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Non-Markovian SIR epidemic spreading model of COVID-19

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  • Basnarkov, Lasko
  • Tomovski, Igor
  • Sandev, Trifce
  • Kocarev, Ljupco

Abstract

We introduce non-Markovian SIR epidemic spreading model inspired by the characteristics of the COVID-19, by considering discrete- and continuous-time versions. The distributions of infection intensity and recovery period may take an arbitrary form. By taking corresponding choice of these functions, it is shown that the model reduces to the classical Markovian case. The epidemic threshold is analytically determined for arbitrary functions of infectivity and recovery and verified numerically. The relevance of the model is shown by modeling the first wave of the epidemic in Italy, Spain and the UK, in the spring, 2020.

Suggested Citation

  • Basnarkov, Lasko & Tomovski, Igor & Sandev, Trifce & Kocarev, Ljupco, 2022. "Non-Markovian SIR epidemic spreading model of COVID-19," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
    • Handle: RePEc:eee:chsofr:v:160:y:2022:i:c:s0960077922004969
    DOI: 10.1016/j.chaos.2022.112286
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    References listed on IDEAS

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    1. Avila-Ponce de León, Ugo & Pérez, Ángel G.C. & Avila-Vales, Eric, 2020. "An SEIARD epidemic model for COVID-19 in Mexico: Mathematical analysis and state-level forecast," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
    2. Mi Feng & Shi-Min Cai & Ming Tang & Ying-Cheng Lai, 2019. "Publisher Correction: Equivalence and its invalidation between non-Markovian and Markovian spreading dynamics on complex networks," Nature Communications, Nature, vol. 10(1), pages 1-2, December.
    3. Mi Feng & Shi-Min Cai & Ming Tang & Ying-Cheng Lai, 2019. "Equivalence and its invalidation between non-Markovian and Markovian spreading dynamics on complex networks," Nature Communications, Nature, vol. 10(1), pages 1-10, December.
    4. Basnarkov, Lasko, 2021. "SEAIR Epidemic spreading model of COVID-19," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
    5. Christel Faes & Steven Abrams & Dominique Van Beckhoven & Geert Meyfroidt & Erika Vlieghe & Niel Hens & Belgian Collaborative Group on COVID-19 Hospital Surveillance, 2020. "Time between Symptom Onset, Hospitalisation and Recovery or Death: Statistical Analysis of Belgian COVID-19 Patients," IJERPH, MDPI, vol. 17(20), pages 1-18, October.
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    Cited by:

    1. Li, Wenjie & Li, Jiachen & Nie, Yanyi & Lin, Tao & Chen, Yu & Liu, Xiaoyang & Su, Sheng & Wang, Wei, 2024. "Infectious disease spreading modeling and containing strategy in heterogeneous population," Chaos, Solitons & Fractals, Elsevier, vol. 181(C).

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