title: Ecological niche modelling of Rift Valley fever virus vectors in Baringo, Kenya.
abstract: BACKGROUND
  Rift 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).
  
  
  OBJECTIVE
  To 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.
  
  
  METHODS
  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.
  
  
  RESULTS
  Model results predicted potential suitable areas with high success rates forCulex quinquefasciatus, Culex univitattus, Mansonia africana, andMansonia uniformis. Under the present climatic conditions, the lowlands were found to be highly suitable for all the species. Future climatic conditions indicate an increase in the spatial distribution ofCx. quinquefasciatusandM. africana. Model performance was statistically significant.
  
  
  CONCLUSIONS
  Soil types, precipitation in the driest quarter, precipitation seasonality, and isothermality showed the highest predictive potential for the four species.
authors.affiliation: Department of Biological Sciences, Jaramogi Oginga Odinga University of Science and Technology, Bondo, Kenya.
authors.forename: Alfred O
authors.initials: AO
authors.lastname: Ochieng
authors.affiliation: Department of Biomedical Sciences, Colorado State University, Fort Collins, CO, USA.|Department of Public Health, Pharmacology and Toxicology, University of Nairobi, Nairobi, Kenya; mnanyingi@gmail.com.
authors.forename: Mark
authors.initials: M
authors.lastname: Nanyingi
authors.affiliation: Division of Research Innovation and Outreach, Jaramogi Oginga Odinga University of Science and Technology, Bondo, Kenya.
authors.forename: Edwin
authors.initials: E
authors.lastname: Kipruto
authors.affiliation: School of Biological Sciences, University of Nairobi, Nairobi, Kenya.
authors.forename: Isabella M
authors.initials: IM
authors.lastname: Ondiba
authors.affiliation: School of Health Sciences, Jaramogi Oginga Odinga University of Science and Technology, Bondo, Kenya.
authors.forename: Fred A
authors.initials: FA
authors.lastname: Amimo
authors.affiliation: Department of Meteorology, University of Nairobi, Nairobi, Kenya.
authors.forename: Christopher
authors.initials: C
authors.lastname: Oludhe
authors.affiliation: Department of Geology, University of Nairobi, Nairobi, Kenya.
authors.forename: Daniel O
authors.initials: DO
authors.lastname: Olago
authors.affiliation: Institute of Anthropology, Gender and African Studies, University of Nairobi, Nairobi, Kenya.
authors.forename: Isaac K
authors.initials: IK
authors.lastname: Nyamongo
authors.affiliation: Division of Research Innovation and Outreach, Jaramogi Oginga Odinga University of Science and Technology, Bondo, Kenya.
authors.forename: Benson B A
authors.initials: BB
authors.lastname: Estambale
keywords: Baringo County; Rift Valley fever; climate change; ecological niche modelling