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Forecasting Malaria Cases in Bujumbura

Authors: Hermenegilde Nkurunziza, Albrecht Gebhardt, Juergen Pilz


The focus in this work is to assess which method allows a better forecasting of malaria cases in Bujumbura ( Burundi) when taking into account association between climatic factors and the disease. For the period 1996-2007, real monthly data on both malaria epidemiology and climate in Bujumbura are described and analyzed. We propose a hierarchical approach to achieve our objective. We first fit a Generalized Additive Model to malaria cases to obtain an accurate predictor, which is then used to predict future observations. Various well-known forecasting methods are compared leading to different results. Based on in-sample mean average percentage error (MAPE), the multiplicative exponential smoothing state space model with multiplicative error and seasonality performed better.

Keywords: Forecasting, Malaria, State Space Model, Burundi, Regressionmodel

Digital Object Identifier (DOI):

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