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 (R 2 ) 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.
Indigenous chicken production system has long been characterised by low productivity due to among other factors, poor management, inadequate and poor feeding regime, poor (or lack) ISSN 2166-0379 2015 www.macrothink.org/jas 146 of disease control measures, poor hygiene, inappropriate housing, negative attitudes, lack of technical knowledge and lack of institutional support in terms of policy and infrastructure. This research was carried out to evaluate uptake by farmers of improved management practices (interventions) and their effect on performance of indigenous chickens at farm level and consequences for farmer participation in the implementation of research activities. The research involved 200 farmers in five regions in three counties. Four villages were selected per region and10 farms in each village. Interventions housing, feed supplementation, vaccination and deworming were implemented by farmers and monitoring and evaluation carried out. Farmers used own local inputs in implementing the project interventions and recorded various project activities and outputs. The project was monitored over a span of five, 3-months long periods. 25% of farmers in the entire five regions did not have housing as a treatment in any of 5 periods. Feed supplementation had high level of use by all farmers in each period. More farmers applied deworming in later periods, 25% had vaccination in period 1, and 40% in period 5. Periods 3 -5 generally seem to be the time most applications were done. Flock sizes rose from 10 -20 birds per farm to 20 -30. Farmer participatory research is a tool for technology testing and transfer and a quick and effective means of generating and disseminating information.
Journal of Agricultural Studies
Diarrheal diseases often attributable to poor sanitary conditions and fecal contamination of drinking water remain a leading cause of mortality for children younger than five years. Water contaminated with human faeces, for example from municipal sewage, septic tanks and latrines, is of particular concern. Animal faeces also contain microorganisms that can cause diarrhea. Kakamega County in Kenya has a diarrhea prevalence rate of 20.2%, which is the highest in the country; a good proportion of these cases are believed to be water borne. This study was designed to determine
Original Research Article
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