Revue d'économie et de statistique appliquée
Volume 22, Numéro 2, Pages 68-78
2025-12-09
Modeling The Covid-19 Omicron Variant Spread In Algeria With A Predictive Sir Model
Authors : Kebaili Feriel Kheira . Hamimes Ahmed . Ababsa Mostefa . Lounis Mohamed . Djouadi Issam . Aouissi Hani Amir .
Abstract
On February 2020, Algeria declared the first infected case with the novel Coronavirus (SARS-CoV-2) announcing the country’s involvement in the global COVID-19 crisis. Since then, infected cases have been continuously increasing, reaching 271 496 cases and 6881 related deaths on March 9, 2023. Therefore, it is important to study the trend of the disease to understand disease trends and to allow the adoption of the best preventive strategies. In this context, our study aims to use a predictive SIR model to understand the future epidemiology of COVID-19 in Algeria using data from January 1, 2022 to February 15, 2022. Results: Our results showed that the new epidemic peaked in Algeria will be after more than 8 months, with more than 54790 infected people and more than 1095 deaths. The reproduction number (R_0) was estimated at 1.0538. Conclusions: This model may possibly be useful for the National Health Authorities not only for the COVID-19 pandemic, but also for other diseases such as Influenza or Monkeypox. Thus, we recommend in priority initial vaccination, along with booster doses for all eligible individuals in order to control the spread of the disease.
Keywords
COVID-19 ; SIR Model ; Algeria ; Omicron ; Predictive Epidemiology
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