Fractional Mathematical Model Research Articles

A new co-infection model for HBV and HIV with vaccination and asymptomatic transmission using actual data from Taiwan

The co-infection of Human Immunodeficiency Virus (HIV) and Hepatitis B virus (HBV) poses a major threat to public health due to their combined negative impacts on health and increased risk of complications. A novel fractional mathematical model of the dynamics of co-infection between HBV and HIV for Taiwan is presented in this paper. Detailed analyses are conducted on the possible impact of HBV vaccination on the dynamics of HBV and HIV co-infection. The next-generation matrix technique is used to calculate the fundamental reproduction number R 0 = max{R 1, R 2}, where R 1 and R 2 are the reproduction numbers for HBV and HIV, respectively. The disease-free and endemic equilibria of the co-infection model are calculated. An extensive investigation is carried out to determine the local and global stability of the disease-free equilibrium point through Rough Hurtwiz criteria and the construction of Lyapunov function, respectively. We demonstrate that when R 1 < 1 < R 2, HBV infection is eradicated, but HIV remains prevalent. If R 2 < 1 < R 1, the opposite outcome occurs. The real data from 2000-2023 for Taiwan is used to fit the model. The fitting results show how effectively our model handles the data. In addition, numerical simulations are run for different scenarios to observe how the vaccine and fractional parameters changed the model state variables, as well as how the solutions behaved and how quickly they reached the model’s equilibrium points. According to the model’s numerical analysis, greater vaccination efforts against HBV have a positive effect on the propagation of co-infection.

A general fractional breast cancer model: Model graph energy, Caputo-Fabrizio derivative existence and uniqueness plus numerical simulation

In the study of epidemiology, mathematical modelling is crucial because it improves understanding of the underlying mechanisms that cause illnesses to spread and offers the possibility of developing preventative interventions. In this paper, we have discussed a fractional mathematical model. A set of fractional differential equations is used to build the model. We have applied a Caputo Fabrizio (CF) to describe the fractional breast cancer model. The model consists of five subpopulations that make up a population. They are disease-free (D), cardiotoxic (E), stages 1 and 2 (A), 3 (B), and 4 (C). We have used a digraph chart to present the breast cancer model. We have used some graph theory concepts to compute the energy of the breast cancer model corresponding digraph. We have demonstrated the existence, uniqueness, and positivity of the model solutions. The fixed point hypothesis demonstrates both the existence of a solution to the suggested fractional breast cancer model as well as the fact that this solution is one of a kind. Numerical simulations are a useful tool for explaining the suggested notion. We have presented a numerical method for simulating the problem. We have used an algorithm modelled after the Adams-Bashforth-Moulton method (ABMM) to solve the model. Numerical simulations of the model in various fractional orders illustrate the theoretical conclusions. We have used the Matlab application to calculate every solution. The results demonstrate the efficacy of the proposed fractional model from an epidemiological standpoint.

Fractional mathematical model for the transmission dynamics and control of Lassa fever

This paper aims to investigate various epidemiological aspects of Lassa fever viral infection using a fractional-order mathematical model so as to assess the impacts of treatment and vaccination on the spread of Lassa fever transmission dynamics. Initially, the model employs integer-order nonlinear differential equations, incorporating imperfect vaccination and treatment as control measures for the human population. Subsequently, the model is redefined using a fractional order derivative with power law to enhance understanding of disease dynamics. The paper establishes conditions ensuring the existence and uniqueness of the model’s solution in the fractional case, alongside presenting stability analysis of the endemic equilibrium using the Lyapunov function approach. Numerical simulations are performed using the fractional Adams–Bashforth–Moulton method, shedding light on the influence of model parameters and fractional order values on Lassa fever dynamics and control. Additional numerical simulations conducted utilizing surface and contour plots revealed that elevating the contact rates and diminishing the efficacy of vaccines would escalate the prevalence of Lassa fever among the human populace. It was also observed that optimizing treatment and enhancing vaccination strategies would ultimately mitigate the prevalence of Lassa fever within the human population.

