我国重点省份媒介伊蚊幼蚊密度指数相关性研究
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摘要
目的分析我国重点省份媒介伊蚊幼蚊密度指数相关性,为当地媒介伊蚊传播疾病防控提供科学依据。方法收集我国2005-2017年广东、云南和浙江省媒介伊蚊幼蚊布雷图指数(BI)、容器指数(CI)、房屋指数(HI)和诱蚊诱卵器指数(MOI)并建立数据库,应用SPSS 13.0软件进行相关性分析。结果广东省2016、2017年BI与同期MOI呈正相关关系(r=0.853、0.771,P<0.05)。各监测市中,中山市2016、2017年BI与同期MOI呈正相关(r=0.741、0.918,P<0.05),且2016年中山市BI与CI、BI与HI、CI与HI、HI与MOI均呈正相关(r=0.841、0.990、0.797、0.736,P<0.05);汕头市2016年4项幼蚊密度指数间均呈正相关(r=0.964、0.982、0.988、0.772、0.776、0.805,P<0.05);湛江市2016年BI与CI、BI与HI及CI与HI均呈正相关(r=0.986、0.998、0.980,P<0.05)。云南省2014、2016年BI与CI、BI与HI及CI与HI均呈正相关(r=0.988、0.978、0.973,P<0.05)。各监测县(市)中,勐海县2016、2017年BI与CI、BI与HI及CI与HI均呈正相关(r=0.973、0.982、0.994、0.954、0.995、0.971,P<0.05);河口县2016年BI与HI呈正相关(r=1.000,P<0.05),2017年BI与CI、BI与HI及CI与HI均呈正相关(r=0.962、0.945、0.961,P<0.05);陇川县2016、2017年BI与HI呈正相关(r=1.000、0.974,P<0.05)。浙江省义乌市2005-2010年中,除2007年BI与CI及2008年BI与CI、BI与HI、CI与HI之间不具有相关性(P>0.05)外,其余年份幼蚊密度指数间均呈正相关(P<0.05);奉化市2011年BI与CI、BI与HI及CI与HI均呈正相关(r=1.000、0.994、0.993,P<0.05);慈溪市2011年BI与CI、BI与HI及CI与HI均呈正相关(r=0.980、0.993、0.962,P<0.05)。结论重点省份不同年份媒介伊蚊幼蚊密度指标间相关性存在时空特异性,研究结果可为我国不同省份媒介伊蚊及相关传播疾病风险评估及可持续控制提供基础资料。
Objective To analyze the correlation between density indices of Aedes larvae in key provinces of China, and to provide scientific evidence for the prevention and control of Aedes-borne diseases. Methods The Breteau index(BI),container index(CI), house index(HI), and mosquito ovitrap index(MOI) of Aedes larvae in Guangdong, Yunnan, and Zhejiang provinces of China from 2005 to 2017 were collected, and a database was established. A correlation analysis was performed using SPSS 13.0 software. Results In Guangdong province, there was a positive correlation between BI in 2016 and 2017 and MOI in the same period(r=0.853 and 0.771, respectively, P<0.05). In Zhongshan, BI in 2016 and 2017 was positively correlated with MOI in the same period(r=0.741 and 0.918, respectively, P<0.05), and there was a positive correlation between BI and CI, BI and HI, CI and HI, and HI and MOI in 2016(r=0.841, 0.990, 0.797, and 0.736,respectively, P<0.05). In Shantou, the four density indices in 2016 were all positively correlated with each other(r=0.964,0.982, 0.988, 0.772, 0.776, and 0.805, respectively, P<0.05). There was a positive correlation between BI and CI, BI and HI, and CI and HI in 2016 in Zhanjiang(r=0.986, 0.998, and 0.980, respectively, P<0.05). In Yunnan province, there was a positive correlation between BI and CI, BI and HI, and CI and HI in 2014 and 2016(r=0.988, 0.978, and 0.973,respectively, P<0.05). There were a positive correlation between BI and CI, BI and HI, and CI and HI in 2016 and 2017 in Menghai county(r=0.973, 0.982, 0.994, 0.954, 0.995, and 0.971, respectively, P<0.05). In Hekou county, BI was positively correlated with HI in 2016(r=1.000, P<0.05), and there was a positive correlation between BI and CI, BI and HI, and CI and HI in 2017(r=0.962, 0.945, and 0.961, respectively, P<0.05). In Longchuan county, there was a positive correlation between BI and HI in 2016 and 2017(r=1.000 and 0.974, respectively, P<0.05). During 2005-2010 in Yiwu,Zhejiang province, the four density indices of Aedes larvae were positively correlated with each other(P<0.05), except between BI and CI in 2007 and between BI and CI, BI and HI, and CI and HI in 2008(P>0.05). In Fenghua, there was a positive correlation between BI and CI, BI and HI, and CI and HI in 2011(r=1.000, 0.994, and 0.993, respectively, P<0.05). In Cixi, there was a positive correlation between BI and CI, BI and HI, and CI and HI in 2011(r=0.980, 0.993, and0.962, respectively, P<0.05). Conclusion The correlation between the density indices of Aedes larvae in different years in key provinces of China has spatial and temporal specificity, and the results can provide basic data for risk assessment and sustainable control of Aedes vectors and related diseases in different provinces of China.
