International Research Journal of Innovations in Engineering and Technology - IRJIET International Open Access, Monthly, Peer Reviewed, Reputed Journal ISSN (online): 2581-3048

Impact Factor (2025): 6.9

DOI Prefix: 10.47001/IRJIET

Forecasting Covid-19 New Cases in Lithuania

Abstract

In this study, the ANN approach was applied to analyze COVID-19 new cases in Lithuania. The employed data covers the period 1 January 2020 – 25 March 2021 and the out-of-sample period ranges over the period 26 March – 31 July 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 that the pandemic will disappear in the country around early April 2021. Amongst other suggested policy directions, there is need for the government of Lithuania to ensure adherence to safety guidelines while continuing to create awareness about the COVID-19 pandemic.

Country : Zimbabwe

1 Dr. Smartson. P. NYONI2 Mr. Thabani NYONI3 Mr. Tatenda. A. CHIHOHO

  1. ZICHIRe Project, University of Zimbabwe, Harare, Zimbabwe
  2. SAGIT Innovation Center, Harare, Zimbabwe
  3. Independent Health Economist, Harare, Zimbabwe

IRJIET, Volume 5, Issue 6, June 2021 pp. 328-333

doi.org/10.47001/IRJIET/2021.506058

Full Paper
Download

References

  1. Government of the Republic of Lithuania (2020). Quarantine Announced throughout the Territory of the Republic of Lithuania (Attached Resolution). Available online: https://lrv.lt/en/news/quarantine-announcedthroughout-the-territ
  2. Maradze, T. C., Nyoni, S. P., & Nyoni, T (2021). Modeling and Forecasting COVID-19 mortalities in the United States of America using artificial neural networks (ANN). International Journal of innovations in Engineering and Technology (IRJIET), 5 (3):533-539
  3. Naizhuo Zhao., Katia Charland., Mabel Carabali., Elaine O., Nsoesie., Mathieu MaheuGiroux., Erin Rees., Mengru Yuan., Cesar Garcia Balaguera., Gloria Jaramillo Ramirez., & Kate Zinszer (2020). Machine learning and dengue forecasting: Comparing random forests and artificial neural networks for predicting dengue burden at national and sub-national scales in Colombia. PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0008056
  4. 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.
  5. \Roser M., Ritchie H., Ortiz-Ospina E., & Hasell J (2020). Coronavirus Pandemic (COVID-19). https://ourworldindata. Org/coronavirus/country/Lithuania? Country=~LTU.
  6. Vilma Kriaucioniene., Lina Bagdonaviciene., Celia Rodríguez-Pérez and Janina Petkeviciene (2020). Associations between Changes in Health Behaviours and Body Weight during the COVID-19 Quarantine in Lithuania: The Lithuanian COVIDiet Study, Nutrients 2020, 12, 3119; doi:10.3390/nu12103119

Copyright @ 2026-2017 IRJIET. All Right Reserved.

Developed by Byzero Technologies