Series solution of time-fractional mhd viscoelastic model through non-local kernel approach

The study of ramped condition in the context of unsteady incompressible magnetohydrodynamic Casson fluid flow over a moving vertical plate is a complex and important topic in fluid dynamics and heat transfer. This scenario combines several physical phenomena and has practical applications in various engineering and scientific fields. In this study, Casson fluid is considered unsteady under the influence of magnetic field. The fractional mathematical model is proposed by considering the effect of chemical reaction parameter of the flowing fluid. The governing equations are transformed into the dimensionless form and developed fractional models like Caputo-Fabrizio and Atangana-Baleanu Derivative. We used the Laplace transform technique to find the solution of the dimensionless governing equation analytically. The transformed solutions for velocity, energy and momentum balances developed in terms of series. MATHCAD software is being used for numerical computations and the physical attributes of material and fractional parameters are discussed. To analyze their behavior clearly, two-dimensional graphical results are plotted for velocity profile and temperature as well. It has been concluded that the fluid’s velocity are reduced for larger values of the fractional parameter and Prandtl number and is maximum for small values of both parameters. Further, the velocity behavior becomes larger for isothermal condition as compared to ramped conditions.

A fractional mathematical model approach on glioblastoma growth: tumor visibility timing and patient survival

In this paper, we introduce a mathematical model given by&#x0D; \begin{equation}&#x0D; { }^c \mathfrak{D}_t^\alpha u = \nabla \cdot \mathrm{D} \nabla u + \rho f(u) \quad \text{in } \Omega,&#x0D; \end{equation}&#x0D; where $f(u)=\frac{1}{1-u/\mathrm{K}}, \, u/\mathrm{K} \neq 1, \, \mathrm{K} &gt; 0$, to enhance established mathematical methodologies for better understanding glioblastoma dynamics at the macroscopic scale. The tumor growth model exhibits an innovative structure even within the conventional framework, including a proliferation term, $f(u)$, presented in a different form compared to existing macroscopic glioblastoma models. Moreover, it represents a further refined model by incorporating a calibration criterion based on the integration of a fractional derivative, $\alpha$, which differs from the existing models for glioblastoma. Throughout this study, we initially discuss the modeling dynamics of the tumor growth model. Given the frequent recurrence observed in glioblastoma cases, we then track tumor mass formation and provide predictions for tumor visibility timing on medical imaging to elucidate the recurrence periods. Furthermore, we investigate the correlation between tumor growth speed and survival duration to uncover the relationship between these two variables through an experimental approach. To conduct these patient-specific analyses, we employ glioblastoma patient data and present the results via numerical simulations. In conclusion, the findings on tumor visibility timing align with empirical observations, and the investigations into patient survival further corroborate the well-established inter-patient variability for glioblastoma cases.

Optimization of mass and heat flux of MHD viscous fluid flow with constant proportional Caputo derivative by using response surface methodology: Sensitivity analysis

The study of viscous dissipation in the context of unsteady incompressible magnetohydrodynamic viscous fluid flow over a moving plate is a complex and important topic in fluid dynamics and heat transfer. This scenario combines several physical phenomena and has practical applications in various engineering and scientific fields. The fractional mathematical model is proposed by considering the effect of viscous dissipation force of the flowing fluid. For this purpose, fluid is assumed to be lying over a vertical plate that is moving in its own plane. The governing equations are transformed into the dimensionless form and developed fractional model with a new operator Constant Proportional Caputo Derivative. We used the Laplace transform technique to find the solution of the dimensionless governing equation analytically. The transformed solutions for energy and momentum balances developed in terms of series. The validation of the present model comparison graphs is plotted for temperature. The sensitivity of different input parameters on output response are analyzed and displayed the sensitivity results in tabular and graphical form and found that the permeable parameter is most sensitive to skin friction coefficient, and the Eckert number is most sensitive parameter among others to Nusselt Number. The novelty of present work is to develop a correlation between input parameters and output responses by using Response Surface Methodology (RSM). As no such correlation has been developed for optimization of mass and heat flux of MHD viscous fluid flow with Constant Proportional Caputo derivative by using RSM. By using this correlation, we have performed sensitivity analysis for output responses.

Fractional Order Mathematical Modelling of HFMD Transmission via Caputo Derivative

This paper studies a nonlinear fractional mathematical model for hand, foot, and mouth Disease (HFMD), incorporating a vaccinated compartment. Our initial focus involves establishing the non-negativity and boundedness of the fractional order dynamical model. The existence and uniqueness of the system are discussed using the Caputo derivative operator formulation. Applying a fixed-point approach, we obtain results that confirm the presence of at least one solution. We analyze the stability behavior at the two equilibrium points (disease-free and endemic states) of the model and derive the basic reproduction number. Numerical simulations are conducted using the fractional Euler approach, and the simulation results confirm our analytical conclusions. This comprehensive approach enhances the understanding of HFMD dynamics and facilitates the policy making of health care centers to control the further spread of this disease.

