Abstract
This study explores the dynamic characteristics of a fractional-order model for the hepatitis B virus (HBV) epidemic. We present the existence, uniqueness, and Ulam-Hyers stability of solutions for a fractional-order HBV model utilizing the Atangana-Baleanu-Caputo fractional operator with Mittag-Leffler kernels. For the fractional numerical simulations, we employ the Adams-Moulton numerical scheme. The results from the numerical solutions indicate that the parameter
1 Introduction
In recent years, fractional calculus has gained significant attention due to its effectiveness in modeling a myriad of complex problems. In particular, fractional-order models have shown promising results in the study of infectious diseases, such as hepatitis-B infection. The hepatitis B is a viral infection that affects the liver and can lead to both acute and chronic liver infections [14,31,32].
Acute hepatitis-B infection is characterized by the presence of the hepatitis-B virus (HBV) in the blood for less than 6 months. The symptoms of acute hepatitis-B infection include fatigue, abdominal pain, and jaundice. Often, people with acute hepatitis B may have no symptoms or only mild illness. Others with acute hepatitis B may have severe illness that requires hospitalization [15]. Chronic hepatitis-B infection, on the other hand, is defined as the presence of HBV in the blood for more than 6 months after first test. Chronic infection can lead to liver cirrhosis and liver cancer [27,29].
Fractional calculus is an extension of traditional calculus that deals with derivatives and integrals of noninteger order. Fractional-order models are nonlocal and allows for the inclusion of memory effects, which is important in the study of infectious diseases. Hepatitic B fractional models have been studied and discussed in the literature by several authors using Caputo, Caputo-Fabrizio (CF), and the Atangana-Baleanu Caputo (ABC) derivative [10,16]. Mittag-Leffler (M-L) kernels, which are a class of special functions, are used in fractional calculus to represent memory effects [8,22,25,27,29,34]. These kernels have been shown to provide a more accurate representation of diverse phenomena than traditional exponential functions [22].
For example, in [17], the study introduces a novel fractional derivative concept using a nonsingular kernel, aligning with Caputo’s perspective and extending multiple existing versions documented in scholarly works. In addition, they establish a version following the Riemann-Liouville approach and also thoroughly examine the essential characteristics of these newly formulated generalized fractional derivatives, in both the Caputo and Riemann-Liouville contexts.
Also, in [18], they investigated the qualitative properties, including stability, asymptotic stability, and M-L stability, of solutions to fractional differential equations utilizing the newly developed generalized Hattaf fractional derivative. This derivative integrates various prevalent nonsingular kernel fractional derivatives. The research involved constructing a suitable Lyapunov function to understand these properties. Moreover, it introduced a novel numerical method aimed at approximating solutions for such equations, extending the classic Euler numerical scheme applicable to ordinary differential equations. The culmination of the study was the application of these analytical and numerical insights to a biological nonlinear system, specifically in the context of epidemiology.
The present article introduces a new class of generalized differential and integral operators. This class includes and generalizes a large number of definitions of fractal-fractional derivatives and integral operators used to model the complex dynamics of many natural and physical phenomena found in diverse fields of science and engineering. Some properties of the newly introduced class are rigorously established. As applications of this new class, two illustrative examples are presented, one for a simple problem and the other for a nonlinear problem modeling the dynamical behavior of a chaotic system [19].
In addition, [33] offered intriguing findings regarding the virus between domestic dogs and humans, which have not been adequately explored. In this study, they examined the transmission of Ebola between dogs and humans utilizing CF derivatives. The CF fractional derivative is a mathematical approach used to describe nonlocal and memory-dependent behaviors in various systems. Also, [5], they investigated the transmission dynamics of Ebola utilizing the CF fractional operator and simulated the model across different fractional order values, and the two-step Lagrange interpolation method was applied. The existence of a solution for the Ebola model was confirmed through the application of fixed-point theory.
In this work, we present a fractional-order model with M-L kernels for acute and chronic hepatitis-B transmission dynamics. Fractional-order models including fractional-order with M-L kernels have been used to model both acute and chronic hepatitis-B infections [6,8,27,29]. In these models, the number of susceptible individuals, infected individuals, and recovered individuals are represented by fractional differential equations. The M-L kernel is used to represent the memory effect in the system, which allows the model to capture the long-term behavior of the infection [9,13,24,30].
