Forecasting Covid-19 New Cases in Afghanistan

Dr. Smartson. P. NYONIZICHIRe Project, University of Zimbabwe, Harare, ZimbabweMr. Thabani NYONISAGIT Innovation Center, Harare, ZimbabweMr. Tatenda. A. CHIHOHOIndependent Health Economist, Harare, Zimbabwe

Vol 5 No 6 (2021): Volume 5, Issue 6, June 2021 | Pages: 771-776

International Research Journal of Innovations in Engineering and Technology

OPEN ACCESS | Research Article | Published Date: 10-07-2021

doi Logo doi.org/10.47001/IRJIET/2021.506135

Abstract
In this work, the ANN approach was employed to analyze COVID-19 case volumes in Afghanistan. This study is based on daily new cases of COVID-19 in Afghanistan for the period 1 January 2020 – 25 March 2021. The out-of-sample forecast covers the period 26 March 2021 – 31 July 2021. The residuals and forecast evaluation criteria (Error, MSE and MAE) of the model indicate that it is stable. The results of the study suggest that the COVID-19 pandemic is likely to subside significantly over the out-of-sample period. The government should ensure continued compliance to COVID-19 mitigation measures such as social distancing, quarantine, isolation, face-mask wearing and so on., including COVID-19 vaccine uptake. 
Keywords

ANN, COVID-19, Forecasting, Zimbabwe, corona, pandemic


Citation of this Article

Dr. Smartson. P. NYONI, Mr. Thabani NYONI, Mr. Tatenda. A. CHIHOHO, “Forecasting Covid-19 New Cases in Afghanistan” Published in International Research Journal of Innovations in Engineering and Technology - IRJIET, Volume 5, Issue 6, pp 771-776, June 2021. Article DOI https://doi.org/10.47001/IRJIET/2021.506135

References
  1. Pathak, K. P., Ranabhat, C., & Chalise, H. N. (2020). Vaccines, Temperature, Latitude and Demography Could All be Reasons for Less Infection of Coronavirus in Nepal, Journal of Psychiatry and Mental Disorders, 5 (2): 1 – 2.
  2.  Ribeiro, M. H. D. M., et al. (2020). Short-term Forecasting of COVID-19 Cumulative Confirmed Cases: Perspectives for Brazil, Chaos, Solitons and Fractals, 138 (2020): 1 – 13.
  3. Singhal, A., et al. (2020). Modeling and Prediction of COVID-19 Pandemic Using Gaussian Mixture Model, Chaos, Solitons and Fractals, 138 (2020): 1 – 8.
  4.  Velasquez, R. M. A., & Lara, J. V. M. (2020). Forecast and Evaluation of COVID-19 Spreading in USA With Reduced-space Gaussian Process Regression, Chaos, Solitons and Fractals, 138 (2020): 1 – 9. 
  5. Yousaf, M., et al. (2020). Statistical Analysis of Forecasting COVID-19 for Upcoming Month in Pakistan, Chaos, Solitons and Fractals, 138 (2020): 1 – 15.