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云南省西双版纳州勐腊县2013—2023年登革热流行特征分析 被引量:1

Epidemiological characteristics of dengue fever in Mengla County,Xishuangbanna Prefecture,Yunnan Province,2013-2023
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摘要 目的充分了解与分析西双版纳州勐腊县登革热的流行规律,为防控西双版纳州等云南省边境地区的登革热本地暴发流行提供依据。方法采用描述性流行病学方法,系统分析西双版纳州勐腊县2013—2023年间登革热疫情的时间、地域及人群分布特征。结果2013—2023年累计报告登革热病例3220例,其中本地病例2850例,占88.51%;输入病例370例(境外输入197例,境内输入173例),占11.49%。本地病例和输入病例集中在7—10月,具有季节性和地方性特征,以8—10月高发,主要分布于勐腊镇和磨憨镇。2013—2023年本地病例的男女比例为1.17∶1;20~50岁年龄组的病例占66.91%,2013—2023年勐腊县本地病例各年龄组登革热发病率差异有统计学意义(χ^(2)=372.711,P<0.05);本地病例数居前3位的职业是农民43.79%(1248/2850)、学生11.19%(319/2850)和商业服务者7.54%(215/2850),其中2023年不同职业登革热病例数均高于其他年份。2013—2023年输入病例的男女比例为1.52∶1;20~50岁年龄组的病例占82.70%,2013—2023年勐腊县输入登革热发病率在各年龄之间差异有统计学意义(χ^(2)=68.947,P<0.05);输入病例数居前3位的职业是农民126例(34.05%)、商业服务者61例(16.49%)和学生27例(7.30%)。2023年达到10年来输入病例数的峰值,为163例(占输入总数的44.05%)。2013—2023年布雷图指数(Breteau index,BI)显示5月媒介密度开始上升,BI在5~15之间;7—9月媒介密度达高峰,BI在10~40,大多数BI在20~40;10月和11月逐步下降,BI为5~20。结论西双版纳州勐腊县登革热疫情由输入病例引起本地暴发,具有显著地方性和季节性特征,境外输入主要源于东南亚国家。勐腊县应继续保持警惕,加强跨境传播的监测,并且全面落实病例监测以及防蚊灭蚊等预防措施,在疫情暴发初期,采取及时有效的防控措施,以防止疫情大规模暴发和流行。 Objective To fully understand and analyze the epidemic patterns of dengue fever in Mengla County,Xishuangbanna,and provide a basis for the prevention and control of local outbreaks of dengue fever in Xishuangbanna and other border areas of Yunnan Province.Methods Descriptive epidemiological methods were employed to systematically analyze the temporal,geographical,and demographic distribution characteristics of dengue fever in Mengla County,Xishuangbanna Prefecture,from 2013 to 2023.Results From 2013 to 2023,a total of 3220 cases of dengue fever were reported,including 2850 local cases(88.51%)and 370 imported cases(197 cases imported from overseas,173 cases imported domestically),accounting for 11.49%.Local cases and imported cases were concentrated between July and October,showing seasonal and local characteristics,with a high incidence from August to October,mainly distributed in Mengla Town and Mohan Town.The male-to-female ratio of local cases from 2013 to 2023 was 1.17∶1,and the 20-50 age group accounted for 66.91%of cases.There was a statistically significant difference in the incidence of dengue fever across different age groups for local cases from 2013 to 2023(χ^(2)=372.711,P<0.05).The top three occupations with the highest number of local cases were farmers 43.79%(1248/2850),students 11.19%(319/2850),and business service workers 7.54%(215/2850),with the number of imported cases were farmers 126 cases(34.05%),business service workers 61 cases(16.49%),and students 27 cases(7.30%).The number of imported cases peaked in 2023 with 163 cases(44.05%of the total number of imported cases).The Breteau index(BI)from 2013 to 2023 showed an increase in vector density starting in May,with BI between 5-15;a peak in vector density from July to September,with BI between 10-40,and most BI between 20-40;and a gradual decline in October and November,with BI between 5-20.Conclusions The dengue fever outbreak in Mengla County of Xishuangbanna is caused by imported cases,leading to local outbreaks,and exhibiting significant local and seasonal characteristics.The imported cases mainly originated from Southeast Asian countries.Mengla County should remain vigilant,strengthen the monitoring of cross-border transmission,thoroughly implement case surveillance and mosquito prevention and control measures,and adopt timely and effective prevention and control measures at the early stage of the outbreak to prevent large-scale outbreaks and epidemics.
作者 李海艳 王卫 常巍 李园园 严信留 高阳 LI Haiyan;WANG Wei;CHANG Wei;LI Yuanyuan;YAN Xinliu;GAO Yang(Section of Disease Control and Prevention/Section of Endemic Disease Control and Prevention,Xishuangbanna Dai Autonomous Prefecture Center for Disease Control and Prevention,Xishuangbanna,Yunnan 666100,China;School of Public Health,Kunming Medical University,Kunming,Yunnan 60500,China;Yunnan Institute of Parasitic Disease Prevention and Control,Pu'er,Yunnan 665000,China)
出处 《中国热带医学》 CAS 北大核心 2024年第10期1205-1210,共6页 China Tropical Medicine
关键词 登革热 流行病学特征 防控措施 Dengue fever epidemiological characteristics prevention and control measures
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