This article is organized as follows: In Section 2, we present the necessary definitions and properties of fractional calculus. In Section 3, we formulate the model and show the existence and uniqueness of positive solutions. In Section 4, we study the existence of equilibria and their local and global stabilities. In order to illustrate our theoretical results, we present the numerical simulations of the model equations given in Section 5. To illustrate our theoretical results, we present the numerical simulations of the model equations given in Section 6. We conclude this article Section 7, which highlights our conclusions and future perspectives.
2 Mathematical preliminary on fractional calculus
In this section, we present and highlight important definitions for development of the HBV model.
2.1 M-L function
In fractional calculus, the M-L function is a direct generalization of
Definition 2.1
The one-parameter
and
where the function
2.2 Atangana-Baleanu fractional derivative
In this subsection, we present some important definitions of Atangana-Baleanu fractional derivative and integration in the Caputo (ABC) sense, which will be used in the rest of the article [1–3,7,9,20,21].
Definition 2.2
The Atangana-Baleanu fractional derivative in Caputo sense of a function
where
and
for
Definition 2.3
The Atangana-Baleanu fractional integral of a function is
3 Formulation of fractional order HBV model
In recent years, the dynamics of infectious disease modeling have attracted a lot of interest. We consider the model available in [24] in which the total population is denoted by
with the initial conditions
The model parameters are fully described in Table 1.
Description of model parameters
Parameters | Description |
---|---|
|
Birth rate |
|
HBV transmission rate |
|
Vaccination rate |
|
Natural death rate |
|
Constant recovery rate for chronically infected individuals |
|
HBV induced death rate |
|
Moving rate of acutely infected individuals to the chronic stage |
|
Recovery rate for acutely infected individuals |
These dynamics are reformulated using the
with the initial conditions
3.1 Positivity and Boundedness
Lemma 3.1
The epidemiologically feasible region of the model (4) is follows:
Proof
The dynamics of the system’s entire human population in (4) is as follows:
By applying the Laplace transform to (6), we obtain
where
4 Stability analysis of fractional-order HBV model
The disease-free equilibrium (DFE) and endemic equilibrium (EE) of the proposed model (9) are obtained from the following system:
The DFE is represented by
Also, the EE is represented by
4.1 Basic reproduction number
ℛ
0
The basic reproduction number denoted by
we calculate
As we know that, basic reproduction number
The infection will increase if there is an increase in the HBV transmission rate
4.2 Local and global stability of DFE and DEE points
We establish the local stability of system (4) in this section at HBV free point
Theorem 4.1
The HBV free equilibrium (DFE) point
Proof
The Jacobian matrix of system (4) at
Therefore, by the Routh-Hurwitz stability conditions for fractional-order systems [4], the necessary and sufficient condition is
for various fractional order models. Therefore, the disease-free equilibrium of system (4) is asymptotically stable if all of the eigenvalues
where
Theorem 4.2
Given
Proof
Consider a suitable Lyapunov function of the form
By applying the Atangana-Baleanu Caputo derivative on (15), we obtain
Exploiting equations (4) and (15) gives
Hence,
Theorem 4.3
The HBV EE point
Proof
In a similar way as in Theorem 4.1, the Jacobian matrix can be written as follows:
Therefore, by the Routh-Hurwitz stability conditions for fractional order systems [4,22], the necessary and sufficient condition for stability is
for various fractional order models. Therefore, the EE of system (4) is asymptotically stable if all the eigenvalues
The aforementioned equation gives one negative eigenvalue
where
It is clear that
Therefore, by Routh-Hurwitz criteria, all roots of (21) have negative real parts if and only if
Theorem 4.4
The DEE point
Proof
To study the global stability of
Now, we calculate the derivative with respect to time of (31) and then using model (9), we obtain
If we put
Since the right-hand side of system (26) has a negative sign, the derivative on right-hand side is less than or equal to zero, i.e.,
4.3 Existence and uniqueness
We denote a Banach space by
Now, by using equation (1), we obtain
where
Here,
Considering
we obtain
Similarly,
where
together with the initial condition
We note that
Taking into account equations (38)–(39), and considering that
we obtain
Theorem 4.5
System (4) has a unique solution for
holds.
