Browsing by Author "Wakhungu, Jacob."

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Dynamic risk model for rift valley fever outbreaks in Kenya based on climate and disease outbreak data
(Geospatial health, 2016-05-31) Gikungu, David.; Wakhungu, Jacob.; Siamba, Donald N.; Neyole, Edward.; Muita, Richard.; Bett, Bernard.
Rift Valley fever (RVF) is a mosquito-borne viral zoonotic disease that occurs throughout sub-Saharan Africa, Egypt and the Arabian Peninsula, with heavy impact in affected countries. Outbreaks are episodic and related to climate variability, especially rainfall and flooding. Despite great strides towards better prediction of RVF epidemics, there is still no observed climate data-based warning system with sufficient lead time for appropriate response and mitigation. We present a dynamic risk model based on historical RVF outbreaks and observed meteorological data. The model uses 30-year data on rainfall, temperature, relative humidity, normalised difference vegetation index and sea surface temperature data as predictors. Our research on RVF focused on Garissa, Murang’a and Kwale counties in Kenya using a research design based on a correlational, experimental, and evaluational approach. The weather data were obtained from the Kenya Meteorological Department while the RVF data were acquired from International Livestock Research Institute, and the Department of Veterinary Services. Performance of the model was evaluated by using the first 70% of the data for calibration and the remaining 30% for validation. The assessed components of the model accurately predicted already observed RVF events. The Brier score for each of the models (ranging from 0.007 to 0.022) indicated high skill. The coefficient of determination (R2) was higher in Garissa (0.66) than in Murang’a (0.21) and Kwale (0.16). The discrepancy was attributed to data distribution differences and varying ecosystems. The model outputs should complement existing early warning systems to detect risk factors that predispose for RVF outbreaks.
Sustainable growth of the Kenyan dairy sector : a quick scan of robustness, reliability and resilience
(Journal of international academic research for multidisciplinary, 2016) Nabiswa, Koyi.; Patrick; Wakhungu, Jacob.; Siamba, Donald N.; Wanyama, Kadian Wanyonyi.
This report provides an overview of how the Kenyan dairy sector performs in three analytical domains: the robustness of the supply chains, the reliability of institutional governance and the resilience of the innovation system. Analysis is by literature review, stakeholder interviews and a validation workshop guided by a SWOT framework to identify strengths, weaknesses, opportunities and threats. The findings inform the existing opportunities and challenges that potentially impede growth in the sector. The report is a first step towards documenting and sharing insights that support the move towards a more Robust, Reliable and Resilient (3R) dairy sector. The findings and recommendations presented will guide policy engagement and action in the transition of Dutch government bilateral engagement in Kenya from development aid–support to a trade approach in the agricultural sector, with a focus on partnering opportunities to drive competitive market-oriented dairy sector development that attracts investments.