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DOI Prefix: 10.47001/IRJIET

Modelling and Forecasting Covid-19 Mortalities in the United States of America Using Artificial Neural Networks (ANN)

Mr. Takudzwa. C. MaradzeIndependent Researcher, Harare, ZimbabweDr. Smartson. P. NYONIZICHIRe Project, University of Zimbabwe, Harare, ZimbabweMr. Thabani NYONISAGIT Innovation Center, Harare, Zimbabwe

Vol 5 No 3 (2021): Volume 5, Issue 3, March 2021 | Pages: 533-539

International Research Journal of Innovations in Engineering and Technology

OPEN ACCESS | Research Article | Published Date: 05-04-2021

doi Logo doi.org/10.47001/IRJIET/2021.503090

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Abstract
In this research paper, the ANN approach was employed to analyze COVID-19 deaths in the United States of America (USA). The employed data covers the period January – December 2020 and the out-of-sample period ranges over the period January – May 2021. The residuals and forecast evaluation criteria (Error, MSE and MAE) of the applied model indicate that the model is quite stable. The results of the study indicate thatCOVID-19 deaths in the USA will continue to decline significantly in the out-of-sample period. Amongst other policy prescriptions, we strongly advise the US government to continue ensuring strict adherence to COVID-19 guidelines.
Keywords

Modelling, Artificial Neural Networks, ANN.


Citation of this Article

Mr. Takudzwa. C. Maradze, Dr. Smartson. P. NYONI, Mr. Thabani NYONI, “Modelling and Forecasting Covid-19 Mortalities in the United States of America Using Artificial Neural Networks (ANN)” Published in International Research Journal of Innovations in Engineering and Technology - IRJIET, Volume 5, Issue 3, pp 533-539, March 2021. Article DOI https://doi.org/10.47001/IRJIET/2021.503090

Licence Copyright (c) 2026 International Research Journal of Innovations in Engineering and Technology creative common licence This work is licensed under Creative common Attribution Non Commercial 4.0 Internation Licence
References
  1. Brown, Patrick, Prabhat Jha, and CGHR COVID Mortality Consortium. "Mortality from COVID-19 in 12 countries and 6 states of the United States." medRxiv (2020).
  2. COVID, IHME, and Christopher JL Murray. "Forecasting COVID-19 impact on hospital bed-days, ICU-days, ventilator-days and deaths by US state in the next 4 months." MedRxiv (2020).
  3. Gold, Jeremy AW, Lauren M. Rossen, Farida B. Ahmad, Paul Sutton, Zeyu Li, Phillip P. Salvatore, Jayme P. Coyle et al. "Race, ethnicity, and age trends in persons who died from COVID-19—United States, May–August 2020." Morbidity and Mortality Weekly Report 69, no. 42 (2020): 1517.
  4. Hui, David S., Esam I. Azhar, Tariq A. Madani, Francine Ntoumi, Richard Kock, Osman Dar, Giuseppe Ippolito et al. "The continuing 2019-nCoV epidemic threat of novel coronaviruses to global health—The latest 2019 novel coronavirus outbreak in Wuhan, China." International journal of infectious diseases 91 (2020): 264-266.
  5. Ioannidis, John PA. "Infection fatality rate of COVID-19 inferred from seroprevalence data." Bulletin of the World Health Organization 99, no. 1 (2021): 19
  6. Mollalo, Abolfazl, Kiara M. Rivera, and Behzad Vahedi. "Artificial neural network modeling of novel coronavirus (COVID-19) incidence rates across the continental United States." International journal of environmental research and public health 17, no. 12 (2020): 4204.
  7. WHO. Coronavirus disease 2019 (COVID-19) Situation Report – 62. March 2020.https://www.who.int/emergencies/diseases/novel-coronavirus-2019/situation-reports.Accessed March 16, 2021.
  8. World Health Organization. WHO Coronavirus Disease (COVID-19) Dashboard. Available online: https://covid19.who.int (accessed on 4 March 2021).

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