Modeling and Forecasting Annual TB Incidence in Mauritania Using Artificial Neural Networks
Abstract
In this piece of work the ANN approach was applied to analyze TB
incidence in Mauritania. The employed annual data covers the period 2000-2018
and the out-of-sample period ranges over the period 2019-2023. The residuals
and forecast evaluation criteria (Error, MSE and MAE) of the applied model
indicate that the model is stable in forecasting TB incidence in Mauritania.
The results of the study indicate that TB incidence will continue on a downward
trajectory over the period 2019-2023. The government is encouraged to intensify
TB surveillance and control programs in order to significantly reduce the
incidence of TB.
Country : Zimbabwe
1 Dr. Smartson. P. NYONI2 Thabani NYONI
ZICHIRe Project, University of Zimbabwe, Harare, Zimbabwe
Department of Economics, University of Zimbabwe, Harare, Zimbabwe
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