ARIMA-based time-series analysis for forecasting of COVID-19 cases in Egypt

Ibrahim Sabry, Abdel Hamid Ismail Mourad, Amir Hussain Idrisi, Mohamed ElWakil

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


A significant purpose of this study is to examine the distribution of COVID-19 in Egypt to develop an effective forecasting model. It can be used as a decision-making mechanism to administer health interventions and mitigate the transmission of contamination by COVID-19. By this definition, we developed a model and then used it to predict possible COVID-19 cases in Egypt. The analysis suggests a growth trajectory for the events in the days to come. Statistics based on time series analysis and kinetic model analysis indicate that the total case of COVID-19 pneumonia in mainland Egypt can hit 281,478 after a week (March 1, 2020, through July 31, 2021), and the number of simple regenerations can hit 12. Analysis of ARIMA (2, 1, 2) and (2, 1, 3) sequences shows increasing growth in the number of events.

Original languageEnglish
Pages (from-to)86-96
Number of pages11
JournalInternational Journal of Simulation and Process Modelling
Issue number1-2
Publication statusPublished - 2022


  • COVID-19
  • Egypt
  • auto-regressive integrated moving average
  • coronavirus
  • forecast
  • pandemic

ASJC Scopus subject areas

  • Modelling and Simulation
  • Computer Science Applications
  • Applied Mathematics


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