Objective To analyze the correlation between density indices of Aedes larvae in key provinces of China, and to provide scientific evidence for the prevention and control of Aedes-borne diseases. Methods The Breteau index(BI),container index(CI), house index(HI), and mosquito ovitrap index(MOI) of Aedes larvae in Guangdong, Yunnan, and Zhejiang provinces of China from 2005 to 2017 were collected, and a database was established. A correlation analysis was performed using SPSS 13.0 software. Results In Guangdong province, there was a positive correlation between BI in 2016 and 2017 and MOI in the same period(r=0.853 and 0.771, respectively, P<0.05). In Zhongshan, BI in 2016 and 2017 was positively correlated with MOI in the same period(r=0.741 and 0.918, respectively, P<0.05), and there was a positive correlation between BI and CI, BI and HI, CI and HI, and HI and MOI in 2016(r=0.841, 0.990, 0.797, and 0.736,respectively, P<0.05). In Shantou, the four density indices in 2016 were all positively correlated with each other(r=0.964,0.982, 0.988, 0.772, 0.776, and 0.805, respectively, P<0.05). There was a positive correlation between BI and CI, BI and HI, and CI and HI in 2016 in Zhanjiang(r=0.986, 0.998, and 0.980, respectively, P<0.05). In Yunnan province, there was a positive correlation between BI and CI, BI and HI, and CI and HI in 2014 and 2016(r=0.988, 0.978, and 0.973,respectively, P<0.05). There were a positive correlation between BI and CI, BI and HI, and CI and HI in 2016 and 2017 in Menghai county(r=0.973, 0.982, 0.994, 0.954, 0.995, and 0.971, respectively, P<0.05). In Hekou county, BI was positively correlated with HI in 2016(r=1.000, P<0.05), and there was a positive correlation between BI and CI, BI and HI, and CI and HI in 2017(r=0.962, 0.945, and 0.961, respectively, P<0.05). In Longchuan county, there was a positive correlation between BI and HI in 2016 and 2017(r=1.000 and 0.974, respectively, P<0.05). During 2005-2010 in Yiwu,Zhejiang province, the four density indices of Aedes larvae were positively correlated with each other(P<0.05), except between BI and CI in 2007 and between BI and CI, BI and HI, and CI and HI in 2008(P>0.05). In Fenghua, there was a positive correlation between BI and CI, BI and HI, and CI and HI in 2011(r=1.000, 0.994, and 0.993, respectively, P<0.05). In Cixi, there was a positive correlation between BI and CI, BI and HI, and CI and HI in 2011(r=0.980, 0.993, and0.962, respectively, P<0.05). Conclusion The correlation between the density indices of Aedes larvae in different years in key provinces of China has spatial and temporal specificity, and the results can provide basic data for risk assessment and sustainable control of Aedes vectors and related diseases in different provinces of China.
引文
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[3]吴海霞,刘起勇,刘小波,等.2006-2013年中国19省自纹伊蚊监测数据分析[J].疾病监测,2015,30(4):310-315.
[4]刘小波,郭玉红,吴海霞,等.2015-2017年我国媒介伊蚊幼蚊监测结果分析[J].中国媒介生物学及控制杂志,2018,29(4):325-330.DOI:10.1 1853/j.issn.1003.8280.2018.04.001.
[5]刘小波,吴海霞,郭玉红,等.2016年中国媒介伊蚊密度监测结果分析[J].疾病监测,2018,33(2):144-149.DOI:10.3784/j.issn.1003-9961.2018.02.008.
[6]杨明东,姜进勇,郑宇婷,等.云南省边境地区埃及伊蚊分布调查[J].中国媒介生物学及控制杂志,2015,26(4):406-408.DOI:10.11 853/j.issn.1003.4692.2015.04.020.
[7]郑宇婷,杨明东,周克梅.云南省边境地区2016年登革热媒介监测结果分析[J].中国媒介生物学及控制杂志,2018,29(2):157-160.DOI:10.1 1853/j.issn.1003.8280.2018.02.010.
[8]骆淑英,傅涛,何安庆,等.义乌市2005-2010年登革热流行特征与监测分析[J].中国预防医学杂志,2012,13(6):468-470.DOI:10.16506/j.1009-6639.2012.06.013.
[9]吴寅徽,夏颖苹,周国定.奉化市2011年白纹伊蚊监测结果分析[J].上海预防医学,2012,24(8):457-459.DOI:10.3969/j.issn.1004-923 1.2012.08.021.
[10]马晓,范飞能,吕辉,等.宁波市2011年登革热媒介白纹伊蚊监测结果分析[J].中国媒介生物学及控制杂志,2012,23(6):567-568.
[11]Romero-Vivas CM,Falconar AKI.Investigation of relationships between Aedes aegypti egg,larvae,pupae,and adult density indices where their main breeding sites were located indoors[J].J Am Mosq Control Assoc,2005,21(1):15-21.DOI:10.2987/8756-971X(2005)21[15:IORBAA]2.0.CO;2.
[12]江毅民,严子锵,胡志刚,等.诱蚊诱卵指数作为蚊虫密度监测指标适用性的探讨[J].热带医学杂志,2015,15(11):1555-1557.
[13]茌静,古文媚,陈戊申,等.3种媒介伊蚊监测方法在登革热疫点中的应用及相关性研究[J].中国媒介生物学及控制杂志,2015,26(5):495-497.DOI:10.11853/j.issn.1003.4692.2015.05.016.