We’d like to extend an invitation to you for Microsoft Africa Research Institute (MARI) Seminar this month with our guest speaker Prof Muthoni Masinde, a Professor and the Head of the IT Department at the Central University of Technology, Free State (South Africa).
Topic: A Prediction Model for Malaria using an Ensemble of Machine Learning and Hydrological Drought Indices.
Abstract: Literature is awash with evidence that points to climate change as one of the reasons for the upward increase in infectious disease outbreaks around the globe. With the advancement in Artificial Intelligence (AI) and big climate data, accurate analysis of medical and climate data allows prediction and early detection of infectious diseases associated with climate change. The effectiveness of AI and drought indices in predicting oncoming droughts has been demonstrated elsewhere in research, this has however not been explored in the prediction of infectious diseases. We present a model that uses machine learning to predict the outbreak of infectious diseases using two drought indices and historical incidents of malaria in Limpopo (South Africa). Having achieved up to 99% prediction accuracies, we demonstrate that such a model equips stakeholders with a new perspective when it comes to prediction of infectious diseases’ outbreaks that are associated with extreme climate variations.
When: 24th August 2022 from 3:00PM – 4:00PM EAT
Droughts remain the number one disaster in Africa, and of all the people affected by all types of disasters, drought is responsible for over 88% of them. There is currently no appropriate drought-forecasting tool for smallholder farmers. Farmers continue to rely on their indigenous knowledge to reach critical cropping decisions.
Our drought early warning system forecasting tool integrates indigenous and scientific drought forecasting and uses a mobile application, a web portal, and SMS service to pool weather information through a network of sensors that monitor weather conditions for smallholder farmers. The system is anchored on the novel integration framework called Information Technology and Indigenous Knowledge with Intelligence (ITIKI), forecasts are available via the ITIKI Smartphone App and USSD service.
Indigenous knowledge ensures that the system is relevant, acceptable and resilient. ITIKI further employs three ICTs (mobile phones, wireless sensor networks, and artificial intelligence) to enhance the system’s effectiveness, affordability, sustainability, and intelligence.
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