Christopher Oludhe

Ecological niche modelling of Rift Valley fever virus vectors in Baringo, Kenya.

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). Objectives 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. 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. Results Model results predicted potential suitable areas with high success rates for Culex quinquefasciatus, Culex univitattus, Mansonia africana, and Mansonia 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 of Cx. quinquefasciatus and M. africana. Model performance was statistically significant. Conclusion Soil types, precipitation in the driest quarter, precipitation seasonality, and isothermality showed the highest predictive potential for the four species.

Chapter 10 – Renewable Energy Resources in Kenya

Abstract Energy is an important input in a countrys development process since it provides the stimulus, drive and momentum for socioeconomic development. It forms one of the foundations on which the three key pillars of the Kenya Vision 2030 (Economic, Social and Political Governance) are anchored on. The country therefore needs to generate more energy and increase efficiency in energy consumption in order to realize Vision 2030 and the overall socioeconomic growth in the country. Kenya is endowed with significant amounts of renewable energy resources such as wind, solar, geothermal, small hydro and biomass. However, few renewable energy resources in the country have been fully assessed, mapped and appraised for their technical and economic viability. If harnessed, these resources can play a significant role in the countrys energy supply mix. Kenya has made a significant effort to assess wind, solar and small-hydro potential in the country. However, comprehensive assessment, mapping and appraisal of all the renewable energy resources in the country have not been fully done in order to determine their technical and economic viability. The sections below present the renewable energy situation in Kenya.

Statistical characteristics of the surface wind speeds over Kenya

In this study attempts were made to fit several statistical distributions to the surface maximum, minimum and mean daily wind speed records at 24 Kenyan sites. The statistical distributions fitted included the 2 and 3 parameter Lognormal, Pearson type III, Log Pearson type III, the 2 and 3 parameter Weibull distributions. The various parameters for these distributions were obtained from the methods of moments and maximum likelihood. The goodness of fit of the various distributions were investigated at each of the 24 sites using the Kolmogorov-Smirnov and x2 tests. The corresponding standard errors were also computed.