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Agboli, E.

Publications and source records attributed to Agboli, E..

2 recordsLinked to original sources

Morphological and genetic heterogeneity in Aedes aegypti (Diptera: Culicidae) populations across diverse landscapes in West Africa

Native to sub-Saharan Africa, Aedes aegypti has spread across the globe and is now one of the most significant vectors of arboviruses worldwide. However, data on the ranges of its populations remain sparse, and the genetic variability and ecological adaptability in West Africa are still poorly understood. In this study, we characterized the morphological and genetic diversity of Ae. aegypti across four landscape types (urban, peri-urban, rural, and sylvatic sites) in three West African countries (Burkina Faso, Cote dIvoire, and Ghana). Ae. aegypti exhibited significant variation in abdominal scaling patterns across countries and landscape types, with the sylvatic and urban populations in Burkina Faso displaying the highest proportions of white scales (>50% white scales), while black scales predominated among those from Cote dIvoire and Ghana (>80% black scales). Wing shape displayed limited differentiation between the countries, landscape types, and genetic clusters. Bayesian analysis indicated high gene flow among populations, with notable outliers observed in sylvatic sites from Burkina Faso and admixture patterns suggesting possible human-mediated dispersal. Additionally, two major mitochondrial lineages, clades A and B, were identified. Most samples were categorized under clade B, showing no evidence of clustering by country or landscape type. In contrast, clade A comprised primarily sylvatic specimens from Burkina Faso and a single urban individual from Cote dIvoire. These findings highlight the complex interplay of genetic, environmental, and ecological factors shaping the variations in Ae. aegypti populations in West Africa. They provide insights into the phenotypic and genetic diversity of Ae. aegypti, offering valuable implications for understanding arbovirus transmission dynamics and formulating targeted interventions against arboviral diseases.

ecology↗

Mosquito Wing Image Repository for Advancing Research on Geometric Morphometric- and AI-Based Identification

Accurate identification of mosquito species is essential for effective vector control and mitigation of mosquito-borne disease outbreaks. Traditional morphological identification requires highly specialized personnel and is time-consuming, while molecular techniques can be cost-effective and dependent on comprehensive genetic information. Wing geometric morphometry has emerged as a promising alternative, leveraging detailed geometric measurements of wing shapes and vein patterns to distinguish between species and detect intraspecies variations. This paper presents a curated dataset of 18,104 mosquito wing images, collected from 10,500 mosquito specimens, annotated with extensive meta-information, designed to support research in wing geometric morphometry and the development of machine learning models, ultimately supporting efforts in vector surveillance and research.

ecology↗