Forecasting Covid-19 New Cases in Bahamas

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: 749-753

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/2021.506131

Abstract
Caused by a novel coronavirus, COVID-19 has played havoc on many countries across the globe and the Bahamas have never been an exception. Just like the rest of the world, the country continues to live a restricted environment in order to prevent exposure to this highly infectious disease. In this research article, the ANN approach was used to model and forecast daily COVID-19 cases in Bahamas. This study is based on daily new cases of COVID-19 in Bahamas 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 applied model show us that the model is stable in forecasting COVID-19 daily new infections in Bahamas. The results of the study indicate that daily COVID-19 cases in Bahamas are likely to hover around 55 cases per day over the out-of-sample period. We encourage government of the Bahamas to continue enforcing control and preventive measures such as mass-media sensitization, social distancing, face-mask wearing, contact tracing, disinfection and decontamination of infected areas, washing and sanitization of hands and so on as advised by the WHO. 
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 Bahamas” Published in International Research Journal of Innovations in Engineering and Technology - IRJIET, Volume 5, Issue 6, pp 749-753, June 2021. Article DOI https://doi.org/10.47001/IRJIET/2021.506131

References
  1. Singhal, A., et al. (2020). Modeling and Prediction of COVID-19 Pandemic Using Gaussian Mixture Model, Chaos, Solitons and Fractals, 138 (2020): 1 – 8.
  2. 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.