Fractional order models of infectious diseases: a review

  • Authors

    • M. Khalil Faculty of Engineering, MSA university, Giza, Egypt
    • M. Said Faculty of Engineering, MSA university, Giza, Egypt
    • H. Osman Faculty of Engineering, MSA university, Giza, Egypt
    • B. Ahmed Department of electrical and computer engineering, Faculty of engineering, University of Victoria, Canada
    • D Ahmed Department of electrical systems engineering, Faculty of engineering, Modern sciences and arts University(MSA), Egypt
    • N Younis Department of English and American studies, University of Vienna, Austria
    • B Maher Department of electrical systems engineering, Faculty of engineering, Modern sciences and arts University(MSA), Egypt
    • M Osama Department of electrical systems engineering, Faculty of engineering, Modern sciences and arts University(MSA), Egypt
    • M Ashmawy Department of electrical systems engineering, Faculty of engineering, Modern sciences and arts University(MSA), Egypt
    2019-05-05
    https://doi.org/10.14419/jes.v1i1.19436
  • Constant/Variable Fractional Order Models-Models with Complex Fractional Order -Fractional Order Models with Time Delay-Infectious Diseases Models with Memory.

  • Abstract

    The aim of this paper is to present a succinct review on fractional order models of infectious diseases. Fractional order derivative is a potential tool which gives a better understanding of the impact of memory on spread of infectious diseases. This paper reviews different infectious diseases models with constant, variable or complex fractional order. Fractional order models with time delay are presented in this paper as well. We argue that, such models are essential for decision makers in health organizations.

     

     

     

  • References

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  • How to Cite

    Khalil, M., Said, M., Osman, H., Ahmed, B., Ahmed, D., Younis, N., Maher, B., Osama, M., & Ashmawy, M. (2019). Fractional order models of infectious diseases: a review. SPC Journal of Environmental Sciences, 1(1), 1-11. https://doi.org/10.14419/jes.v1i1.19436

    Received date: 2018-09-10

    Accepted date: 2019-04-18

    Published date: 2019-05-05