A Wavelet Framework for Fractional Epidemic Models with Delay

Authors

DOI:

https://doi.org/10.64891/jome.15

Keywords:

Euler wavelet expansion, Fractional epidemic model, Fractional-order derivative, Mathematical epidemiology, Nonlinear incidence rate, Stability analysis, Time-delay systems

Abstract

A fractional-order epidemic model with a nonlinear incidence rate and a biologically motivated time delay is proposed using a new fractional derivative operator. The nonlinear incidence accounts for behavioral and psychological effects in disease transmission, while the delay represents latency and incubation periods. An efficient numerical scheme based on Euler wavelet expansion is developed to obtain approximate solutions of the resulting system. Fundamental analytical properties, including existence, uniqueness, and positivity of solutions, are established, and the stability of equilibrium points together with the basic reproduction number is analyzed. Numerical simulations demonstrate the influence of the fractional order, time delay, and nonlinear incidence on the qualitative dynamics of the epidemic model. The proposed framework generalizes several existing models and provides a unified approach for incorporating memory and delay effects in epidemic dynamics.

References

R. M. Anderson and R. M. May, Infectious Diseases of Humans: Dynamics and Control, Oxford University

Press, (1991).

F. Brauer, C. Castillo-Chavez, and Z. Feng, Mathematical models in epidemiology, New York: Springer.

(2019).

F. Brauer, Mathematical epidemiology: Past, present, and future, Infectious Disease Modelling, 2(2),

(2017), 113-127.

K. Diethelm, The Analysis of Fractional Differential Equations: An Application-oriented Exposition

Using Differential Operators of Caputo Type, Lecture Notes in Mathematics, 2004, (2010). https:

//doi.org/10.1007/978-3-642-14574-2

A. Atangana, Application of fractional calculus to epidemiology, Fractional dynamics, 2015, (2015)

-190.

M. Khan, N. Khan, I. Ullah, K. Shah, T. Abdeljawad, and B. Abdalla, A novel fractal fractional mathematical

model for HIV/AIDS transmission: Stability and sensitivity with numerical analysis, Scientific

Reports, 15(1), (2025), 9291. https://doi.org/10.1038/s41598-025-93436-0

M. M. A. Hasan, A. M. Alghanmi, S. M. AL-Mekhlafi, H. Al Ali, and Z. Mukandavire, A Novel Crossover

Dynamics of Variable-Order Fractal-Fractional Stochastic Diabetes Model: Numerical Simulations, Journal

of Mathematics, 2025(1), (2025), 2986543. https://doi.org/10.1155/jom/2986543

M. M. A. Hasan, S. M. AL-Mekhlafi, F. A. Rihan, and H. A. Al Ali, Modeling Hybrid Crossover Dynamics

of Immuno-Chemotherapy and Gene Therapy: A Numerical Approach, Mathematical Methods in the

Applied Sciences, 48(8), (2025), 8925-8938.

M. M. A. Hasan, Variable order fractional diabetes models: numerical treatment, International Journal

of Modelling and Simulation, (2024), 1-15.

N. H. Sweilam, M. M. A. Hasan, S. M. AL-Mekhlafi, and S. A. Alkhatib, Time fractional of nonlinear

heat-wave propagation in a rigid thermal conductor: Numerical treatment, Alexandria Engineering

Journal, 61(12), (2022), 10153-10159.

L. Zhang, M. U. Rahman, S. Ahmad, M. B. Riaz, and F. Jarad, Dynamics of fractional order delay

model of coronavirus disease, AIMS Mathematics, 7(3), 4211-4232. https://doi.org/10.3934/

math.2022234

W. M. Liu, H. W. Hethcote, and S. A. Levin, Dynamical behavior of epidemiological models with nonlinear

incidence rates. Journal of Mathematical Biology, 25(4), (1987), 359-380. https://doi.org/10.

/BF00277162

M. Y. Li, H. L. Smith, and L. Wang, Global dynamics of an SEIR epidemic model with vertical transmission,

SIAM Journal on Applied Mathematics, 62(1), (2001) 58-69. https://doi.org/10.1137/

S0036139999359860

A. Kashkynbayev and F. A. Rihan, Dynamics of fractional-order epidemic models with general nonlinear

incidence rate and time-delay, Mathematics, 9(15), 1829. https://doi.org/10.3390/math9151829

K. L. Cooke and P. Van Den Driessche, Analysis of an SEIRS epidemic model with two delays, Journal of

Mathematical Biology, 35(2), (1996) 240-260.

