Use of Bio-Physical Indicators to Map and Characterize Coping Strategies of Households to Rift Valley Fever Outbreaks in Ijara District-Kenya

Extended and above normal rainfall in the study after a warm phase of El Nio creates conditions favorable for an outbreak of Rift Valley Fever (RVF). We used geospatial techniques together with focus group discussions to map and characterize bio-physical indicators influencing the outbreak of Rift Valley Fever (RVF) in Ijara District, Kenya. By applying geo-statistical tools, a generalized linear model was used to characterize and differentiate RVF indices in the study area. Our results indicate that the occurrence of RVF is diametrically distributed between high and low risk areas approximately half-way across the study area. Households have put in place coping mechanisms and are able to cope with RVF outbreaks. However, communities living in high risk areas were found to have more strategic coping mechanisms while those at low risk areas use ad hoc coping strategies. Communities at high risk areas would therefore cope better with adverse climate variability and extended disease burden compared to those at low risk areas who have minimal knowledge of coping strategies.