Seasonal variation in mosquito abundance and environmental predictors in semi-pastoral southern Kenya: implications for endemic Rift Valley fever

作者：Keli Nicole Gerken, Richard Rasto Olubowa, Tatenda Chiuya, Max Korir, Eric M. Fèvre, Andrew Stringer, Andy Morse, Matthew Baylis · 发表于：Parasites & Vectors · 年份：2025 · DOI：10.1186/s13071-025-07122-1 · 被引用次数：2 · 研究领域：Viral Infections and Vectors、Mosquito-borne diseases and control、Vector-borne infectious diseases

Abstract Background Ecological variables that vary across time and space shape mosquito populations, creating microenvironments that can become disease transmission hotspots. Rift Valley fever virus (RVFV), a priority zoonotic arbovirus, thrives in diverse conditions and has been detected in over 50 mosquito species. This diversity complicates efforts to identify the key vectors involved in transmission and highlights the need to understand how environmental conditions shape mosquito abundance in high-risk landscapes. Methods This study investigated spatio-temporal variation in mosquito abundance across the semi-pastoral landscape of Loitokitok sub-county, Kajiado County, Kenya. Over a full year, inclusive of the 2023–2024 El Niño rains, repeated mosquito trapping events were conducted at households enrolled in a human clinical cohort study, with weather station data linked to each trapping event. Results A total of 441 mosquitoes were captured across 39 trapping events, with an average of 11.3 mosquitoes per event. The highest rainfall occurred in November 2023, while mosquito abundance peaked in April 2024. Traps placed at households in cropland areas hosted significantly more mosquitoes overall and were associated with more Anopheles spp., predominantly Anopheles gambiae (Kruskal–Wallis χ 2 = 6.9, df = 2, P = 0.03), while those in shrubland areas had more Aedes aegypti (Kruskal–Wallis χ 2 = 11.9, df = 2, P = 0.002). Multivariable models showed that land use/land cover (LUL...