GigabyteZoologyPeer-reviewed journal article
Aedes mosquito distribution across urban and peri-urban areas of Kinshasa city, Democratic Republic of Congo
Victoire NsabatieniD, Josué ZangaiD, Nono M. MvuamaiD, Arsène BokuluiD, Hyacinthe Nkosi LUKOKIiD, Glodie DizaiD, Dorcas KantiniD, Leon MbashiiD, Christelle BosuluiD, Narcisse BasosilaiD, Erick BukakaiD, Fiacre Rodrigue AgossaiD, Jonas Mbongu Sodi NagahuediiD, Jean Claude PalataiD, Emery MeteloiD
Abstract
In the Democratic Republic of Congo (DRC) Aedes mosquitoes are principal vectors of medically important arboviruses, with major implications for yellow fever, chikungunya and dengue. However, systematic surveillance of these species remains limited, constrained by competing public health priorities such as malaria and other neglected tropical diseases. This gap in surveillance prevents the rapid detection of changes in the distribution, abundance and behaviour, particularly in rapidly urbanizing environments where breeding habitats are proliferating and ecological conditions are favourable for the establishment of these vectors. To address this gap, spatially explicit, small-scale data on Aedes populations in urban and peri-urban areas are needed to accurately assess transmission risk and develop targeted, evidence-based vector control strategies. Here, we present a geo-referenced dataset of 6,577 entomological occurrence records collected in 20224 throughout urban and peri-urban areas of Kinshasa city, DRC, using Larval dipping, Human landing catches, Prokopack aspirator, and BG-Sentinel traps. Records include Aedes albopictus (n = 2,694), Aedes aegypti (n = 1939), Aedes vittatus (n = 2), and Aedes spp. (n = 1,942), each annotated with species, sex, life stage, reproductive status, and spatial coordinates. The dataset is published as a Darwin Core archive in the Global Biodiversity Information Facility (GBIF), and represents the most detailed, spatially explicit record of Aedes mosquito occurrence in Kinshasa to data, providing a robust foundation for entomological and modelling research to support data driven arbovirus vector control strategies in DRC. Subject AreasEcology, Biodiversity, Vector Biology
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- 1
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- 0.92
- Field percentile
- top 23%
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