negative relationship with the KRL (Person=-0.825, P=0.000). The dominance of An.jeyporiensis could be mimiced by linearity model with DTF [d=7.9204×10-4×DTF-0.0232 (R2=0.267, F test P=0.023)], and it had the positive relationship with DTF (Person=0.562, P=0.012). Conclusion In the process of new villages building, the changing of some environment factors origining from building action could lead to population fluctuation of these two malaria vectors.