ArticleInfection ecology & epidemiology2016
Ecological niche modelling of Rift Valley fever virus vectors in Baringo, Kenya.
Article in Infection ecology & epidemiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Seroprevalence of rift valley fever virus and associated risk factors in small ruminants at human-livestock-wildlife interface within Uganda's conservation areas.BMC veterinary research · 2026Article
- Gaps and opportunities for data systems and economics to support priority setting for climate-sensitive infectious diseases in sub-Saharan Africa: A rapid scoping review.PLOS global public health · 2025Article
- Entomological survey of the potential vectors of Rift Valley fever virus and absence of detection of the virus genome from the vectors in various niches in the southern half of the Great Rift Valley of Ethiopia.Veterinary medicine and science · 2022Article
- The Burden of Dengue in Children by Calculating Spatial Temperature: A Methodological Approach Using Remote Sensing Techniques.International journal of environmental research and public health · 2021Article
- Present and future climatic suitability for dengue fever in Africa.Infection ecology & epidemiology · 2020Article
- Ecological Niche Modeling of West Nile Virus Vector in Northwest of Iran.Oman medical journal · 2019Article
- Article
- Ecological niche modeling of Aedes mosquito vectors of chikungunya virus in southeastern Senegal.Parasites & vectors · 2018Article
- Support for research towards understanding the population health vulnerabilities to vector-borne diseases: increasing resilience under climate change conditions in Africa.Infectious diseases of poverty · 2017Article
- Effect of climatic variability on malaria trends in Baringo County, Kenya.Malaria journal · 2017Article
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundRift Valley fever (RVF) is a vector-borne zoonotic disease that has an impact on human health and animal productivity. Here, we explore the use of vector presence modelling to predict the distribution of RVF vector species under climate change scenario to demonstrate the potential for geographic spread of Rift Valley fever virus (RVFV).
objectivesTo evaluate the effect of climate change on RVF vector distribution in Baringo County, Kenya, with an aim of developing a risk map for spatial prediction of RVF outbreaks. METHODOLOGY: The study used data on vector presence and ecological niche modelling (MaxEnt) algorithm to predict the effect of climatic change on habitat suitability and the spatial distribution of RVF vectors in Baringo County. Data on species occurrence were obtained from longitudinal sampling of adult mosquitoes and larvae in the study area. We used present (2000) and future (2050) Bioclim climate databases to model the vector distribution.
resultsModel results predicted potential suitable areas with high success rates for
conclusionSoil types, precipitation in the driest quarter, precipitation seasonality, and isothermality showed the highest predictive potential for the four species.
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