热带病与寄生虫学

热带病与寄生虫学 ›› 2026, Vol. 24 ›› Issue (3): 142-148.doi: 10.20199/j.issn.1672-2302.2026.03.003

• 蚊媒传染病防控专题 • 上一篇    下一篇

白纹伊蚊密度与气象因素的关系及滞后效应分析

束灵1(), 吴悦1(), 王萍1, 汪子豪1, 钟培松1, 刘洪霞2, 王巧燕1()   

  1. 1 上海市嘉定区疾病预防控制中心， 上海 201821
    2 上海市疾病预防控制中心
  • 收稿日期:2026-02-12 出版日期:2026-06-20 发布日期:2026-07-31
  • 通信作者: 王巧燕，E-mail: jdcdcwqy@163.com
  • 作者简介:束灵，男，本科，主管医师，研究方向：病媒生物防制。E-mail: 1005200119@qq.com|吴悦，女，硕士，主管医师，研究方向：病媒生物防制。E-mail: wy09222023@163.com;束灵和吴悦同为第一作者
  • 基金资助:
    上海市嘉定区第二轮公共卫生优秀人才培养项目(JDGWYC-2026-XK01)

Relationships and lag effects between Aedes albopictus density and meteorological factors

SHU Ling1(), WU Yue1(), WANG Ping1, WANG Zihao1, ZHONG Peisong1, LIU Hongxia2, WANG Qiaoyan1()   

  1. 1 Jiading District Center for Disease Control and Prevention, Shanghai 201821, China
    2 Shanghai Municipal Center for Disease Control and Prevention
  • Received:2026-02-12 Online:2026-06-20 Published:2026-07-31
  • Contact: WANG Qiaoyan, E-mail: jdcdcwqy@163.com

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摘要：

目的 探讨白纹伊蚊密度与气象因素之间的关系及滞后效应，为蚊媒传染病的精准监测和风险预警提供科学依据。方法 收集2023年4—10月上海市嘉定区白纹伊蚊监测数据及同期气象资料，使用诱蚊诱卵指数（mosquito ovitrap index, MOI）和停落指数（landing index, LI）作为白纹伊蚊密度指标，采用广义可加模型和分布滞后非线性模型分析白纹伊蚊密度与气象因素之间的关系及滞后效应。结果 2023年4—10月上海市嘉定区白纹伊蚊密度呈明显的季节性消长。MOI对数与日平均气温（F=12.05，P<0.01）、日最低气温（F=12.56，P<0.01）呈非线性正相关，与日累计降雨量（F=9.32，P<0.05）和日平均相对湿度（F=10.60，P<0.01）呈线性正相关。气象因素对MOI影响的滞后效应为：日最高气温为38.6 ℃时，滞后5 d的相对危险度（relative risk, RR）最大，为2.5（95%CI：1.3~3.8）；日最低气温在26.3 ℃时，滞后5 d的RR值最大，为2.9（95%CI：2.6~3.3）；日累计降雨量在157.0 mm时，滞后0 d的RR值最大，为1.6（95%CI：1.2~2.3）；日平均相对湿度在52.1%时，滞后0~1 d的RR值最大，为20.0（95%CI：12.1~38.5）。LI对数与日平均气温（F=13.32，P<0.01）、日最低气温（F=13.63，P<0.01）、日累计降雨量（F=6.16，P<0.05）和日平均相对湿度（F=9.33，P<0.05）呈非线性正相关，与日最高气温（F=9.76，P<0.01）呈线性正相关。气象因素对LI影响的滞后效应为：日平均气温在15.0 ℃时，滞后5 d的RR值最大，为57.5（95%CI：20.1~113.6）；日累计降雨量在157.0 mm时，滞后0 d的RR值最大，为7.8（95%CI：2.7~12.5）；日平均相对湿度在88.0%时，滞后5 d的RR值最大，为3.2（95%CI：1.5~4.9），在52.1%时，滞后30 d的RR值最大，为6.7（95%CI：3.4~10.1）。结论 气温、降雨量和平均相对湿度与嘉定区白纹伊蚊密度存在相关性，其中气温和降雨对白纹伊蚊密度的影响存在明显的滞后效应。建议将气象因素与蚊媒监测结合，指导当地蚊媒传染病防控预警工作。

关键词: 白纹伊蚊, 气象因素, 广义可加模型, 分布滞后非线性模型, 滞后效应

Abstract:

Objective To investigate the relationships and lag effects between Aedes albopictus density and meteorological factors, for scientific evidences for rational monitoring and early risk warning of mosquito-borne diseases. Methods Aedes albopictus surveillance data and concurrent meteorological records from April to October 2023 were collected in Jiading District, Shanghai. The mosquito ovitrap index (MOI) and landing index (LI) were used as indicators of Aedes albopictus density. The generalized additive model and the distributed lag nonlinear model were used to analyze the nonlinear effects of and lag effects between meteorological factors and Aedes albopictus density. Results From April to October 2023, Aedes albopictus density in Jiading District, Shanghai, showed significantly seasonal fluctuations. The logarithm of MOI was nonlinearly and positively correlated with daily average temperature (F=12.05, P<0.01) and daily minimum temperature (F=12.56, P<0.01), linearly and positively correlated with daily cumulative rainfall (F=9.32, P<0.05) and daily average relative humidity (F=10.60, P<0.01). The lag effects of meteorological factors on MOI were as follows: when the daily maximum temperature was 38.6 ℃, the relative risk (RR) peaked at lag 5 days (RR=2.5, 95%CI: 1.3-3.8); at a daily minimum temperature of 26.3 ℃, the maximum RR was observed at lag 5 days (RR=2.9, 95%CI: 2.6-3.3); under daily cumulative rainfall of 157.0 mm, the maximum RR was observed at lag 0 day (RR=1.6, 95%CI: 1.2-2.3); and at a daily average relative humidity of 52.1%, the maximum RR was observed at lag 0-1 day (RR=20.0, 95%CI: 12.1-38.5). The logarithm of LI was nonlinearly and positively correlated with daily average temperature (F=13.32, P<0.01), daily minimum temperature (F=13.63, P<0.01), daily cumulative rainfall (F=6.16, P<0.05) and daily average relative humidity (F=9.33, P<0.05), whereas showed linear and positive correlation with daily maximum temperature (F=9.76, P<0.01). The lag effects of meteorological factors on LI were as follows: at a daily average temperature of 15.0 ℃, the maximum RR was observed at lag 5 days (RR=57.5, 95%CI: 20.1-113.6); at a daily cumulative rainfall of 157.0 mm, the maximum RR was observed at lag 0 day (RR=7.8, 95%CI: 2.7-12.5); for daily average relative humidity, the maximum RR was 3.2 (95%CI: 1.5-4.9) at 88.0% with a lag of 5 days, and 6.7 (95%CI: 3.4-10.1) at 52.1% with a lag of 30 days. Conclusion The temperature, rainfall, and average relative humidity are associated with the density of Aedes albopictus in Jiading District, Shanghai, with temperature and rainfall showing obvious lagged effects on its density. It is recommended to combine meteorological factors with mosquito vector monitoring to guide local prevention and early warning of mosquito-borne diseases.

Key words: Aedes albopictus, Meteorological factors, Generalized additive model, Distributed lag non-linear model, Lag effect

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