An Efficient Numerical Scheme for Fractional Order Mathematical Model of Cytosolic Calcium Ion in Astrocytes

The major aim of this article is to obtain the numerical solution of a fractional mathematical model with a nonsingular kernel for thrombin receptor activation in calcium signals using two numerical schemes based on the collocation techniques. We present the computational solution of the considered fractional model using the Laguerre collocation method (LCM) and Jacobi collocation method (JCM). An operational matrix of the fractional order derivative in the Caputo sense is needed for the recommended approach. The computational scheme converts fractional differential equations (FDEs) into an algebraic set of equations using the collocation method. The technique is used more quickly and successfully than in other existing schemes. A comparison between LCM and JCM is also presented in the form of figures. We obtained very good results with a great agreement between both the schemes. Additionally, an error analysis of the suggested procedures is provided.

Investigating a Fractal–Fractional Mathematical Model of the Third Wave of COVID-19 with Vaccination in Saudi Arabia

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for coronavirus disease-19 (COVID-19). This virus has caused a global pandemic, marked by several mutations leading to multiple waves of infection. This paper proposes a comprehensive and integrative mathematical approach to the third wave of COVID-19 (Omicron) in the Kingdom of Saudi Arabia (KSA) for the period between 16 December 2022 and 8 February 2023. It may help to implement a better response in the next waves. For this purpose, in this article, we generate a new mathematical transmission model for coronavirus, particularly during the third wave in the KSA caused by the Omicron variant, factoring in the impact of vaccination. We developed this model using a fractal-fractional derivative approach. It categorizes the total population into six segments: susceptible, vaccinated, exposed, asymptomatic infected, symptomatic infected, and recovered individuals. The conventional least-squares method is used for estimating the model parameters. The Perov fixed point theorem is utilized to demonstrate the solution’s uniqueness and existence. Moreover, we investigate the Ulam–Hyers stability of this fractal–fractional model. Our numerical approach involves a two-step Newton polynomial approximation. We present simulation results that vary according to the fractional orders (γ) and fractal dimensions (θ), providing detailed analysis and discussion. Our graphical analysis shows that the fractal-fractional derivative model offers more biologically realistic results than traditional integer-order and other fractional models.

Fractional mathematical model of Listeria infection caused by pre-cooked package food

This article introduces a novel mathematical approach for modeling and analyzing Listeria infection dynamics by considering a system of fractional-order differential equations to understand the complexities. The homotopy perturbation general transform method (HPGTM) is applied to derive approximate solutions for the fractional-order Listeria infection model to obtain valuable insights. The obtained numerical and graphical solutions are rigorously analyzed to explore the effect of fractional orders on the dynamics of Listeria infections. Furthermore, we explore the existence, uniqueness, and stability properties of the solutions, unveiling the critical parameters influencing infection spread and persistence.

A new application of fractional glucose-insulin model and numerical solutions

Along with the developing technology, obesity and diabetes are increasing rapidly among people. The identification of diabetes diseases, modeling, predicting their behavior, conducting simulations, studying control and treatment methods using mathematical methods has become of great importance. In this paper, we have obtained numerical solutions by considering the glucose-insulin fractional model. This model consists of three compartments: the blood glucose concentration (G), the blood insulin concentration (I) and the ready-to-absorb glucose concentration (D) in the small intestine. The fractional derivative is used in the sense of Caputo. By performing mathematical analyzes for the Glucose-Insulin fractional mathematical model, numerical results were obtained with the help of the Euler method and graphs were drawn.

Analysis of a discrete time fractional-order Vallis system

Vallis system is a model describing nonlinear interactions of the atmosphere and temperature fluctuations with a strong influence in the equatorial part of the Pacific Ocean. As the model approaches the fractional order from the integer order, numerical simulations for different situations arise. To see the behavior of the simulations, several cases involving integer analysis with different non-integer values of the Vallis systems were applied. In this work, a fractional mathematical model is constructed using the Caputo derivative. The local asymptotic stability of the equilibrium points of the fractional-order model is obtained from the fundamental production number. The chaotic behavior of this system is studied using the Caputo derivative and Lyapunov stability theory. Hopf bifurcation is used to vary the oscillation of the system in steady and unsteady states. In order to perform these numerical simulations, we apply Grünwald–Letnikov tactics with Binomial coefficients to obtain the effects on the non-integer fractional degree and discrete time vallis system and plot the phase diagrams and phase portraits with the help of MATLAB and MAPLE packages.

