Forecasting Covid-19 Deaths in Ukraine

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: 824-829

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/2021.506144

Abstract
COVID-19 has already brought unprecedented challenges for public health and resulted in huge numbers of cases and deaths across the globe. In this study, the ANN approach was applied to analyze COVID-19 deaths in Ukraine. This study is based on daily COVID-19 deaths in Ukraine for the period 1 January 2020 – 20 April 2021. The out-of-sample forecast covers the period 21 April – 31 August 2021.The residuals and forecast evaluation criteria (Error, MSE and MAE) of the applied model indicate that the model is quite stable. It is projected that daily COVID-19 deaths in Ukraine are likely to remain high over the out-of-sample period. Amongst other suggested policy directions, there is need for the government of Ukraine to ensure adherence to safety guidelines while continuing to create awareness about the COVID-19 pandemic as well as scaling up vaccinations.
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 Deaths in Ukraine” Published in International Research Journal of Innovations in Engineering and Technology - IRJIET, Volume 5, Issue 6, pp 824-829, June 2021. Article DOI https://doi.org/10.47001/IRJIET/2021.506144

References
  1. Ferguson, N.M., Laydon, D., Nedjati-Gilani, G., Imai, N., Ainslie, K., Baguelin, M., Bhatia, S., Boonyasiri, A., Cucunubá, Z., Cuomo-Dannenburg, G (2020). Impact of Non-Pharmaceutical Interventions (NPIs) to Reduce COVID-19 Mortality and Healthcare Demand; Imperial College: London, UK.
  2. He, X., Lau, E.H.Y., Wu, P., Deng, X., Wang, J., Hao, X., Lau, Y.C., Wong, J.Y., Guan, Y., Tan, X (2020). Temporal dynamics in viral shedding and transmissibility of COVID-19. Nat. Med. 2020, 26, 672–675.
  3. Jordan times (2020). Jordan’s Extraordinary Measures to Contain COVID-19 Spread Draw Int’l Accolades (Jordan Times, 2 April 2020
  4. Maradze, T. C., Nyoni, S. P., & Nyoni, T (2021). Modeling and Forecasting Child immunization against measles disease in Djibouti using artificial neural networks (ANNs). International Journal of innovations in Engineering and Technology (IRJIET), 5 (3):449-452.
  5. Nyoni, S. P., & Nyoni, T (2021). Forecasting ART coverage in Egypt using artificial neural networks. International Journal of Innovations in Engineering and Technology (IRJIET), 5 (3): 161-165.
  6. UN (2020). Socio-economic framework for Jordan COVID-19 response, pp 1-44
  7. Wong, A.C.-P., Li, X., Lau, S.K.P., & Woo, P.C.Y (2019). Global Epidemiology of Bat Coronaviruses. Viruses 2019, 11, 174.
  8. World Health Organization (2020). 2019 Novel Coronavirus (2019-nCoV): Strategic Preparedness and Response Plan; WHO: Geneva, Switzerland.
  9. Yu, F., Du, L., Ojcius, D.M., Pan, C., & Jiang, S (2020). Measures for diagnosing and treating infections by a novel coronavirus responsible for a pneumonia outbreak originating in Wuhan, China. Microbes Infect. 2020, 22, 74–79.