中国媒介生物学及控制杂志 ›› 2011, Vol. 22 ›› Issue (5): 487-489.

• 调查研究 • 上一篇    下一篇

2009年汶川地震极重灾区蚊密度监测分析

胡雅劼, 钱薇萍, 陈东平, 周忆昭   

  1. 四川省疾病预防控制中心寄生虫病预防控制所,四川成都 610041
  • 收稿日期:2011-05-17 出版日期:2011-10-20 发布日期:2011-10-20
  • 通讯作者: 钱薇萍,Email: zqwp620@yahoo.com.cn
  • 作者简介:胡雅劼(1984-),女,研究实习员,主要从事病媒生物防制与研究。Email: yajie.hu@yahoo.com

Surveillance and analysis of mosquito density in the worst-hit areas of earthquake-stricken Wenchuan, 2009

HU Ya-jie, QIAN Wei-ping, CHEN Dong-ping, ZHOU Yi-zhao   

  1. Sichuan Center for Disease Control and Prevention, Chengdu 610041, Sichuan Province, China
  • Received:2011-05-17 Online:2011-10-20 Published:2011-10-20

摘要:

目的 掌握汶川地震极重灾区蚊类的种群构成和不同生境的蚊密度情况,为做好蚊媒传染病的风险评估,指导开展汶川地震灾区蚊类和相关传染病的防控工作提供可靠依据。方法 采用诱蚊灯法诱捕成蚊,并对捕获蚊虫进行分类鉴定。结果 四川省汶川地震极重灾区蚊虫总密度为1.64只/(灯·h),蚊种构成以致倦库蚊数量最多,占捕获总数的64.53%,三带喙库蚊和中华按蚊分别占15.69%和10.77%;各类生境密度以安置区和中心城区较高,地震遗址较低;季节消长显示,6-8月是灾区蚊虫的高峰期。结论 蚊虫总密度较低,其中安置区和中心城区应作为开展综合防治的重点区域;通过开展系统的蚊密度监测工作,科学指导汶川地震灾区蚊类的综合防治,防止了相关传染病的暴发流行。

关键词: 蚊虫, 密度监测, 地震极重灾区

Abstract:

Objective To determine the population constitution and density of mosquitoes in different habitats in the worst- hit areas of earthquake - stricken Wenchuan to inform risk evaluation, prevention and control of mosquito - borne disease. Methods Light traps were applied to collect adult mosquitoes, followed by classification and identification. Results The mosquito density was 1.64 per light per hour. The population consisted of Culex pipiens quinquefasciatus mostly, which accounted for 64.53% of the total number. Cx. tritaeniorhynchus and Anopheles sinensis accounted for 15.69% and 10.77%, respectively. The mosquito density in settlement residences and central city was higher than that in earthquake ruins. An upward trend from June to August was shown from the seasonal fluctuation. Conclusion The overall density of mosquitoes was low. However, integrated management is still needed for the settled communities and central city in combination with systematic monitoring to prevent potential outbreaks of related infectious diseases.

Key words: Mosquito, Density monitoring, Worst-hit earthquake-stricken area

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