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 Daily New Covid-19 Cases in the Gambia Using the Artificial Neural Networks

Abstract

In this research paper, the ANN approach was applied to analyze daily new COVID-19 cases in Gambia. The employed data covers the period 1 January 2020 to 31 December 2020 and the out-of-sample period ranges over the period 1 January 2021 to 31 May 2021. The residuals and forecast evaluation criteria (Error, MSE and MAE) of the applied model indicate that the model is stable in forecasting daily COVID-19 in the Gambia. The results of the study indicate that Gambia is likely to witness another wave of infections over the period 1 January 2021 and 31 May 2021 as indicated by the out of sample forecasts. Therefore the government is encouraged to continue practicing WHO guidelines on prevention and control of COVID-19.

Country : Zimbabwe

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

  1. ZICHIRe Project, University of Zimbabwe, Harare, Zimbabwe
  2. SAGIT Innovation Centre, Harare, Zimbabwe
  3. Independent Researcher, Harare, Zimbabwe

IRJIET, Volume 5, Issue 3, March 2021 pp. 197-206

doi.org/10.47001/IRJIET/2021.503033

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References

  1. Banerjee A., Kulcsar K., & Misra V (2019). Bats and Coronaviruses. Viruses, 1:E41. Doi: 10.3390/ v11010041.
  2. Du Toit A (2020). Outbreak of a novel coronavirus. Nat Rev Microbial, 18:123. Doi: 10.1038/s41579-020- 0332-0.
  3. Fojnica, A., Osmanoviae & Badnjeviae A (2016). Dynamic model of tuberculosis-multiple strain prediction based on artificial neural network. In proceedings of the 2016 5th Mediterranean conference on embedded computing pp290-293
  4. Forster P., Forster L & Renfrew C (2020). Phylogenetic network analysis of SARS-CoV-2 genomes. Proc Malt Acad Sci U S A, 2020: (pii=202004999.). doi:10.1073/pnas.2004999117.
  5. Giovanetti M., Benvenuto D., Angeletti (2020). The first two cases of 2019-nCoV in Italy: where they come from? J Med Virol, 92:518–521. Doi: 10.1002/ jmv.25699.
  6. Hampton T (2005). Bats may be SARS reservoir. JAMA, 2005; 294:2291. doi:10.1001/jama.294.18.2291.
  7. Kaushik AC & Sahi. S (2018). Artificial neural network-based model for orphan GPCRs.Neural.Comput.Appl. 29,985-992
  8. Li W., Shi Z., Yu M (2005). Bats are natural reservoirs of SARS-like coronaviruses. Science, 310:676–679. doi:10.1126/science.1118391.
  9. Liu Z., Xiao X & Wei X (2020). Composition and divergence of coronavirus spike proteins and host ACE2 receptors predict potential intermediate hosts of SARS-CoV-2. J Med Virol, doi:10.1002/jmv.25726.
  10. Lu R., Zhao X & Li J (2020). Genomic characterization and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding. Lancet, 395:565–574. doi:10.1016/S0140-6736(20)30 251-8
  11. 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
  12. NCDC (2020). First case of corona virus disease confirmed in Nigeria. Available from: https://ncdc.gov.ng/news/227/first-case-ofcorona-virus-disease-confirmed-in-nigeria
  13. Paraskevis D., Kostaki EG., Magiorkinis G (2020). Full genome evolutionary analysis of the novel corona virus (2019-nCoV) rejects the hypothesis of emergence as a result of a recent recombination event. Infect Genet Evol, 79:104212. doi:10.1016/j.meegid. 2020.104212.
  14. 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
  15. Smartson. P. Nyoni., Thabani Nyoni & Tatenda A. Chihoho (2020). Forecasting COVID-19 cases in Ethiopia using artificial neural networks, IJARIIE, 6, 6, 2395-4396
  16. 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
  17. WHO (2020). COVID-19 cases top 10,000 in Africa. Available from: https://www. afro.who.int/news/covid-19-cases-top-10-000-africa
  18. WHO (2020).WHO announces COVID-19 outbreak a pandemic. Available from: http://www.euro.who. int/en/health-topics/health-emergencies/coronaviruscovid-19/news/news/2020/3/who-announces-covid
  19. Wu A., Peng Y & Huang B (2020). Genome composition and divergence of the novel corona virus (2019- nCoV) originating in China. Cell Host Microbe, 27:325–328. doi:10.1016/j.chom.2020.02.001.
  20. Zhang G P (2003), “Time series forecasting using a hybrid ARIMA and neural network model”, Neurocomputing 50: 159
  21. Zhou P., Yang XL, & Wang XG (2020). A pneumonia outbreak associated with a new coronavirus of probable bat origin. Nature, 579:270–273. Doi: 10. 1038/s41586-020-2012-7.
  22. Zhu N., Zhang D & Wang W (2020). A novel coronavirus from patients with pneumonia in China, 2019. N Engl J Med, 382:727–733. Doi: 10.1056/NEJMoa2001017.

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