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 Fiji Islands

Abstract

In this study, the ANN approach was applied to analyze COVID-19 new cases in Fiji Islands. 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 no cases of COVID-19 are likely to be experienced over the out-of-sample period. Amongst other suggested policy directions, there is need for the authorities in Fiji Islands 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. 214-217

doi.org/10.47001/IRJIET/2021.506039

Full Paper
Download

References

  1. CDC (2020). The Novel Coronavirus Pneumonia Emergency Response Epidemiology Team, The epidemiological characteristics of an outbreak of 2019 novel coronavirus diseases (COVID-19) in China. China CDC Weekly 2, 113–122
  2. Garda World. (2020). Fiji: Authorities announce changes to curfew and further relax COVID-19 restrictions on June 22 /update 9. Garda World. Retrieved from https://www.garda.com/crisis24/news-alerts/353446/fiji-authoritiesannounce-changes-to-curfew-and-further-relax-covid-19-restrictions-on-june-22-upd
  3. 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
  4. 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
  5. Nyoni, S. P., & Nyoni, T (2021). Forecasting ART coverage in Kenya using the Multilayer perceptron neural network. International Journal of Innovations in Engineering and Technology (IRJIET), 5 (3): 161-165.
  6. Nyoni, S. P., & Nyoni, T (2021). Forecasting ART coverage in South Africa using the Multilayer perceptron neural network. International Journal of Innovations in Engineering and Technology (IRJIET), 5 (3): 207-211.
  7. Nyoni, S. P., & Nyoni, T (2021). Predicting TB incidence in Zimbabwe: Artificial neural networks reveal TB program success, IRJIET, 5(3): 380-384.
  8. Read et al (2020). Novel coronavirus 2019-nCoV: Earlyestimationofepidemiologicalparametersandepidemicpredictions. medRxiv:10.1101/2020.01.23.20018549
  9. Smartson P. Nyoni., Thabani Nyoni & Tatenda. A. Chihoho (2020). Prediction of daily new COVID-19 cases in Italy using artificial neural netwotks. IJARIIE-ISSN(O)-2395-4396 Vol-6 Issue-6 2020,
  10. Smartson. P. Nyoni, Thabani Nyoni, Tatenda. A. Chihoho (2020) Prediction of new Covid-19 cases in Ghana using artificial neural networks. IJARIIE Vol-6 Issue-6             2395-4396
  11. Smartson. P. Nyoni., Thabani Nyoni & Tatenda A. Chihoho (2020). Forecasting COVID-19 cases in Ethiopia using artificial neural networks, IJARIIE, 6, 6, 2395-4396
  12. Smartson. P. Nyoni., Thabani Nyoni., Tatenda. A. Chihoho (2020). Prediction of daily new Covid-19 cases in Egypt using artificial neural networks. IJARIIE-  Vol-6 Issue-6         2395-4396
  13. Tang. B et al (2020).  An updated estimation of the risk of transmission of the novel coronavirus (2019-nCoV). Infectious Disease Modelling 5, 248–255.
  14. Tang. B et al (2020). Estimation of the transmission risk of the 2019-nCoV and its implication for public health interventions. J. Clinical Med. 9, 462.
  15. United Nations. (2020). UNCT Fiji COVID-19 Multi-sectorial response Plan. Suva: United Nations. World Health Organization (WHO). (2011). Global tuberculosis control: WHO report 2011. World Health Organization. Retrieved from https://apps.who.int/iris/handle/10665/44728
  16. Wang D et al (2020).  Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus–infected pneumonia in Wuhan, China. JAMA 323, 1061–1069.
  17. Wang H et al (2020). Phase-adjusted estimation of the number of coronavirus disease 2019 cases in Wuhan, China. Cell Discovery 6, 76.
  18. Wang. W et al (2020). Updated understanding of the outbreak of 2019 novel coronavirus (2019-nCoV) in Wuhan, China. J. Med. Virology 92, 441–447.

Copyright @ 2026-2017 IRJIET. All Right Reserved.

Developed by Byzero Technologies