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A New Polymorphic Comprehensive Model for COVID-19 Transition Cycle Dynamics with Extended Feed Streams to Symptomatic and Asymptomatic Infections

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  • Yas Al-Hadeethi

    (Physics Department, Faculty of Science, King Abdulaziz University, Jeddah 21589, Saudi Arabia
    Lithography in Devices Fabrication and Development Research Group, Deanship of Scientific Research, King Abdulaziz University, Jeddah 21589, Saudi Arabia)

  • Intesar F. El Ramley

    (Physics Department, Faculty of Science, King Abdulaziz University, Jeddah 21589, Saudi Arabia)

  • Hiba Mohammed

    (Fondazione Novara Sviluppo, 28100 Novara, Italy)

  • Abeer Z. Barasheed

    (Physics Department, Faculty of Science, King Abdulaziz University, Jeddah 21589, Saudi Arabia)

Abstract

This work presents a new polymorphic, reusable, and comprehensive mathematical model for COVID-19 epidemic transition cycle dynamics. This model has the following characteristics: (1) The core SEIR model includes asymptomatic and symptomatic infections; (2) the symptomatic infection is a multi-variant; (3) the recovery stage provides a partial feed to the symptomatic infection; and (4) the symptomatic and asymptomatic stages have additional feed streams from the protected stage. The proposed formalisation template is a canonical way to achieve different models for the underlying health control environment. This template approach endows the model with polymorphic and reusable capability across different scenarios. To verify the model’s reliability and validity, this work utilised two sets of initial conditions: date range and COVID-19 data for Canada and Saudi Arabia.

Suggested Citation

  • Yas Al-Hadeethi & Intesar F. El Ramley & Hiba Mohammed & Abeer Z. Barasheed, 2023. "A New Polymorphic Comprehensive Model for COVID-19 Transition Cycle Dynamics with Extended Feed Streams to Symptomatic and Asymptomatic Infections," Mathematics, MDPI, vol. 11(5), pages 1-27, February.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:5:p:1119-:d:1078249
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    References listed on IDEAS

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    1. Alberto Godio & Francesca Pace & Andrea Vergnano, 2020. "SEIR Modeling of the Italian Epidemic of SARS-CoV-2 Using Computational Swarm Intelligence," IJERPH, MDPI, vol. 17(10), pages 1-19, May.
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    Cited by:

    1. Yu, Zhenhua & Zhang, Jingmeng & Zhang, Yun & Cong, Xuya & Li, Xiaobo & Mostafa, Almetwally M., 2024. "Mathematical modeling and simulation for COVID-19 with mutant and quarantined strategy," Chaos, Solitons & Fractals, Elsevier, vol. 181(C).

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