A fractional-order model for Ebola virus infection with delayed immune response on heterogeneous complex networks

V. Preethi Latha; Fathalla A. Rihan; R. Rakkiyappan; G. Velmurugan

doi:10.1016/j.cam.2017.11.032

A fractional-order model for Ebola virus infection with delayed immune response on heterogeneous complex networks

V. Preethi Latha, Fathalla A. Rihan, R. Rakkiyappan, G. Velmurugan

Department of Mathematical Sciences

Research output: Contribution to journal › Article › peer-review

48 Citations (Scopus)

Abstract

Most of the biological systems have long-range temporal memory and modeling of such systems by fractional-order differential equations has more advantages than classical models with integer-orders. In this paper, we provide a fractional-order Ebola virus epidemic model with delayed immune response on heterogeneous complex networks. The time-delay is introduced in the cytotoxic T-lymphocyte (CTLs) term. Based on fractional Laplace transform, some conditions on stability are derived for the model. The analysis shows that the fractional-order time-delay can effectively enrich the dynamics and strengthen the stability condition of fractional-order infection model. Finally, the derived theoretical results are justified by some numerical simulations.

Original language	English
Pages (from-to)	134-146
Number of pages	13
Journal	Journal of Computational and Applied Mathematics
Volume	339
DOIs	https://doi.org/10.1016/j.cam.2017.11.032
Publication status	Published - Sept 2018

Keywords

CTL response
Complex networks
Ebola virus
Stability
Time-delay

ASJC Scopus subject areas

Computational Mathematics
Applied Mathematics

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10.1016/j.cam.2017.11.032

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title = "A fractional-order model for Ebola virus infection with delayed immune response on heterogeneous complex networks",

abstract = "Most of the biological systems have long-range temporal memory and modeling of such systems by fractional-order differential equations has more advantages than classical models with integer-orders. In this paper, we provide a fractional-order Ebola virus epidemic model with delayed immune response on heterogeneous complex networks. The time-delay is introduced in the cytotoxic T-lymphocyte (CTLs) term. Based on fractional Laplace transform, some conditions on stability are derived for the model. The analysis shows that the fractional-order time-delay can effectively enrich the dynamics and strengthen the stability condition of fractional-order infection model. Finally, the derived theoretical results are justified by some numerical simulations.",

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AU - Latha, V. Preethi

AU - Rihan, Fathalla A.

AU - Rakkiyappan, R.

AU - Velmurugan, G.

PY - 2018/9

Y1 - 2018/9

N2 - Most of the biological systems have long-range temporal memory and modeling of such systems by fractional-order differential equations has more advantages than classical models with integer-orders. In this paper, we provide a fractional-order Ebola virus epidemic model with delayed immune response on heterogeneous complex networks. The time-delay is introduced in the cytotoxic T-lymphocyte (CTLs) term. Based on fractional Laplace transform, some conditions on stability are derived for the model. The analysis shows that the fractional-order time-delay can effectively enrich the dynamics and strengthen the stability condition of fractional-order infection model. Finally, the derived theoretical results are justified by some numerical simulations.

AB - Most of the biological systems have long-range temporal memory and modeling of such systems by fractional-order differential equations has more advantages than classical models with integer-orders. In this paper, we provide a fractional-order Ebola virus epidemic model with delayed immune response on heterogeneous complex networks. The time-delay is introduced in the cytotoxic T-lymphocyte (CTLs) term. Based on fractional Laplace transform, some conditions on stability are derived for the model. The analysis shows that the fractional-order time-delay can effectively enrich the dynamics and strengthen the stability condition of fractional-order infection model. Finally, the derived theoretical results are justified by some numerical simulations.

KW - CTL response

KW - Complex networks

KW - Ebola virus

KW - Stability

KW - Time-delay

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A fractional-order model for Ebola virus infection with delayed immune response on heterogeneous complex networks

Abstract

Keywords

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