Mathematical Investigation of the Infection Dynamics of COVID-19 Using the Fractional Differential Quadrature Method

In recent times, the global community has been faced with the unprecedented challenge of the coronavirus disease (COVID-19) pandemic, which has had a profound and enduring impact on both global health and the global economy. The utilization of mathematical modeling has become an essential instrument in the characterization and understanding of the dynamics associated with infectious illnesses. In this study, the utilization of the differential quadrature method (DQM) was employed in order to anticipate the characterization of the dynamics of COVID-19 through a fractional mathematical model. Uniform and non-uniform polynomial differential quadrature methods (PDQMs) and a discrete singular convolution method (DSCDQM) were employed in the examination of the dynamics of COVID-19 in vulnerable, exposed, deceased, asymptomatic, and recovered persons. An analysis was conducted to compare the methodologies used in this study, as well as the modified Euler method, in order to highlight the superior efficiency of the DQM approach in terms of code-execution times. The results demonstrated that the fractional order significantly influenced the outcomes. As the fractional order tended towards unity, the anticipated numbers of vulnerable, exposed, deceased, asymptomatic, and recovered individuals increased. During the initial week of the inquiry, there was a substantial rise in the number of individuals who contracted COVID-19, which was primarily attributed to the disease’s high transmission rate. As a result, there was an increase in the number of individuals who recovered, in tandem with the rise in the number of infected individuals. These results highlight the importance of the fractional order in influencing the dynamics of COVID-19. The utilization of the DQM approach, characterized by its proficient code-execution durations, provided significant insights into the dynamics of COVID-19 among diverse population cohorts and enhanced our comprehension of the evolution of the pandemic. The proposed method was efficient in dealing with ordinary differential equations (ODEs), partial differential equations (PDEs), and fractional differential equations (FDEs), in either linear or nonlinear forms. In addition, the stability of the DQM and its validity were verified during the present study. Moreover, the error analysis showed that DQM has better error percentages in many applications than other relevant techniques.

A numerical study of a new non-linear fractal fractional mathematical model of malicious codes propagation in wireless sensor networks

This paper presents a novel non-linear fractal fractional mathematical model for analyzing the spread of malicious codes in wireless sensor networks (WSNs). The model incorporates fractional calculus and non-linear interactions among nodes in a WSN. It is based on the Fractal-Fractional (FF) operator, a powerful mathematical tool that combines fractional and fractal calculus. This study explores the potential of fractional derivatives in addressing computer virus-related issues and proposes a model that elucidates the spread of viruses in a vulnerable system and potential countermeasures. The Fractal-Fractional operator is utilized to fractionalize the model, and the fixed point theory of Schauder and Banach is applied to establish the existence and uniqueness of a solution. Numerical simulations, employing MATLAB and the Adams-Bashforth method, validate the effectiveness of the proposed model in capturing the propagation dynamics of malicious codes. Ulam-Hyers stability techniques are also employed for stability analysis. The model's insights contribute to enhancing the security and robustness of WSNs against malicious code propagation, paving the way for more secure network designs. This research provides a unique perspective on analyzing the dynamics of WSNs and underscores the significance of fractional derivatives in addressing security threats in network systems.

A fractional mathematical model of heartwater transmission dynamics considering nymph and adult amblyomma ticks

Heartwater is a tick-borne illness that affects ruminants and is carried by the amblyomma ticks. The condition may sometimes be deadly. This paper studies the Caputo fractional version of the disease spread in domestic ruminants and amblyomma ticks. We obtain the positivity and boundedness condition through the Laplace transform. The stability state of the proposed model is obtained using the Ulam–Hyers and Ulam–Hyers–Rassias stability conditions. The heartwater-free equilibrium point is obtained. The fractional model is fitted to the heartwater incidence data from 2006 to 2019. The heartwater reproduction number, R0τ, from the parameter estimation is R0τ=1.9345 with a fitting fractional order, τ, of 0.6990. The residuals from the data fitting were randomly distributed, indicating that the proposed model could be used for further predictions. Furthermore, we observed the dynamic effect of varying the fractional order and noticed that changing the fractional order produces crisscrossed behaviour in infected compartments of domestic ruminants and infected adult amblyomma ticks. Finally, we showed the relative impact of varying the transmission rates and the infectivity potential of peractive, active, and recovered carrier ruminants on the overall dynamics of the disease. Thus, a reduction in the rate of transmission from nymph and adult amblyomma ticks to vaccinated ticks will increase the number of healthy domestic ruminants.

