Stability analysis and optimal control strategies of a fractional-order monkeypox virus infection model

El-Mesady, A; Adel, Waleed; Elsadany, A A; Elsonbaty, Amr

doi:10.1088/1402-4896/acf16f

Cited by 21 publications

(5 citation statements)

References 41 publications

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“…This feature enhances the model’s fidelity to real-world scenarios of disease spread. However, beyond the mere existence of endemic equilibrium points, the analysis of the stability of both disease-free and endemic equilibrium points constitutes a crucial aspect of infectious disease dynamics research [ 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 ]. Accordingly, our forthcoming research will primarily focus on examining the stability of equilibrium points within infectious disease models, thereby contributing significantly to the advancement of our work.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

Dynamical Analysis of an Improved Bidirectional Immunization SIR Model in Complex Network

Han,

Yan,

Pei

et al. 2024

Entropy

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In order to investigate the impact of two immunization strategies—vaccination targeting susceptible individuals to reduce their infection rate and clinical medical interventions targeting infected individuals to enhance their recovery rate—on the spread of infectious diseases in complex networks, this study proposes a bilinear SIR infectious disease model that considers bidirectional immunization. By analyzing the conditions for the existence of endemic equilibrium points, we derive the basic reproduction numbers and outbreak thresholds for both homogeneous and heterogeneous networks. The epidemic model is then reconstructed and extensively analyzed using continuous-time Markov chain (CTMC) methods. This analysis includes the investigation of transition probabilities, transition rate matrices, steady-state distributions, and the transition probability matrix based on the embedded chain. In numerical simulations, a notable concordance exists between the outcomes of CTMC and mean-field (MF) simulations, thereby substantiating the efficacy of the CTMC model. Moreover, the CTMC-based model adeptly captures the inherent stochastic fluctuation in the disease transmission, which is consistent with the mathematical properties of Markov chains. We further analyze the relationship between the system’s steady-state infection density and the immunization rate through MCS. The results suggest that the infection density decreases with an increase in the immunization rate among susceptible individuals. The current research results will enhance our understanding of infectious disease transmission patterns in real-world scenarios, providing valuable theoretical insights for the development of epidemic prevention and control strategies.

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Section: Conclusion and Discussionmentioning

confidence: 99%

Dynamical Analysis of an Improved Bidirectional Immunization SIR Model in Complex Network

Han,

Yan,

Pei

et al. 2024

Entropy

View full text Add to dashboard Cite

show abstract

“…Disease models [25] by various authors also help us gain meaningful insights into recent applications [26,27]. El-Mesady et al [28] presented a comprehensive analysis of the stability and control of the fractional-order monkeypox virus infection model, whereas Higazy et al [29]. elucidated a generalized Lotka-Volterra model using Caputo fractional derivatives and explored the impact of history depth and nonlinear interactions on model dynamics.…”

Section: Fractional Order Applications In Multi-disciplinary Fieldsmentioning

confidence: 99%

Analyzing election trends incorporating memory effect through a fractional-order mathematical modeling

Santra,

Mahapatra

2024

Phys. Scr.

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This study proposes a new mathematical model to analyze and predict the results of a political election. In general, we predict or analyze the results using statistical methods; however, to minimize the effort of the study, we propose a fractional-order modeling approach. This study proposes a model to analyze and predict general election result trends in India, focusing on the state of West Bengal. To incorporate memory into the model, we consider the Caputo fractional derivative. The model solution's positivity, boundedness, existence, and uniqueness were tested analytically. Numerical simulations were carried out to investigate the impact of the parameters and evaluate the model's performance by incorporating the implications of the previous election for realistic situations. Following this, a qualitative analysis of the performance of political parties is discussed, and a prediction of the electoral victory is obtained.

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“…Moreover, Sabbar et al 4 investigated the solution of fractal–fractional differentiation and independent quadratic Lévy jumps on the dynamics of a general epidemiological model. Other examples of deadly diseases that have been simulated using mathematical models may include Lassa fever 5 , 6 , Influenza virus 7 , 8 , Monkeypox virus 9 – 12 , Zika virus 13 , Leptospirosis virus 14 and Lassa disease 15 . All of these viruses have a life-threatening effect on human lives.…”

Section: Introductionmentioning

confidence: 99%

Designing a novel fractional order mathematical model for COVID-19 incorporating lockdown measures

Adel,

Günerhan,

Nisar

et al. 2024

Sci Rep

Self Cite

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This research focuses on the design of a novel fractional model for simulating the ongoing spread of the coronavirus (COVID-19). The model is composed of multiple categories named susceptible $$S(t)$$ S ( t ) , infected $$I(t)$$ I ( t ) , treated $$T(t)$$ T ( t ) , and recovered $$R(t)$$ R ( t ) with the susceptible category further divided into two subcategories $${S}_{1} (t)$$ S 1 ( t ) and $${S}_{2} (t)$$ S 2 ( t ) . In light of the need for restrictive measures such as mandatory masks and social distancing to control the virus, the study of the dynamics and spread of the virus is an important topic. In addition, we investigate the positivity of the solution and its boundedness to ensure positive results. Furthermore, equilibrium points for the system are determined, and a stability analysis is conducted. Additionally, this study employs the analytical technique of the Laplace Adomian decomposition method (LADM) to simulate the different compartments of the model, taking into account various scenarios. The Laplace transform is used to convert the nonlinear resulting equations into an equivalent linear form, and the Adomian polynomials are utilized to treat the nonlinear terms. Solving this set of equations yields the solution for the state variables. To further assess the dynamics of the model, numerical simulations are conducted and compared with the results from LADM. Additionally, a comparison with real data from Italy is demonstrated, which shows a perfect agreement between the obtained data using the numerical and Laplace Adomian techniques. The graphical simulation is employed to investigate the effect of fractional-order terms, and an analysis of parameters is done to observe how quickly stabilization can be achieved with or without confinement rules. It is demonstrated that if no confinement rules are applied, it will take longer for stabilization after more people have been affected; however, if strict measures and a low contact rate are implemented, stabilization can be reached sooner.

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Stability analysis and optimal control strategies of a fractional-order monkeypox virus infection model

Cited by 21 publications

References 41 publications

Dynamical Analysis of an Improved Bidirectional Immunization SIR Model in Complex Network

Dynamical Analysis of an Improved Bidirectional Immunization SIR Model in Complex Network

Analyzing election trends incorporating memory effect through a fractional-order mathematical modeling

Designing a novel fractional order mathematical model for COVID-19 incorporating lockdown measures

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