Efficiency of four trap types and human landing catch in the sampling of Mansonia (Diptera, Culicidae) in Porto Velho, Rondônia, Brazil

在巴西朗多尼亚州波多韦柳,四种诱捕器类型和人工诱捕法在曼氏蚊(双翅目,蚊科)采样中的效率

阅读:1

Abstract

Entomological surveillance plays a crucial role in designing and implementing mosquito control measures. In this context, developing more effective collection strategies is essential to accurately estimate the entomological parameters necessary for effective control. In this study, we investigated the effectiveness of four traps: CDC light trap, MosqTent, BG-Sentinel, and SkeeterVac, compared to human landing catch (HLC) in the collection of Mansonia mosquitoes, known to cause discomfort to riverside populations along the Madeira River in the District of Jaci Paraná, Porto Velho, in Rondônia state, Brazil. Sampling was conducted, during three periods corresponding to two seasons, dry and rainy, over five consecutive days for each period. The captures using HLC and the installation of the traps took place on the grounds of five selected residences from 6 to 10 pm. Rotational exchanges between houses ensured that all traps and the HLC were used in each of the five residences, following a predetermined Latin square pattern. A total of 7,080 mosquitoes were collected, of which 90.5% belonged to the Mansonia genus, distributed in four species: Mansonia titillans (75.97%), Mansonia humeralis (18.91%), Mansonia amazonensis (1.90%), and Mansonia indubitans (1.37%). HLC captured the highest number of Mansonia mosquitoes (58.1%), followed by SkeeterVac (21.8%) and MosqTent (18.9%). CDC and BG-Sentinel showed a very low performance (0.92 and 0.23%, respectively). Although HLC performed better in capturing Mansonia, our results suggest that SkeeterVac and MosqTent can serve as valuable additional tools to entomological inventories or sentinels for detecting invasive species in areas with high epidemiological vulnerability, thereby providing evidence-based recommendations for improving mosquito control measures and entomological surveillance.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。