中国媒介生物学及控制杂志 ›› 2019, Vol. 30 ›› Issue (4): 430-433.DOI: 10.11853/j.issn.1003.8280.2019.04.017

• 论著 • 上一篇    下一篇

气候因素对浦东新区蚊虫密度影响的效应分析

谢博, 冯磊, 顾盈培, 沈安梅, 刘汉昭, 刘俊, 蔡凤珠   

  1. 上海市浦东新区疾病预防控制中心(复旦大学浦东预防医学研究院), 上海 200136
  • 收稿日期:2019-04-11 出版日期:2019-08-20 发布日期:2019-08-20
  • 通讯作者: 蔡凤珠,Email:13671671455@163.com
  • 作者简介:谢博,男,硕士,主要从事病媒生物控制工作,Email:bbyn0208@163.com
  • 基金资助:
    上海市浦东新区卫生局卫生科技项目

An analysis of the effect of climatic factors on mosquito density in Pudong New Area, Shanghai, China

XIE Bo, FENG Lei, GU Ying-pei, SHEN An-mei, LIU Han-zhao, LIU Jun, CAI Feng-zhu   

  1. Shanghai Pudong New Area Center for Disease Control and Prevention(Pudong Institute of Fudan University for Preventive Medicine), Shanghai 200136, China
  • Received:2019-04-11 Online:2019-08-20 Published:2019-08-20
  • Supported by:
    Supported by the Research Grant for Health Science and Technology of Pudong Health Bureau of Shanghai

摘要: 目的 分析上海市气象情况变化趋势以及浦东新区人工小时法监测结果的蚊虫密度消长规律;探索各种气象因素对浦东新区蚊虫密度的影响。方法 收集2011年3月至2015年11月上海市的单日气象数据,整理同时期浦东新区蚊虫人工小时法监测结果。使用分布滞后非线性模型研究气象因素对蚊虫密度指数的影响效应。结果 单日平均气温与蚊虫密度指数呈明显非线性关系,滞后天数与效应强度呈“U”型,在温度为32℃时,相对危险度值最高达到2.2。滞后效应在3 d左右达到最强,随后逐渐降低,在10 d后又逐渐回升。湿度的影响情况与温度类似,风速的结果与温、湿度相反。结论 温度对蚊虫密度指数效应在滞后3 d时最强,湿度对蚊虫密度影响效应无明显滞后。

关键词: 病媒生物, 人工小时法, 分布滞后非线性模型

Abstract: Objective To analyze the trend in the meteorological characteristics of Shanghai, China, and the pattern of changes in mosquito density (surveyed by the labor hour method) in Pudong New Area, Shanghai, and to explore the effect of meteorological factors on mosquito density in Pudong New Area. Methods The single-day meteorological data from March 2011 to November 2015 in Shanghai were collected; meanwhile, the mosquito surveillance data based on the labor hour method in Pudong New Area during the same period were collected. The distributed lag non-linear model was used to determine the effect of meteorological factors on mosquito density index. Results A significant non-linear relationship was found between single-day average temperature and mosquito density index. The number of lag days showed a U-shaped relationship with the effect intensity. The relative ratio value reached a maximum of 2.2 at 32℃. The lag effect achieved a peak within about 3 days, then gradually decreased, and gradually recovered after 10 days. The effect of humidity was similar to that of temperature. The result of wind velocity was contrary to that of temperature and humidity. Conclusion The temperature shows a maximum effect on mosquito density index after 3 lag days, and the humidity has no significant lag effect on mosquito density.

Key words: Vector, Labor hour method, Distributed lag non-linear model

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