Forecasting Art Coverage in the Kingdom of Eswatini Using Artificial Neural Networks

In this research article, the ANN approach was applied to analyze ART coverage in the Kingdom of Eswatini. 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 ART coverage in Eswatini Kingdom. The ANN (9, 12, 1) model predictions suggest that the Kingdom is likely to record a high ART coverage which will be around 88% over the period 2019-2023.The authorities should therefore strengthen TB/HIV collaboration, create more demand for ART services and strengthen tracking of loss to follow up ART clients to improve adherence and clinical outcomes of HIV/TB treatment.