You are invited to the Microsoft Africa Research Institute (MARI) Seminar, where Professor Muthoni Masinde, Head of CUT's Department of Information Technology will present on the topic: A Prediction Model for Malaria using an Ensemble of Machine Learning and Hydrological Drought Indices.

About the research
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.

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