Seasonal variation in mosquito abundance and environmental predictors in semi-pastoral southern Kenya: implications for endemic Rift Valley fever
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 mosquit...
| Autores principales: | , , , , , , , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
BioMed Central
2026
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/178431 |
| _version_ | 1855540797571596288 |
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| author | Gerken, Keli N. Olubowa, Richard R. Chiuya, Tatenda Korir, Max Fèvre, Eric M. Stringer, A. Morse, A. Baylis, M. |
| author_browse | Baylis, M. Chiuya, Tatenda Fèvre, Eric M. Gerken, Keli N. Korir, Max Morse, A. Olubowa, Richard R. Stringer, A. |
| author_facet | Gerken, Keli N. Olubowa, Richard R. Chiuya, Tatenda Korir, Max Fèvre, Eric M. Stringer, A. Morse, A. Baylis, M. |
| author_sort | Gerken, Keli N. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | 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 χ2 = 6.9, df = 2, P = 0.03), while those in shrubland areas had more Aedes aegypti (Kruskal–Wallis χ2 = 11.9, df = 2, P = 0.002). Multivariable models showed that land use/land cover (LULC) consistently improved model fit, though temporal weather factors were stronger predictors. Weather conditions from the prior month better predicted mosquito abundance than weather conditions over shorter time frames, with temperature consistently included in top models and humidity outperforming rainfall as an additional covariate in the best-fit model that included LULC, temperature, and humidity.
Conclusions: These findings highlight the role of weather patterns and LULC in shaping mosquito dynamics, with irrigated cropland likely creating persistent breeding sites and shrubland providing niches for Ae. aegypti. This emphasizes the need for targeted, community-driven vector control strategies to mitigate RVFV transmission risk and highlights the importance of altered agricultural landscapes in driving vector dynamics. |
| format | Journal Article |
| id | CGSpace178431 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2026 |
| publishDateRange | 2026 |
| publishDateSort | 2026 |
| publisher | BioMed Central |
| publisherStr | BioMed Central |
| record_format | dspace |
| spelling | CGSpace1784312026-01-05T14:06:07Z Seasonal variation in mosquito abundance and environmental predictors in semi-pastoral southern Kenya: implications for endemic Rift Valley fever Gerken, Keli N. Olubowa, Richard R. Chiuya, Tatenda Korir, Max Fèvre, Eric M. Stringer, A. Morse, A. Baylis, M. rift valley fever zoonoses 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 χ2 = 6.9, df = 2, P = 0.03), while those in shrubland areas had more Aedes aegypti (Kruskal–Wallis χ2 = 11.9, df = 2, P = 0.002). Multivariable models showed that land use/land cover (LULC) consistently improved model fit, though temporal weather factors were stronger predictors. Weather conditions from the prior month better predicted mosquito abundance than weather conditions over shorter time frames, with temperature consistently included in top models and humidity outperforming rainfall as an additional covariate in the best-fit model that included LULC, temperature, and humidity. Conclusions: These findings highlight the role of weather patterns and LULC in shaping mosquito dynamics, with irrigated cropland likely creating persistent breeding sites and shrubland providing niches for Ae. aegypti. This emphasizes the need for targeted, community-driven vector control strategies to mitigate RVFV transmission risk and highlights the importance of altered agricultural landscapes in driving vector dynamics. 2026-12 2025-12-02T06:08:05Z 2025-12-02T06:08:05Z Journal Article https://hdl.handle.net/10568/178431 en Open Access BioMed Central Gerken, K.N., Olubowa, R.R., Chiuya, T., Korir, M., Fèvre, E.M., Stringer, A., Morse, A. and Baylis, M. 2026. Seasonal variation in mosquito abundance and environmental predictors in semi-pastoral southern Kenya: implications for endemic Rift Valley fever. Parasites and Vectors 19 (1): 1. |
| spellingShingle | rift valley fever zoonoses Gerken, Keli N. Olubowa, Richard R. Chiuya, Tatenda Korir, Max Fèvre, Eric M. Stringer, A. Morse, A. Baylis, M. Seasonal variation in mosquito abundance and environmental predictors in semi-pastoral southern Kenya: implications for endemic Rift Valley fever |
| title | Seasonal variation in mosquito abundance and environmental predictors in semi-pastoral southern Kenya: implications for endemic Rift Valley fever |
| title_full | Seasonal variation in mosquito abundance and environmental predictors in semi-pastoral southern Kenya: implications for endemic Rift Valley fever |
| title_fullStr | Seasonal variation in mosquito abundance and environmental predictors in semi-pastoral southern Kenya: implications for endemic Rift Valley fever |
| title_full_unstemmed | Seasonal variation in mosquito abundance and environmental predictors in semi-pastoral southern Kenya: implications for endemic Rift Valley fever |
| title_short | Seasonal variation in mosquito abundance and environmental predictors in semi-pastoral southern Kenya: implications for endemic Rift Valley fever |
| title_sort | seasonal variation in mosquito abundance and environmental predictors in semi pastoral southern kenya implications for endemic rift valley fever |
| topic | rift valley fever zoonoses |
| url | https://hdl.handle.net/10568/178431 |
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