Forecasting Daily New Covid-19 Cases in the Gambia Using the Artificial Neural Networks

Dr. Smartson. P. NYONIZICHIRe Project, University of Zimbabwe, Harare, ZimbabweThabani NYONISAGIT Innovation Centre, Harare, ZimbabweTatenda. A. CHIHOHOIndependent Researcher, Harare, Zimbabwe

Vol 5 No 3 (2021): Volume 5, Issue 3, March 2021 | Pages: 197-206

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/2021.503033

Abstract
In this research paper, the ANN approach was applied to analyze daily new COVID-19 cases in Gambia. The employed data covers the period 1 January 2020 to 31 December 2020 and the out-of-sample period ranges over the period 1 January 2021 to 31 May 2021. The residuals and forecast evaluation criteria (Error, MSE and MAE) of the applied model indicate that the model is stable in forecasting daily COVID-19 in the Gambia. The results of the study indicate that Gambia is likely to witness another wave of infections over the period 1 January 2021 and 31 May 2021 as indicated by the out of sample forecasts. Therefore the government is encouraged to continue practicing WHO guidelines on prevention and control of COVID-19.
Keywords

ANN, Forecasting, COVID-19.


Citation of this Article

Dr. Smartson. P. NYONI, Thabani NYONI, Tatenda. A. CHIHOHO, “Forecasting Daily New Covid-19 Cases in the Gambia Using the Artificial Neural Networks” Published in International Research Journal of Innovations in Engineering and Technology - IRJIET, Volume 5, Issue 3, pp 197-206, March 2021. Article DOI https://doi.org/10.47001/IRJIET/2021.503033
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