Simulation of the evolution of the Covid-19 pandemic in the United Arab Emirates using the sir epidemical model

A. Haj Ismail, E. A. Dawi, T. Jwaid, Saleh T. Mahmoud, A. AbdelKader

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

The Coronavirus Disease 2019 (COVID-19) is a pulmonary disease produced by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and has become a global pandemic March 2019. The aim of this research is to study a modelling approach on the spread of the COVID-19 pandemic utilizing analysis that is based on the well-known susceptible-infectious-removed (SIR) model. Since the declaration of the epidemic in Wuhan-city in China and other places around the world, several studies have addressed the development and evolution of the disease in different countries and have shown good stability of the use of such model. The United Arab Emirates is among the countries affected by the spread of the virus. Using collected data from 1 March 2020 to 31 August 2020 collected by John Hopkins University and the Federal Competitiveness and Statistics Authority (FCSA) in the UAE, we apply the SIR model to simulate the evolution of the virus in the United Arab Emirates. Our model predicts a peak in the daily infected cases on 19 May 2020, and the cumulative number of infected individuals to reach 100,000 cases by the end of October 2020.

Original languageEnglish
Pages (from-to)128-134
Number of pages7
JournalArab Journal of Basic and Applied Sciences
Volume28
Issue number1
DOIs
Publication statusPublished - 2021

Keywords

  • COVID-19
  • SIR model
  • data analysis
  • pandemic evolution

ASJC Scopus subject areas

  • Chemistry(all)
  • Mathematics(all)
  • Materials Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Environmental Science(all)
  • Agricultural and Biological Sciences(all)
  • Energy(all)

Fingerprint

Dive into the research topics of 'Simulation of the evolution of the Covid-19 pandemic in the United Arab Emirates using the sir epidemical model'. Together they form a unique fingerprint.

Cite this