Data-Driven Model for Animal Surveillance: Case of Pastoral Communities in Kajiado County, Kenya
Kenya Agricultural and Livestock Research Organization (KALRO)
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Abstract: The objective of this study was to test cognified distributed technology in handling data-driven models to generate data evidence that can be used to predict the next chances of disease re-occurrences. The study used the constructive research approach to develop a custom-made surveillance and reporting prototype that leverage high-performance computing resources and real-time weather forecast data from remote satellites. The prototype showed a tandem between the number of infections reported and the predicted chances of occurrence generated by the model. When the incoming data from different types, locations, and magnitudes are well formatted and compared with the historical data pattern, the computing resources can perform pattern and matching analysis to determine the next chances of disease occurrence. The technology can guide agricultural stakeholders, including policymakers, on early response mechanisms and vaccination prioritization.