Nepal’s TB Program Success to Be Reversed over the Period 2019-2023: Evidence from Artificial Neural Networks
Abstract
Tracking the evolution of the TB epidemic in Nepal is important in order
to stimulate a timeous evidence based national heath response. In this research
article, the ANN approach was applied to analyze TB incidence in Nepal. 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 Nepal. The model predicted that over the
period 2019-2023 TB incidences will rise sharply. Therefore, Health authorities
in Nepal should seriously consider intensification of TB surveillance and
control programs in order to reverse the undesirable model predictions.
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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