Ecological niche modelling of Rift Valley fever virus vectors in Baringo, Kenya.
作者： Alfred O. Ochieng , Mark Nanyingi , Edwin Kipruto , Isabella M. Ondiba , Fred A. Amimo
DOI: 10.3402/IEE.V6.32322
关键词: Ecological niche 、 Culex 、 Culex quinquefasciatus 、 Rift Valley fever 、 Ecology 、 Vector (epidemiology) 、 Mansonia uniformis 、 Geography 、 Climate change scenario 、 Climate change
摘要: 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 distribution RVF species under climate change scenario demonstrate potential for geographic spread virus (RVFV). Objectives To evaluate effect in Baringo County, Kenya, with aim developing risk map spatial prediction outbreaks. Methodology The study used data ecological niche (MaxEnt) algorithm climatic habitat suitability vectors County. Data occurrence were obtained from longitudinal sampling adult mosquitoes larvae area. We present (2000) future (2050) Bioclim databases model distribution. Results Model results predicted suitable areas high success rates Culex quinquefasciatus, univitattus, Mansonia africana, uniformis. Under conditions, lowlands found be highly all species. Future conditions indicate increase Cx. quinquefasciatus M. africana . performance was statistically significant. Conclusion Soil types, precipitation driest quarter, seasonality, isothermality showed highest predictive four Keywords: fever; modelling; change; County (Published: 17 November 2016) Citation: Infection Ecology Epidemiology 2016, 6: 32322 - http://dx.doi.org/10.3402/iee.v6.32322
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