上海市松江区2017－2022年白纹伊蚊分布特征及时空聚集性分析

doi:10.11853/j.issn.1003.8280.2024.02.008

摘要/Abstract

摘要： 目的了解上海市松江区白纹伊蚊密度分布及时空聚集性特征,为伊蚊传播疾病的监测预警、风险研判和精准防控提供参考依据。方法收集2017-2022年6-10月上海市松江区17个街道(镇)的媒介伊蚊监测数据,对白纹伊蚊诱蚊诱卵指数(MOI)进行描述分析,分别利用ArcGIS 10.8软件和SaTScan 10.1.2软件,开展空间自相关分析和时空扫描分析。结果松江区白纹伊蚊密度每年先升后降,7-8月达到峰值;年均密度前3位的区域为方松街道、泗泾镇和车墩镇;平均密度最高的生境类型为居民区。2022年白纹伊蚊密度分布具有空间聚集性(Moran's I=0.139,P=0.047),2018年广富林、岳阳和中山街道,2021年广富林、岳阳街道和洞泾镇,2022年岳阳、中山和永丰街道,白纹伊蚊密度分布均存在局部聚集性;2018年存在白纹伊蚊密度聚集热点,热点为中山街道和车墩镇,2022年存在聚集热点,热点为中山街道、岳阳街道和车墩镇,时空扫描分析得出1个涉及方松、岳阳、永丰、中山街道和车墩镇的一类聚集区(对数似然比值为68.61,相对危险度为2.66,P<0.001)。结论松江区2017-2022年白纹伊蚊密度分布逐渐呈现向中心城区空间聚集的趋势,其中方松、岳阳、永丰、中山街道和车墩镇是白纹伊蚊局部聚集的主要热点区域。

关键词: 白纹伊蚊, 诱蚊诱卵指数, 分布特征, 空间自相关, 时空聚集性

Abstract: Objective To investigate the density distribution and spatiotemporal aggregation of Aedes albopictus in Songjiang District, Shanghai, China, so as to provide a reference for monitoring, early warning, risk analysis, and precise prevention and control of Aedes-borne infectious diseases.Methods Descriptive analyses were performed on Ae. albopictus larvae density data (mosq-ovitrap index, MOI) in 17 sub-districts and towns of Songjiang District of Shanghai from June to October, 2017-2022. ArcGIS 10.8 and SaTScan 10.1.2 softwares were used to conduct spatial autocorrelation analysis and spatiotemporal scanning analysis, respectively.Results In 2017-2022, the density of Ae. albopictus in Songjiang District increased first and then decreased every year, with the peak in July and August. The top three regions by annual average density were Fangsong Sub-district, Sijing Town, and Chedun Town, and residential areas had the highest mosquito density among habitats. Spatial aggregation was found in the density distribution of Ae. albopictus in 2022 (Moran's I=0.139, P=0.047); Ae. albopictus density showed local aggregation in Guangfulin, Yueyang, and Zhongshan sub-districts in 2018, in Guangfulin Sub-district, Yueyang Sub-district, and Dongjing Town in 2021, and in Yueyang, Zhongshan, and Yongfeng sub-districts in 2022; the aggregation hotspots in 2018 were observed in Zhongshan Sub-district and Chedun Town; and the aggregation hotspots in 2022 were observed in Zhongshan Sub-district, Yueyang Sub-district, and Chedun Town. Spatiotemporal scanning analysis indicated a class-Ⅰ gathering area involving Fangsong, Yueyang, Yongfeng, and Zhongshan sub-districts and Chedun Town (log-likelihood ratio was 68.61, relative risk was 2.66, P<0.001).Conclusion The density distribution of Ae. albopictus was gradually aggregating towards central urban areas in Songjiang District from 2017 to 2022, and Fangsong, Yueyang, Yongfeng, and Zhongshan sub-districts and Chedun Town were the main areas of local aggregation.

Key words: Aedes albopictus, Mosq-ovitrap index, Distribution characteristic, Spatial autocorrelation, Spatiotemporal aggregation

中图分类号:

R384.1

叶独秋, 庞博文, 蒋露芳, 陶骏捷, 张驰, 李萌, 吕锡宏. 上海市松江区2017－2022年白纹伊蚊分布特征及时空聚集性分析[J]. 中国媒介生物学及控制杂志, 2024, 35(2): 171-176.

YE Du-qiu, PANG Bo-wen, JIANG Lu-fang, TAO Jun-jie, ZHANG Chi, LI Meng, LYU Xi-hong. Distribution characteristics and spatiotemporal aggregation of Aedes albopictus in Songjiang District, Shanghai, China, 2017-2022[J]. Chinese Journal of Vector Biology and Control, 2024, 35(2): 171-176.

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