IDEAS home Printed from https://ideas.repec.org/a/bjf/journl/v5y2020i8p141-144.html
   My bibliography  Save this article

Forecasting the Confirmed Cases of COVID-19 in Selected West African Countries Using ARIMA Model Technique

Author

Listed:
  • Musa Ganaka Kubi

    (Department of Mathematics and Statistics, Federal Polytechnic, Nasarawa, Nasarawa State, Nigeria)

  • Son-Allah Mallaka Philemon

    (Department of Management & Information Technology, ATBU, Bauchi, Nigeria)

  • Olope Ganiu Ibrahim

    (Department of Mathematical Sciences, ATBU, Bauchi, Nigeria)

Abstract

COVID-19 is a disease caused by the novel coronavirus that was reported in China in 2019. The virus has infected more than a million people globally leading to hundred-thousands of deaths. Hence, forecasting the future confirmed cases to support prevention of the disease and aid in the healthcare service preparation is very important especially in developing countries. In order to support governments’ effort in the prevention of COVID-19, we developed an ARIMA model which was used in forecasting future COVID-19 cases in selected West African Countries. The forecasting results from this study indicates an increase cases in the coming days. It is expected that the present prediction models will assist the government and medical personnel in the selected countries to be prepared for the upcoming conditions and have more readiness in healthcare systems.

Suggested Citation

  • Musa Ganaka Kubi & Son-Allah Mallaka Philemon & Olope Ganiu Ibrahim, 2020. "Forecasting the Confirmed Cases of COVID-19 in Selected West African Countries Using ARIMA Model Technique," International Journal of Research and Innovation in Applied Science, International Journal of Research and Innovation in Applied Science (IJRIAS), vol. 5(8), pages 141-144, August.
    • Handle: RePEc:bjf:journl:v:5:y:2020:i:8:p:141-144
    as

    Download full text from publisher

    File URL: https://www.rsisinternational.org/journals/ijrias/DigitalLibrary/Vol.5&Issue8/141-144.pdf
    Download Restriction: no
    File URL: https://www.rsisinternational.org/journals/ijrias/digital-library/Vol.V-Issue-VIII.php
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Cleo Anastassopoulou & Lucia Russo & Athanasios Tsakris & Constantinos Siettos, 2020. "Data-based analysis, modelling and forecasting of the COVID-19 outbreak," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-21, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. František Božek & Irena Tušer, 2021. "Measures for Ensuring Sustainability during the Current Spreading of Coronaviruses in the Czech Republic," Sustainability, MDPI, vol. 13(12), pages 1-22, June.
    2. Cooper, Ian & Mondal, Argha & Antonopoulos, Chris G., 2020. "Dynamic tracking with model-based forecasting for the spread of the COVID-19 pandemic," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    3. Cooper, Ian & Mondal, Argha & Antonopoulos, Chris G., 2020. "A SIR model assumption for the spread of COVID-19 in different communities," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    4. Fantazzini, Dean, 2020. "Short-term forecasting of the COVID-19 pandemic using Google Trends data: Evidence from 158 countries," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 59, pages 33-54.
    5. Pau Fonseca i Casas & Joan Garcia i Subirana & Víctor García i Carrasco & Xavier Pi i Palomés, 2021. "SARS-CoV-2 Spread Forecast Dynamic Model Validation through Digital Twin Approach, Catalonia Case Study," Mathematics, MDPI, vol. 9(14), pages 1-17, July.
    6. Song, Jialu & Xie, Hujin & Gao, Bingbing & Zhong, Yongmin & Gu, Chengfan & Choi, Kup-Sze, 2021. "Maximum likelihood-based extended Kalman filter for COVID-19 prediction," Chaos, Solitons & Fractals, Elsevier, vol. 146(C).
    7. Li, Shaoran & Linton, Oliver, 2021. "When will the Covid-19 pandemic peak?," Journal of Econometrics, Elsevier, vol. 220(1), pages 130-157.
    8. Mati, Sagiru, 2021. "Do as your neighbours do? Assessing the impact of lockdown and reopening on the active COVID-19 cases in Nigeria," Social Science & Medicine, Elsevier, vol. 270(C).
    9. Memon, Zaibunnisa & Qureshi, Sania & Memon, Bisharat Rasool, 2021. "Assessing the role of quarantine and isolation as control strategies for COVID-19 outbreak: A case study," Chaos, Solitons & Fractals, Elsevier, vol. 144(C).
    10. Bhardwaj, Rashmi & Bangia, Aashima, 2020. "Data driven estimation of novel COVID-19 transmission risks through hybrid soft-computing techniques," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
    11. Dorn, Florian & Lange, Berit & Braml, Martin & Gstrein, David & Nyirenda, John L.Z. & Vanella, Patrizio & Winter, Joachim & Fuest, Clemens & Krause, Gérard, 2023. "The challenge of estimating the direct and indirect effects of COVID-19 interventions – Toward an integrated economic and epidemiological approach," Economics & Human Biology, Elsevier, vol. 49(C).
    12. Huang, Chiou-Jye & Shen, Yamin & Kuo, Ping-Huan & Chen, Yung-Hsiang, 2022. "Novel spatiotemporal feature extraction parallel deep neural network for forecasting confirmed cases of coronavirus disease 2019," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).
    13. Umar Albalawi & Mohammed Mustafa, 2022. "Current Artificial Intelligence (AI) Techniques, Challenges, and Approaches in Controlling and Fighting COVID-19: A Review," IJERPH, MDPI, vol. 19(10), pages 1-24, May.
    14. Yiannakoulias, Nikolaos & Slavik, Catherine E. & Sturrock, Shelby L. & Darlington, J. Connor, 2020. "Open government data, uncertainty and coronavirus: An infodemiological case study," Social Science & Medicine, Elsevier, vol. 265(C).
    15. Roland Pongou & Guy Tchuente & Jean-Baptiste Tondji, 2020. "An Economic Model of Health-vs-Wealth Prioritization During COVID-19: Optimal Lockdown, Network Centrality, and Segregation," Working Papers 2009E Classification-E61,, University of Ottawa, Department of Economics.
    16. Masud M A & Md Hamidul Islam & Khondaker A. Mamun & Byul Nim Kim & Sangil Kim, 2020. "COVID-19 Transmission: Bangladesh Perspective," Mathematics, MDPI, vol. 8(10), pages 1-19, October.
    17. Han, Zhimin & Wang, Yi & Cao, Jinde, 2023. "Impact of contact heterogeneity on initial growth behavior of an epidemic: Complex network-based approach," Applied Mathematics and Computation, Elsevier, vol. 451(C).
    18. Marco Gribaudo & Mauro Iacono & Daniele Manini, 2021. "COVID-19 Spatial Diffusion: A Markovian Agent-Based Model," Mathematics, MDPI, vol. 9(5), pages 1-12, February.
    19. Pongou, Roland & Tchuente, Guy & Tondji, Jean-Baptiste, 2021. "Optimally Targeting Interventions in Networks during a Pandemic: Theory and Evidence from the Networks of Nursing Homes in the United States," GLO Discussion Paper Series 957, Global Labor Organization (GLO).
    20. Daniel K Sewell & Aaron Miller & for the CDC MInD-Healthcare Program, 2020. "Simulation-free estimation of an individual-based SEIR model for evaluating nonpharmaceutical interventions with an application to COVID-19 in the District of Columbia," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-18, November.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bjf:journl:v:5:y:2020:i:8:p:141-144. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Dr. Renu Malsaria (email available below). General contact details of provider: https://rsisinternational.org/journals/ijrias/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.