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Forecasting Malaria Cases in Bujumbura
Abstract: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.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1084260Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1715
 A. Gomez-Elipe, Otero A, M. Van Herp and A.Aguirre-Jaime, "Forecasting malaria incidence based on monthly case reports and environmental factors in Karuzi, Burundi, 1997-2003," Malaria Journal 2007, 6:129, 1-10.
 R. J. Hynman, A. B. Koehler, J. K. Ord, and R. D.Snyder, Forecasting with exponential smoothing: the state space approach. Springer, 2008.
 R. J. Hyndman, M. Akram, and B. C. Archibal, " The admissible parameter space for exponential smoothing models," Annals of the Institute of Statistical Mathematics 2008, 60: 407-426.
 D. C. Medina, E. S. Findley, and S. Doumbia " State-Space Forecast of Schistosoma haematobium Time-Series in Niono, Mali," PLOS neglected tropical diseases 2008, 8: 1-12.
 Ministry of Health in Burundi , EPISTAT.
 Ministry of Planning and Environment in Burundi, IGEBU.
 WHO: Stratégie de coopération de l-OMS avec les pays. République du Burundi 2005-2009.
 T. A. Abeku, S. J. De Vlas, G. Borsboom, A.Teklehaimanot, A. Kebede, D. Olana, G. J. Van Oortmarssen, and J. D. Habbema, "Forecasting malaria incidence from historical morbidity patterns in epidemic-prone areas of Ethiopia: a simple seasonal adjustment method performs best," Tropical Meicine of International Health 2002, 7(10):851-7.
 H. Pruscha, "Residual and forecast methods in time series models with covariates," Collaborative Research Center 386, University of Munich, 1996.
 M. J. Bouma , C. Dye , and H. J. Van der Kaay , "Falciparum malaria and climate change in the North West Frontier Province of Pakistan," American Journal of Tropical Medicine and Hygiene 1996,55:131-137.
 A. J. Dobson. An Introduction to Generalized Linear Models. Second Edition, Chapman & Hall, 2002.
 P.J.Diggle, P. Heagerty , K.Y. Liang S., and Zeger, Analysis of Longitudinal Data. Oxford Science Publications, 1994.
 T. J. Hastie and R. J. Tibshirani, Generalized Additive Models. Chapman & Hall, 1997.
 L. Fahrmeir and G. Tutz, Multivariate Statistical Modelling based on generalized linear models. Springer, 2001.
 S. Wang, Exponential Smoothing for Forecasting and Bayesian Validation of Computer Models, Thesis, Georgia Institute of Technology , 2006.
 R. J. Hyndman, A. B. Koehler, R.D. Snyder, and S. Grose, "A state space framework for automatic forecasting using exponential smoothing methods," International Journal of Forecasting 2002, 18: 439- 454.
 R. J. Hyndman and A. B. Koehler, "Another look at measures of forecast accuracy," International Journal of Forecasting 2006, 22: 679- 688.