The Layla and Majnun mathematical model of fractional order: Stability analysis and numerical study

In this research paper, we investigate the numerical solutions of the nonlinear complex Layla and Majnun fractional mathematical model, which describes the emotional behavior of two lovers. The fractional model is defined using the Liouville-Caputo derivative. The model is solved using a spectral collocation matrix method and a quasilinearization method with the aid of Schröder polynomials as basis functions. The existence of solutions for the model is investigated to ensure a unique solution, and a stability analysis is performed to highlight the stability regions ensuring stable solutions. In addition, the convergence analysis and error bound for the main model are illustrated in detail, and the theoretical findings are verified by several examples. The acquired results prove the ability of the proposed technique to find accurate solutions and to capture the effect of heredity of the fractional order model. The proposed techniques are proven to be effective in providing accurate solutions and can be extended to simulate similar complex problems.

A fractional mathematical model with nonlinear partial differential equations for transmission dynamics of severe acute respiratory syndrome coronavirus 2 infection

This study presents a fractional mathematical model based on nonlinear Partial Differential Equations (PDEs) of fractional variable-order derivatives for the host populations experiencing transmission and evolution of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic. Five host population groups have been considered, the Susceptible, Exposed, Infected, Recovered, and Deceased (SEIRD). The new model, not introduced before in its current formulation, is governed by nonlinear PDEs with fractional variable-order derivatives. As a result, the proposed model is not compared with other models or real scenarios. The advantage of the proposed fractional partial derivatives of variable orders is that they can model the rate of change of subpopulation for the proposed model. As an efficient tool to obtain the solution of the proposed model, a modified analytical technique based on the homotopy and Adomian decomposition methods is introduced. Then again, the present study is general and is applicable to a host population in any country.

A fractional order age-specific smoke epidemic model

This paper presents a nonlinear fractional mathematical model for the smoke epidemic that includes two age groups. To solve the smoke epidemic, the Atangana-Baleanu-Caputo fractional derivative is used. The Banach and Krasnoselskii type fixed point theorem is used to determine existence and uniqueness. We explored model stability using the Hyers-Ulam form of stability. Using Lagrange interpolation, the behaviour of the smoke epidemic of the 2-age group model is generated. The numerical simulation shows that the model has potential for both groups, and that age-specific interventions can be used to reduce smoking rates in the general population.

A fractional mathematical model for listeriosis infection using two kernels

Listeriosis is a life-threatening illness that can be spread through contaminated food. The bacteria responsible for this disease is Listeria monocytogenes. The annual incidence rate ranges from less than one to more than ten per one million persons in different parts of the world. Despite the low incidence of listeriosis, the high mortality rate linked with the disease makes it a major public health problem. In this paper, we present an investigation of a nonlinear fractional mathematical model of listeriosis infection using two fractional kernels. To analyse the existence of the fractional model, we employ the fixed point technique, whereas stability is determined using the Hyers–Ulam analysis. The fractional model is numerically investigated using the Caputo–Fabrizio and Atangana-Baleanu-Caputo fractional kernels. The numerical results reveal that the Mittag- Leffler kernel captures fewer human infections than the exponential kernel. In other simulations, we presented the trajectory impacts of varying environmental transmission rates, the rate of infected human recovery, the rate at which uncontaminated food becomes contaminated, and the net growth rate of Listeria monocytogenes on all the affected compartments. We observed that these parameters in the model give distinct disease pathways (a unique rate of convergence), unlike the integer model. Furthermore, the exponential kernel shows more dynamics of contaminated foods than the Mittag-Leffler kernel, which indicates that an increase in contaminated food could lead to a high spread of listeriosis. Finally, we noticed the reduction in the rate of uncontaminated food becoming contaminated increases the number of recovered individuals.

Analysis of Monkeypox viral infection with human to animal transmission via a fractional and Fractal-fractional operators with power law kernel.

Monkeypox (MPX) is a global public health concern. This infectious disease affects people all over the world, not just those in West and Central Africa. Various approaches have been used to study epidemiology, the source of infection, and patterns of transmission of MPX. In this article, we analyze the dynamics of MPX using a fractional mathematical model with a power law kernel. The human-to-animal transmission is considered in the model formulation. The fractional model is further reformulated via a generalized fractal-fractional differential operator in the Caputo sense. The basic mathematical including the existence and uniqueness of both fractional and fractal-fractional problems are provided using fixed points theorems. A numerical scheme for the proposed model is obtained using an efficient iterative method. Moreover, detailed simulation results are shown for different fractional orders in the first stage. Finally, a number of graphical results of fractal-fractional MPX transmission models are presented showing the combined effect of fractal and fractional orders on model dynamics. The resulting simulations conclude that the new fractal-fractional operator added more biological insight into the dynamics of illness.