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Please use this identifier to cite or link to this item: http://hdl.handle.net/10204/2762

Title: Comparison of various modelling approaches applied to cholera case data
Authors: Van Den Bergh, F
Holloway, JP
Pienaar, M
Koen, R
Elphinstone, CD
Woodborne, S
Keywords: Cholera
Modelling
Signal processing
Dynamic regression
Negative binomial regression
Cross-wavelet analysis
Wavelet analysis
Issue Date: Jun-2008
Citation: Van Den Bergh, F, Holloway, JP et al. 2008. Comparison of various modelling approaches applied to cholera case data. Orion: Journal of the Operations Research Society of South Africa, Vol 24(1), pp 17-36
Abstract: The application of a methodology that proposes the use of spectral methods to inform the development of statistical forecasting models for cholera case data is explored in this paper. The seasonal behaviour of the target variable (cholera cases) is analysed using singular spectrum analysis followed by spectrum estimation using the maximum entropy method. This seasonal behaviour is compared to that of environmental variables (rainfall and temperature). The spectral analysis is re ned by means of a cross-wavelet technique, which is used to compute lead times for co-varying variables, and suggests transformations that enhance co-varying behaviour. Several statistical modelling techniques, including generalised linear models, ARIMA time series modelling, and dynamic regression are investigated for the purpose of developing a cholera cases forecast model fed by environmental variables. The analyses are demonstrated on data collected from Beira, Mozambique. Dynamic regression was found to be the preferred forecasting method for this data set
Description: Copyright: 2008 Operations Research Society of South Africa (ORSSA)
URI: http://www.ajol.info/viewarticle.php?jid=239&id=36998&layout=abstract
http://hdl.handle.net/10204/2762
ISSN: 0529-191-X
Appears in Collections:Water resources and human health
General science, engineering & technology

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