E. Beretta and Y. Takeuchi, Global stability of an SIR epidemic model with time delays, Journal of

Mathematical Biology, 33(3), (1995), 250-260. https://doi.org/10.1007/BF00169563

H. Miao, Z. Teng, and Z. Li, Global stability of delayed viral infection models with nonlinear antibody

and CTL immune responses and general incidence rate, Computational and Mathematical Methods in

Medicine, 2016(1), (2016), 3903726. https://doi.org/10.1155/2016/3903726

W. Ma, M. Song, and Y. Takeuchi, Global stability of an SIR epidemic model with time delay, Applied

Mathematics Letters, 17(10), (2004), 1141-1145. https://doi.org/10.1016/j.aml.2003.11.005

S. Kumar, R. Kumar, S. Momani, and S. Hadid, A study on fractional COVID-19 disease model by

using Hermite wavelets, Mathematical Methods in the Applied Sciences, 46(7), (2023) 7671-7687.

https://doi.org/10.1002/mma.7065

D. K. Chiranahalli Vijaya, P. Doddabhadrappla Gowda, and B. Hadimani, A numerical study on the

dynamics of SIR epidemic model through Genocchi wavelet collocation method, Scientific Reports, 15(1),

(2025) 9780.

M. Mohammad, M. Sweidan and A. Trounev, Piecewise fractional derivatives and wavelets in epidemic

modeling, Alexandria Engineering Journal, 101, (2024) 245-253. https://doi.org/10.1016/

j.aej.2024.05.053

M. Mohammad, A. Trounev, and S. Kumar, High-precision Euler wavelet methods for fractional

Navier–Stokes equations and two-dimensional fluid dynamics, Physics of Fluids, 36(12), (2024).

M. Mohammad, Cognitive AI and implicit pseudo-spline wavelets for enhanced seismic prediction, International

Journal of Cognitive Computing in Engineering, 6, (2025) 401-411.

M. Mohammad and A. Trounev, Fractal-induced flow dynamics: Viscous flow around Mandelbrot and

Julia sets, Chaos, Solitons and Fractals, 199, (2025), 116619.

M. Mohammad, I. A. Baba, E. Hincal and F. A. Rihan, A novel fractional order model for analyzing

counterterrorism operations and mitigating extremism, Decision Analytics Journal, (2025), 100589.

M. Mohammad and A. Trounev, Computational precision in time fractional PDEs: Euler wavelets

and novel numerical techniques, Partial Differential Equations in Applied Mathematics, 12, (2024),

M. Mohammad, A Tight Wavelet Frames-Based Method for Numerically Solving Fractional Riccati Differential

Equations, Mathematical Methods in the Applied Sciences, (2025).

I. Podlubny, Fractional Differential Equations, Academic Press, 1998.

M. Caputo and M. Fabrizio, A new definition of fractional derivative without singular kernel, Progress

in fractional differentiation and applications, 1(2), (2015), 73-85.

A. Atangana and D. Baleanu, New fractional derivatives with nonlocal and non-singular kernel: theory

and application to heat transfer model, Thermal Science, 20(2), (2016), 763-769.

M. Mohammad and M. Saadaoui, A new fractional derivative extending classical concepts: Theory and

applications, Partial Differential Equations in Applied Mathematics, 11, (2024), 100889.

F. A. Rihan and M. N. Anwar, Qualitative analysis of delayed SIR epidemic model with a saturated

incidence rate, International Journal of Differential Equations, 2012(1), (2012) 408637.

S. Erman, A. Demir, and E. Ozbilge, Solving inverse non-linear fractional differential equations by

generalized Chelyshkov wavelets, Alexandira Engineering Journal, 66, (2023), 947-956. https://

doi.org/10.1016/j.aej.2022.10.063

S. Behera and S. Sasha Ray, An efficient numerical method based on Euler wavelets for solving fractional

order pantograph Volterra delay-integro-differential equations, Journal of Compuatational and Applied

Mathematics, 406, (2022), 113825. https://doi.org/10.1016/j.cam.2021.113825

M. Mohammad and A. Trounev, A new technique for solving neutral delay differential equations based on

Euler wavelets. Complexity, 2022(1), (2022), 1753992. https://doi.org/10.1155/2022/1753992

Downloads

Published

2025-12-31

How to Cite

Mohammad, M., Trounev, A., & Rihan, F. (2025). A Wavelet Framework for Fractional Epidemic Models with Delay. Journal of Mathematical Epidemiology, 1(2), 167–180. https://doi.org/10.64891/jome.15

Similar Articles

You may also start an advanced similarity search for this article.