IDEAS home Printed from https://ideas.repec.org/a/ids/ijmdma/v20y2021i3p241-262.html
   My bibliography  Save this article

A tuned Holt-Winters white-box model for COVID-19 prediction

Author

Listed:
  • Seng Hansun
  • Vincent Charles
  • Tatiana Gherman
  • Subanar
  • Christiana Rini Indrati

Abstract

The year 2020 has become memorable the moment the novel COVID-19 spread massively around the world to become a pandemic. In this paper, we analyse and predict the future trend of the COVID-19 cases for the top ten countries with the highest number of confirmed cases to date and the top ten countries with the highest growth percentage within the last month. Since many recent works have proposed that the COVID-19 pattern follows an exponential distribution, we use a tuned approach to the Holt-Winters' additive method as a white-box model. Based on the analysis, we found that most of the countries are still presenting an increasing trend of confirmed cases in the near future. Apart from vaccine and drug development, measures such as vigilance, strategic governmental actions, public awareness, and social distancing are unarguably continuously needed to handle the spreading of COVID-19 and avoid or curb the next wave of the outbreak.

Suggested Citation

  • Seng Hansun & Vincent Charles & Tatiana Gherman & Subanar & Christiana Rini Indrati, 2021. "A tuned Holt-Winters white-box model for COVID-19 prediction," International Journal of Management and Decision Making, Inderscience Enterprises Ltd, vol. 20(3), pages 241-262.
    • Handle: RePEc:ids:ijmdma:v:20:y:2021:i:3:p:241-262
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=116018
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:ids:ijmdma:v:20:y:2021:i:3:p:241-262. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=19 .

    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.