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  • Open Access

    ARTICLE

    A Numerical Efficient Technique for the Solution of Susceptible Infected Recovered Epidemic Model

    Muhammad Shoaib Arif1,*, Ali Raza1,2, Kamaleldin Abodayeh3, Muhammad Rafiq4, Mairaj Bibi5, Amna Nazeer5

    CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.2, pp. 477-491, 2020, DOI:10.32604/cmes.2020.011121 - 20 July 2020

    Abstract The essential features of the nonlinear stochastic models are positivity, dynamical consistency and boundedness. These features have a significant role in different fields of computational biology and many more. The aim of our paper, to achieve the comparison analysis of the stochastic susceptible, infected recovered epidemic model. The stochastic modelling is a realistic way to study the dynamics of compartmental modelling as compared to deterministic modelling. The effect of reproduction number has also observed in the stochastic susceptible, infected recovered epidemic model. For comparison analysis, we developed some explicit stochastic techniques, but they are the More >

  • Open Access

    ARTICLE

    Structure-Preserving Dynamics of Stochastic Epidemic Model with the Saturated Incidence Rate

    Wasfi Shatanawi1, 2, 3, Muhammad Shoaib Arif4, *, Ali Raza4, Muhammad Rafiq5, Mairaj Bibi6, Javeria Nawaz Abbasi6

    CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 797-811, 2020, DOI:10.32604/cmc.2020.010759 - 10 June 2020

    Abstract The structure-preserving features of the nonlinear stochastic models are positivity, dynamical consistency and boundedness. These features have a significant role in different fields of computational biology and many more. Unfortunately, the existing stochastic approaches in literature do not restore aforesaid structure-preserving features, particularly for the stochastic models. Therefore, these gaps should be occupied up in literature, by constructing the structure-preserving features preserving numerical approach. This writing aims to describe the structure-preserving dynamics of the stochastic model. We have analysed the effect of reproduction number in stochastic modelling the same as described in the literature for More >

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