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 Chad

Abstract

In this study, the ANN approach was applied to analyze COVID-19 new cases in Chad. 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 COVID-19 cases are likely to increase up to around 70 cases per day over the out-of-sample period. Amongst other suggested policy directions, there is need for the government of Chad 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. 255-260

doi.org/10.47001/IRJIET/2021.506046

Full Paper
Download

References

  1. 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.
  2. 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
  3. Read et al (2020). Novel coronavirus 2019-nCoV: Earlyestimationofepidemiologicalparametersandepidemicpredictions. medRxiv:10.1101/2020.01.23.20018549
  4. 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,
  5. 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
  6. Smartson. P. Nyoni., Thabani Nyoni & Tatenda A. Chihoho (2020). Forecasting COVID-19 cases in Ethiopia using artificial neural networks, IJARIIE, 6, 6, 2395-4396
  7. 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
  8. Smartson. P. Nyoni., Thabani Nyoni., Tatenda. A. Chihoho (2021). Forecasting daily new Covid-19 cases in Botswana using artificial neural networks. International Journal of innovations in Engineering and Technology (IRJIET), 5 (3):177-186.
  9. 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.
  10. 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.
  11. Wang D et al (2020).  Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus–infected pneumonia in Wuhan, China. JAMA 323, 1061–1069.
  12. Wang H et al (2020). Phase-adjusted estimation of the number of coronavirus disease 2019 cases in Wuhan, China. Cell Discovery 6, 76.
  13. 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
  14. WHO (2020). Coronavirus Disease (COVID-19) Dashboard, Chad Coronavirus statistics. Total and daily confirmed cases and deaths. https://covid19.who.int/region/afro/country/td
  15. World Health Organization (2020). Weekly epidemiological update. Data as received by WHO from national authorities, as of 10 am CEST 13 September 2020
  16. Zita Aleyo Nodjikouambaye., Chatté Adawaye., Fissou Henry Yandai., & Laurent Bélec (2020).The late arrival of coronavirus disease 2019 (COVID-19) in Chad: mitigating spread in Ndjamena focused on specific target population. PAMJ - 37(338).

Copyright @ 2026-2017 IRJIET. All Right Reserved.

Developed by Byzero Technologies