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DOI Prefix: 10.47001/IRJIET

Forecasting TB Incidence in Yemen Using the Multilayer Perceptron Neural Network

Dr. Smartson. P. NYONIZICHIRe Project, University of Zimbabwe, Harare, ZimbabweThabani NYONIDepartment of Economics, University of Zimbabwe, Harare, Zimbabwe

Vol 5 No 3 (2021): Volume 5, Issue 3, March 2021 | Pages: 316-320

International Research Journal of Innovations in Engineering and Technology

OPEN ACCESS | Research Article | Published Date: 01-04-2021

doi Logo doi.org/10.47001/IRJIET/2021.503054

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Abstract

In this research paper, the ANN approach was applied to analyze TB incidence in Yemen. The employed 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 Yemen. The results of the study indicate that TB incidence will be around 48 cases/100 000 /year over the period 2019-2023. In order to contribute meaningfully to the national control strategy of a TB-free Yemen, authorities should, among other things, intensify TB surveillance and control programmes in order to reduce incidence to below 30 cases per 100 000/year.  

Keywords

ANN, Forecasting, TB incidence.


Citation of this Article

Dr. Smartson. P. NYONI, Thabani NYONI, “Forecasting TB Incidence in Yemen Using the Multilayer Perceptron Neural Network” Published in International Research Journal of Innovations in Engineering and Technology - IRJIET, Volume 5, Issue 3, pp 316-320, March 2021. Article DOI https://doi.org/10.47001/IRJIET/2021.503054

Licence Copyright (c) 2026 International Research Journal of Innovations in Engineering and Technology creative common licence This work is licensed under Creative common Attribution Non Commercial 4.0 Internation Licence
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