Roslan Muhammad Aidil, Ngui Romano, Marzuki Muhammad Fathi, Vythilingam Indra, Shafie Aziz, Musa Sabri, Wan Sulaiman Wan Yusoff
Department of Parasitology, Faculty of Medicine; Department of Paediatric Dentistry and Orthodontics, Faculty of Dentistry; Office of Deputy Vice-Chancellor (Student Affairs), University of Malaya, Kuala Lumpur.
Department of Parasitology, Faculty of Medicine, University of Malaya, Kuala Lumpur.
Geospat Health. 2022 May 11;17(1). doi: 10.4081/gh.2022.1025.
Dengue is a major mosquito-borne disease in many tropical and sub-tropical countries worldwide, with entomological surveillance and control activities as the key management approaches. This study aimed to explore the spatial dispersal of the vector Aedes albopictus, captured by the modified sticky ovitrap (MSO) in residential areas with low-rise buildings in Selangor, Malaysia. Distribution maps were created and shown as temporally distinguished classes based on hotspot analysis by Getis-Ord; spatial autocorrelation assessed by semivariograms using the exponential Kernel function; and universal Kriging showing areas with estimated high and low vector densities. Distribution, hotspot and interpolated maps were analysed based on the total number of mosquitoes by month and week. All maps in the present study were generated and visualised in ArcMap. Spatial autocorrelation of Ae. albopictus based on the monthly occurrence of Ae. albopictus was found in March, April, October, November and December 2018, and when based on the weekly numbers, in weeks 1, 2, 3, 5, 7, 12, 14, 25, 26, 27, 31, 33, 42, 49 and 52. Semivariograms, based on the monthly and weekly numbers of Ae. albopictus, indicated spatial autocorrelation of the species extending between 50 and 70 m. The mosquito density maps reported in this study may provide beneficial information to facilitate implementation of more efficient entomological control activities.
登革热是全球许多热带和亚热带国家的主要蚊媒疾病，昆虫学监测和控制活动是关键的管理方法。本研究旨在探讨在马来西亚雪兰莪州低层建筑居民区中，经改良的粘性诱蚊产卵器（MSO）捕获的白纹伊蚊媒介的空间扩散情况。绘制了分布图，并根据Getis-Ord热点分析按时间区分的类别展示；使用指数核函数通过半变异函数评估空间自相关性；通用克里金法显示估计蚊媒密度高和低的区域。根据每月和每周蚊子总数分析分布、热点和插值图。本研究中的所有地图均在ArcMap中生成并可视化。基于白纹伊蚊每月出现情况的白纹伊蚊空间自相关性在2018年3月、4月、10月、11月和12月被发现，基于每周数量的空间自相关性在第1、2、3、5、7、12、14、25、26、27、31、33、42、49和52周被发现。基于白纹伊蚊每月和每周数量的半变异函数表明该物种的空间自相关性延伸至50至70米之间。本研究报告的蚊虫密度图可能会提供有益信息，以促进实施更有效的昆虫学控制活动。
