海口市2017—2022年伊蚊幼虫密度与气象因素关联研究  

The relationship between Aedes larvae density and meteorological factors in Haikou City,2017-2022

作　　者：陆晶晶 林怡[2] 李卫霞 李慧慧 李艳 陈学文 符方德 王妹 刘莹[7] 刘璞瑜 吴群 曾雪霞[7] 曹莉 孙定炜[7] LU Jingjing;LIN Yi;LI Weixia;LI Huihui;LI Yan;CHEN Xuewen;FU Fangde;WANG Mei;LIU Ying;LIU Puyu;WU Qun;ZENG Xuexia;CAO Li;SUN Dingwei(School of Public Health,Hainan Medical University,Haikou,Hainan 571199,China;Haikou Centre for Disease Control and Prevention,Haikou,Hainan 571199,China;Longhua Center for Disease Control and Prevention,Hainan Haikou 570105,China;Qiongshan Center for Disease Control and Prevention,Hainan Haikou 571199,China;Xiuying Center for Disease Control and Prevention,Hainan Haikou 570311,China;Meilan Center for Disease Control and Prevention,Hainan Haikou 570203,China;Institute for Prevention and Control of Tropical and Chronic Diseases,Hainan Provincial Center for Disease Control and Prevention,Haikou,Hainan 570203,China)

机构地区：[1]海南医科大学公共卫生学院,海南海口571199 [2]海口市疾病预防控制中心,海南海口571199 [3]海口市龙华区疾病预防控制中心,海南海口570105 [4]海口市琼山区疾病预防控制中心,海南海口571199 [5]海口市秀英区疾病预防控制中心,海南海口570311 [6]海口市美兰区疾病预防控制中心,海南海口570203 [7]海南省疾病预防控制中心热带病与慢性病预防控制所,海南海口570203

出　　处：《中国热带医学》2024年第8期948-954,共7页China Tropical Medicine

基　　金：海南省科技专项(No.ZDYF2021GXJS018,No.ZDYF2023SHFZ134,No.ZDKJ2021035);海南省自然科学基金项目(No.821MS0844)。

摘　　要：目的分析海南省海口市气象因素对伊蚊幼虫密度的影响,研究其滞后效应,为登革热病媒监测及控制提供依据。方法收集海口市2017—2022年伊蚊幼虫监测数据和气象因子数据,采用X11模型分解分析伊蚊幼虫密度时间序列呈现的季节性及趋势性基本特征,利用Spearman相关系数检验法分析伊蚊幼虫密度与气象因子的相关性。采用分布滞后非线性模型分析气象因素对伊蚊幼虫密度的滞后非线性效应,利用最长滞后时间相对危险度(relative risk,RR)的显著性检验和赤池信息准则最小原则以确定模型最佳参数。结果伊蚊幼虫密度的时间序列分布呈现明显的季节性及下降趋势。分布滞后非线性模型结果显示:与降雨量中位数120 mm相比,随着月平均降雨量的增加,伊蚊幼虫密度的相对危险度先增后减,呈倒“U”型非线性关系。平均降雨量最长滞后时间为1个月,降雨量为119.89~562.14 mm对伊蚊密度有滞后效应(P<0.05),在397.98 mm时相对危险度值最高(RR=1.57,95%CI:1.11~2.20)。与气温中位数25.35℃相比,随月平均气温上升对伊蚊幼虫密度相对危险度增加,呈“J”型。平均气温最长滞后时间为1个月,在25.35~30.10℃之间对伊蚊幼虫密度有滞后效应(P<0.05),在30.10℃时达到峰值(RR=2.24,95%CI:1.24~4.05)。结论高降雨量和高温均对伊蚊幼虫密度具有危险效应,且存在1个月的滞后效应。及时掌握气象因素对伊蚊幼虫密度的影响,可为登革热媒介防控和登革热的早期预警提供依据。Objective To analyze the influence of meteorological factors on Aedes larvae density in Haikou City,Hainan Province,and to study its lagged effect,providing a basis for monitoring and controlling dengue vectors.Methods The Aedes larvae monitoring data and meteorological factor data were collected from 2017 to 2022.The X11 model was employed to decompose and examine the basic characteristics of seasonality and trend in the Aedes aegypti larval density time series.The correlation between Aedes aegypti larval density and meteorological factors was assessed using the Spearman correlation coefficient test.A distributed lag non-linear model was employed to examine the lag non-linear impact of meteorological factors on Aedes larval density.The significance test of relative risk at the longest lag time and the principle of minimizing Akaike's information criterion were utilized to ascertain the optimal parameters of the model.Results The time-series analysis of Aedes larval density revealed distinct seasonality and a decreasing trend.The distribution lag non-linear modeling results indicated that,compared to the median precipitation of 120 mm,with the increase in monthly average precipitation,the relative risk of Aedes larvae density first increased and then decreased,showing an inverted"U"shaped non-linear relationship.The longest lag time of the average precipitation was 1 month,with a lag effect on Aedes larvae density when the precipitation ranged from 119.89 mm to 562.14 mm(P<0.05),peaking at 397.98 mm(RR=1.57,95%CI:1.11-2.20).Compared to a median temperature of 25.35℃,the relative risk to Aedes larvae density increased with the increase of monthly average temperature in a“J”shape.The longest lag time of average temperature was 1 month,with a lag effect on Aedes larvae density between 25.35℃and 30.10℃(P<0.05),peaking at 30.10℃(RR=2.24,95%CI:1.24-4.05).Conclusions High precipitation and high temperature both have a risk effect on Aedes larvae density,with a 1-month lag effect.Timely knowledge of the effec

关 键 词：伊蚊幼虫密度 平均降雨量 平均气温 分布滞后非线性模型 海口市 

分 类 号：R384.1[医药卫生—医学寄生虫学]