Prediction of the Annual TB Incidence in Niger Using Artificial Neural Networks
Abstract
In this research article, the ANN approach was applied to analyze TB
incidence in Niger. 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 Niger. The model
predictions suggest that TB incidence will continue to decline over the period
2019-2023. Therefore the government is encouraged to intensify TB surveillance
and TB control programs among other measures.
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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