Analysis and Modeling of Prevalence of Measles In The Ashanti Region of Ghana
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Date
2012
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Abstract
In this thesis, autoregressive integrated moving average (ARIMA) model is used to predict the prevalence and incidence of measles in the Ashanti Region of Ghana. The Mean Absolute Error (MAE) and the Mean Square Error (MSE) are used to compare the in-sample forecasting performance of four selected candidates‟ models. The working data from the Ashanti Health Services spans from 2001 to 2011. It is evident from the analysis that measles data in the Ashanti Region of Ghana could best be modelled with ARIMA (2, 1, 1) and that measles prevalence in the Ashanti Region is expected to increase if no preventative measures are taken. The forecasting accuracy using MAE for ARIMA (2, 1, 1) is calculated as 28.1141 and the forecasting accuracy using MSE for ARIMA (2, 1, 1) is calculated as 2947.15. The results of the study recommend to the stakeholders of Ashanti Region that a combination of increased vaccination of newborns and immunization of susceptible adults would reduce measles prevalence in the region to the minimum and therefore must be taken into consideration in the region’s vaccination programs.
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A thesis submitted to the Board of Postgraduate Studies, Kwame Nkrumah University of Science and Technology, Kumasi, in partial fulfilment of the requirements for the award of the Degree of Master of Philosophy in Applied Mathematics, 2012