中国媒介生物学及控制杂志 ›› 2017, Vol. 28 ›› Issue (1): 46-50.DOI: 10.11853/j.issn.1003.8280.2017.01.013

• 论著 • 上一篇    下一篇

长沙市2007-2015年成蚊密度监测及趋势分析

肖珊, 彭莱, 龙建勋, 何俊   

  1. 长沙市疾病预防控制中心消毒与病媒生物防制科, 长沙 410004
  • 收稿日期:2016-10-16 出版日期:2017-02-20 发布日期:2017-02-20
  • 作者简介:肖珊,女,医师,主要从事病媒生物防制工作,Email:514279051@qq.com

The population density analysis of adult mosquitoes in Changsha city, China from 2007 to 2015

XIAO Shan, PENG Lai, LONG Jian-xun, HE Jun   

  1. Changsha Center for Disease Control and Prevention, Changsha 410004, Hunan Province, China
  • Received:2016-10-16 Online:2017-02-20 Published:2017-02-20

摘要:

目的 调查长沙市2007-2015年成蚊密度,分析其季节消长规律,为蚊虫防制提供科学依据。方法 2007-2015年每年4-12月采用诱蚊灯法捕获蚊类,计算蚊密度;利用差分自回归移动平均(ARIMA)模型,预测2016年各月成蚊密度。结果 共捕获成蚊94 515只,成蚊总密度为6.48只(灯/·h);不同生境的优势蚊种差异明显,牲畜棚以三带喙库蚊为优势种,占捕获总数的50.83%;其他各生境中均以致倦库蚊为优势种,构成比均>51.00%;9年中成蚊密度最高峰在6月,6-9月为成蚊密度高峰期。ARIMA模型较好地拟合了既往成蚊密度序列,构建ARIMA(1,0,0)(2,1,1)12模型,残差序列通过白噪声检验,差异无统计学意义(P>0.05),模型决定系数为0.61。结论 基本掌握了长沙市蚊虫种群构成及其季节消长情况,构建的ARIMA(1,0,0)(2,1,1)12模型可较好地模拟长沙市成蚊密度变化趋势;建议对农村地区加大蚊虫消杀力度,在成蚊密度高峰来临前的4、5月进行全面的灭蚊工作。

关键词: 蚊密度, 监测, 差分自回归移动平均模型

Abstract:

Objective To monitor the adult mosquito densities from 2007 to 2015, analyzing pattern of mosquitoes' species, to provide a basic reference for mosquito control measures. Methods The light trapping method was used to monitor adult mosquito density from April to December, 2007-2015. The autoregressive integrated moving average model (ARIMA) was used to predict adult mosquito density in 2016. Results A total of 94 515 mosquitoes were captured from 2007 to 2015, with a total density of 6.48 per hour. The predominant mosquito species in different habitats were significantly different, Culex tritaeniorhynchus accounted for 50.83% in livestock shed area. The predominant mosquito species in other various habitats was Cx. pipiens quinquefasciatus which accounted for more than 51.00%. The peak season of adult mosquito during 9 years was in June, the density of mosquito was high during June to September. ARIMA(1,0,0) (2,1,1)12 was successfully established, residual sequence was tested by white-noise(P>0.05), and the R2 was 0.61. Conclusion The community composition and seasonal density fluctuation of mosquitoes in Changsha city are acquired basically and the ARIMA(1,0,0) (2,1,1)12 model is able to predict the adult mosquito density. It is suggested that we should make more effort to control mosquitoes in the countryside and take measures in April and May before the onset of the peak mosquito density.

Key words: Mosquito density, Monitoring, Autoregressive integrated moving average model

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