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Research Article | Open Access

A dynamical approach for a fractional-order SEIL epidemic model embedding time delay

Suganya Dhandapani1Bhuvaneswari Venkatasubramaniam2( )Ibraheem M. Alsulami3( )Amer Alsulami4Hariharan Soundararajan5Shangerganesh Lingeshwaran6
Department of Mathematics, PSG College of Arts & Science, Coimbatore 641 014, India
Department of Mathematics with Computer Applications, PSG College of Arts & Science, Coimbatore 641 014, India
Mathematics Department, Faculty of Science, Umm Al-Qura University, Makkah 21955, Saudi Arabia
Department of Mathematics, Turabah University College, Taif University, Taif 21944, Saudi Arabia
Department of Mathematics, School of Engineering Dayananda Sagar University, Bangalore 562 112, India
Department of Applied Sciences, National Institute of Technology Goa, Cuncolim, Goa 403 703, India
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Abstract

In this paper, we suggest a fractional-order susceptible, exposed, infectious, and latent (SEIL) epidemic model with discrete time delays that provide for biological factors and memory effects in the spread of disease. Caputo derivatives and fixed-point theory are implemented, and we identify the existence and uniqueness of solutions, as well as the basic reproduction number for both endemic and disease-free equilibria. Local stability is analyzed through characteristic equations and linearization, while numerical simulations confirm theoretical results and illustrate the influence of fractional order, delays, and parameters. The findings show that fractional-delay models provide a more flexible and effective framework for studying disease dynamics and control.

CLC number: 34A08, 34A12, 34D20, 49J15

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AIMS Mathematics
Pages 15725-15744

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Cite this article:
Dhandapani S, Venkatasubramaniam B, Alsulami IM, et al. A dynamical approach for a fractional-order SEIL epidemic model embedding time delay. AIMS Mathematics, 2026, 11(6): 15725-15744. https://doi.org/10.3934/math.2026647

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Received: 16 February 2026
Revised: 10 May 2026
Accepted: 25 May 2026
Published: 15 June 2026
©2026 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)