Proof
So
with
5 Hyers-Ulam stability
Definition 5.1
[1,3,6] The ABC fractional integral system given by (35) is said to be Hyers-Ulam stable if there exist constants
there exist
such that
Proof
Following Theorem 4.5, the proposed ABC fractional model (4) has a unique solution
Taking
Similarly, we derive estimates for the rest
System (28) is Hyers-Ulam stable by taking into account (47) and (48), and hence, model (4) is Hyers-Ulam stable.□
6 Numerical simulations
In this section, we present numerical simulations to illustrate our theoretical results. The numerical method employed to solve the model problem (4) is hinged on the Adams-Moulton Rule based on the M-L kernel for the ABC fractional derivative approximation [26]. The approximate solutions of (4) with

Simulation of the dynamics of the compartments;
![Figure 2
Numerical simulation of the HBV-free equilibrium for varying fractional-order values of
χ
\chi
= [1.0, 0.95, 0.9, 0.85, 0.8, 0.75]. Source: created by authors](/document/doi/10.1515/cmb-2025-0021/asset/graphic/j_cmb-2025-0021_fig_002.jpg)
Numerical simulation of the HBV-free equilibrium for varying fractional-order values of
![Figure 3
Stability of the HBV EE for different values of
χ
\chi
= [1.0, 0.95, 0.9, 0.85, 0.8, 0.75]. Source: created by authors](/document/doi/10.1515/cmb-2025-0021/asset/graphic/j_cmb-2025-0021_fig_003.jpg)
Stability of the HBV EE for different values of
Figure 2 illustrates the outcomes of numerical simulations derived from the M-L generalized function, which is distinguished by its crossover property when transitioning between different operators. This operator possesses a statistical representation, enhancing its applicability. In the graph representing susceptible individuals, it is observed that as the fractional order value
7 Conclusion
The fractional analysis of acute and chronic HBV encompasses the evaluation of various biological markers, stages of infection, and the body’s responses to the virus. This analysis is crucial for public health, as it significantly contributes to diagnosis, disease management, prevention strategies, and the understanding of disease progression. Overall, the fractional analysis of acute and chronic HBV infections is essential for formulating targeted public health initiatives. It facilitates the efficient allocation of resources, minimizes transmission risks, prevents complications, and enhances the overall health of the population. The model captures the memory effects and long-range interactions that are present in the infection and can be used to investigate the effectiveness of various treatment strategies. The use of fractional calculus in infectious disease modeling is a promising area of research that has the potential to lead to new insights into the dynamics of infectious diseases and to the development of more effective treatment strategies. The local and global stability of both DFE and DEE points are demonstrated by utilizing various criteria and conditions. The generalized Adams-Moulton method is employed to present the numerical scheme. Large-scale numerical simulations are performed by varying the value of the parameter
Acknowledgment
We would like to thank Daniel Bentil who passed away on January 17, 2025, for his emence contribution to the writing, editing, and reviewing of the article.
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Funding information: Authors state no funding involved.
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Author contributions: All authors have accepted responsibility for the entire content of this manuscript and consented to its submission to the journal, reviewed all the results, and approved the final version of the manuscript. ENW – conceptualization, methodology, software, investigation, formal analysis, validation, writing – original draft. MVC – formal analysis, validation, writing-review & editing. JAA – validation, supervision, writing-review & editing. SEM - conceptualization, methodology, software, investigation, formal analysis, validation, writing – original draft.
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Conflict of interest: The authors have no conflict of interest to disclose.
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Data availability statement: Data sharing is not applicable to this article as no datasets were generated or analysed during the current study.
-
Use of AI tools declaration: The authors declare that they have not used Artificial Intelligence (AI) tools in the creation of this article.
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Artikel in diesem Heft
- Special Issue: Differential Equations and Control Problems - Part II
- Mathematical model on influence of past experiences on present activities of human brain
- Special Issue: Data-driven Modeling
- Simulation study on the impact of measurement errors in hierarchical Bayesian semi-parametric models
- Special Issue: Infectious Disease Modeling In the Era of Post COVID-19
- Statistical, machine learning, and deep learning models for COVID-19 forecasting in Kenya
- Research Articles
- Understanding biofilm--phage interactions in cystic fibrosis patients using mathematical frameworks
- Existence and uniqueness of solution for a fractional hepatitis B model
- Mathematical model of the impact of chemotherapy and antiangiogenic therapy on drug resistance in glioma growth
- Study of transmission pattern of COVID-19 among cardiac and noncardiac population using a nonlinear mathematical model
- Analysis of a fractional-order prey-predator model with prey refuge and predator harvest using the consumption number: Holling type III functional response
- Analysis of a fractional-order model for acute and chronic hepatitis-B transmission with Mittag-Leffler kernels
- Tumor dynamics model with treatments by oncolytic virotherapy and MEK inhibitors involving TNF-α inhibitors: Stability analysis and optimal control