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DOI Prefix: 10.47001/IRJIET

Forecasting Art Coverage in Gabon Using the Artificial Neural Network Model

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: 150-155

International Research Journal of Innovations in Engineering and Technology

OPEN ACCESS | Research Article | Published Date: 31-03-2021

doi Logo doi.org/10.47001/IRJIET/2021.503026

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Abstract

In this paper, the ANN approach was applied to analyze annual ART coverage in Gabon. 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 ART coverage in Gabon. The ANN (9,12,1) model predictions suggest that ART coverage will be around 70% throughout the period 2019-2023. The government is strongly encouraged to intensify demand creation for HIV testing and ART services, strengthen the system of tracking loss to follow up ART clients and allocating more resources for TB/HIV collaboration. 

Keywords

ANN, ART coverage, Forecasting.


Citation of this Article

Dr. Smartson. P. NYONI, Thabani NYONI, “Forecasting Art Coverage in Gabon Using the Artificial Neural Network Model” Published in International Research Journal of Innovations in Engineering and Technology - IRJIET, Volume 5, Issue 3, pp 150-155, March 2021. Article DOI https://doi.org/10.47001/IRJIET/2021.503026

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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