Forecasting TB Incidence in Myanmar Using the Multilayer Peceptron Neural Network

Abstract

Myanmar is a high TB burden country and forecasting methods can assist uncover the future evolution of the epidemic. In this research paper, the ANN approach was applied to analyze TB incidence in Myanmar. The employed annual data covers the period 2000-2018 and the out-of-sample period ranges over the period January 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 Myanmar. The results of the study indicate that TB incidence will remain high at constant level of 326 cases per 100 000 population/year over the period 2019-2023. In order to contribute significantly to the national control strategy of a TB-free Myanmar, the government should, among other things, intensify TB surveillance and control programs. 

Country : Zimbabwe

1 Dr. Smartson. P. NYONI2 Thabani NYONI

  1. ZICHIRe Project, University of Zimbabwe, Harare, Zimbabwe
  2. Department of Economics, University of Zimbabwe, Harare, Zimbabwe

IRJIET, Volume 5, Issue 3, March 2021 pp. 367-370

doi.org/10.47001/IRJIET/2021.503063

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