Albrieu-Llinás Guillermo, Espinosa Manuel O, Quaglia Agustín, Abril Marcelo, Scavuzzo Carlos Marcelo
Arbovirus laboratory, Dr. Vanella Virology Institute, Faculty of Medical Sciences, National University of Córdoba, CONICET.
Geospat Health. 2018 May 7;13(1):654. doi: 10.4081/gh.2018.654.
The identification of Aedes aegypti breeding hotspots in urban areas is crucial for the rational design of control strategies against this disease vector. Remote sensing and geographic information systems offer valuable tools for mapping habitat suitability of a given area. However, predicting species occurrences by means of probability distribution maps based on transversal entomological surveys has limited utility for local authorities. The aim of the present study was to carefully examine the temporal evolution of the number of houses infested with immature stages of Ae. aegypti in each individual neighbourhood and to explore the value of producing environmental clusters generated with information provided by remotely sensed variables to explain the observed differential temporal behaviour. Entomological surveys were conducted between 2011 and 2013 throughout a small town in Argentina registering the number of houses with containers harbouring immature stages of Ae. aegypti. A SPOT 5 satellite image was used to obtain land cover variables, which were subsequently submitted to k-means partitioning for grouping neighbourhoods into four environmental clusters. Finally, a generalized linear model was fitted showing that the number of houses found to be positive for Ae. aegypti was jointly affected by the interaction between environmental clusters and the year of sampling. Moreover, the number of positive houses in one of the clusters was 9.5 times higher (P<0.005, SE=0.37) in 2013 than in 2012, but we did not observe any other statistically significant increases.
识别城市地区埃及伊蚊的繁殖热点对于合理设计针对这种病媒的控制策略至关重要。遥感和地理信息系统为绘制特定区域的栖息地适宜性提供了有价值的工具。然而，通过基于横断面昆虫学调查的概率分布图来预测物种出现情况，对地方当局的效用有限。本研究的目的是仔细研究每个街区感染埃及伊蚊未成熟阶段的房屋数量的时间演变，并探讨利用遥感变量提供的信息生成环境集群来解释观察到的不同时间行为的价值。2011年至2013年期间，在阿根廷的一个小镇进行了昆虫学调查，记录了带有埃及伊蚊未成熟阶段的容器的房屋数量。利用SPOT 5卫星图像获取土地覆盖变量，随后将其提交给k均值分区，以便将街区划分为四个环境集群。最后，拟合了一个广义线性模型，结果表明，发现感染埃及伊蚊呈阳性的房屋数量受到环境集群与采样年份之间相互作用的共同影响。此外，2013年其中一个集群中的阳性房屋数量比2012年高出9.5倍（P<0.005，SE=0.37），但我们未观察到任何其他具有统计学意义的增加。
