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

Subanar, Seng Hansun, Vincent Charles, Tatiana Gherman, Christiana Rini Indrati

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

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.

Original languageEnglish
Pages (from-to)241-262
Number of pages22
JournalInternational Journal of Management and Decision Making
Volume20
Issue number3
DOIs
StatePublished - 2021
Externally publishedYes

Keywords

  • COVID-19
  • Future wave
  • Holt-winters additive method
  • Prediction
  • White-box model

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