2020—2023年上海市松江区蚊虫密度季节分布特征及气象影响因素  

Seasonal distribution characteristics and meteorological influencing factors of mosquito density in Songjiang District,Shanghai,2020‒2023

作　　者：庞博文 刘洪霞[2] 吕锡宏[1] 张驰 吴佳玲 费胜军[1] PANG Bowen;LIU Hongxia;LYU Xihong;ZHANG Chi;WU Jialing;FEI Shengjun(Songjiang District Center for Disease Control and Prevention,Shanghai 201620,China;Shanghai Municipal Center for Disease Control and Prevention,Shanghai 200336,China)

机构地区：[1]上海市松江区疾病预防控制中心,上海201620 [2]上海市疾病预防控制中心,上海200336

出　　处：《上海预防医学》2024年第12期1195-1198,共4页Shanghai Journal of Preventive Medicine

基　　金：上海市加强公共卫生体系建设三年行动计划(2023—2025年)重点学科(GWVI-11.1-13)。

摘　　要：【目的】了解蚊虫密度消长情况与气象因素之间的关系,为蚊虫监测结果分析、风险研判、综合防控等工作提供科学依据。【方法】2020—2023年蚊虫监测数据来自上海市松江区疾病预防控制中心现场督导抽查,气象资料来自Wheat A小麦芽⁃农业气象大数据系统。运用Excel 2019和SPSS 25.0软件整理分析各监测点二氧化碳诱蚊灯法捕捉的蚊虫数量、种类构成和蚊虫密度季节消长情况,运用圆形分布法计算蚊虫密度高峰时间,结合同期气象资料分析气象因素对蚊虫监测结果的影响。【结果】2020—2023年不同生境蚊虫数量总体分布差异有统计学意义(H=23.11,P<0.05),蚊虫密度峰值日为7月28日,蚊虫季节性高峰期为6月13日—9月11日。Pearson相关性分析得出蚊虫密度与平均气温、平均最高气温、平均最低气温、最高气温极值、最低气温极值、降水量、降水天数呈正相关关系(均P<0.01),平均风速与蚊密度相关性不明显(P>0.05)。多元逐步回归分析得出方程为Y=0.151X_(最低气温极值)+0.321X_(降水天数)+1.002X_(SQRT降水量)−1.288(F=102.635,P<0.05)。【结论】二氧化碳诱蚊灯法监测生境宜选择农户、牲畜棚、居民区、公园、医院和其他外环境。气温、降水对蚊密度影响程度较大。建议在蚊虫活动高峰期前,加强综合防制措施降低蚊虫密度,防范蚊媒传染病。[Objective]To investigate the relationship between mosquito density fluctuations and meteorological factors,so as to provide a scientific basis for mosquito surveillance analysis,risk assessment,and comprehensive prevention and control.[Methods]Mosquito surveillance and monitoring data of 2020‒2023 was obtained from on-site supervisory sampling by Songjiang Center for Disease Control and Prevention,and meteorological data was obtained from the Wheat A wheat malt-agro-meteorological big data system.Excel 2019 and SPSS 25.0 software were used to organize and analyze the mosquito number,species composition,and seasonal changes in mosquito density captured by the CO2-light trap at rach monitoring site.Circular distribution method was used to calculate the peak time of mosquito density,combined with the meteorological data of the same period to explore the impact of meteorological factors on the results of mosquito surveillance.[Results]There was a statistical difference in the overall distribution of mosquito quantity in different habitats(H=23.11,P<0.05),2020‒2023.In addition,the results showed that July 28th was the peak day for mosquito density,and the duration from June 13th to September 11th was the seasonal peak period for mosquitoes.Pearson correlation analysis showed a positive correlation between mosquito density and average air temperature,average highest air temperature,average lowest air temperature,extreme maximum air temperature,extreme minimum air temperature,precipitation,and number of precipitation days(all P<0.01).While,there was no significant correlation between average wind speed and mosquito density(P>0.05).Multiple stepwise regression analysis resulted in the equation of Y=0.151X_(extreme minimum temperature)+0.321X_(number of precipitation days)+1.002X_(SQRT precipitation)−1.288(F=102.635,P<0.05).[Conclusion]The CO2-light trap is advisable to monitor the habitats of farmers,livestock sheds,residential areas,parks,hospitals,and other external environments.Air temperature and precipitation

关 键 词：蚊虫密度 圆形分布法 气象因素 监测 

分 类 号：R183[医药卫生—流行病学]