Strengthening the Health Information System in Mozambique through Malaria Incidence Prediction
2013 (English)In: IST-Africa 2013 Conference Proceedings / [ed] Paul Cunningham, Miriam Cunningham, IEEE Computer Society, 2013, 1-7 p.Conference paper (Refereed)
Malaria is one of the principal health problems in Mozambique, affecting mostly children. The prediction of accurate future incidence cases is crucial for the implementation of appropriate policies of intervention and disease control in order to strengthen the health system. We propose a model based on support vector machines (SVM) for predicting yearly malaria incidence cases for children 0-4 years of age in the Maputo province, Mozambique. The predictive model is trained on two years of historical malaria data in combination with climatic and malaria control factors. A grid optimization parameter tuning procedure was firstly employed to detect the best parameters and select the kernel. In order to determine the most influential factors, variable importance was calculated through estimating the impact of permuting feature values on the predictive performance. The most important malaria incidence predictors turned out to be temperature variation, followed by Matutuine (district), April (month) and Namaacha (district).
Place, publisher, year, edition, pages
IEEE Computer Society, 2013. 1-7 p.
Prediction, Malaria Incidence, Support Vector Regression, Data Mining
Research subject Computer and Systems Sciences
IdentifiersURN: urn:nbn:se:su:diva-97750ISBN: 978-1-905824-38-0OAI: oai:DiVA.org:su-97750DiVA: diva2:679980
IST-Africa 2013, 29 - 31 May, Nairobi, Kenya