Mathematical assessment of Monkeypox with asymptomatic infection: Prediction and optimal control analysis with real data application

Li, Shuo; Samreen,; Ullah, Saif; AlQahtani, Salman A.; Tag, Sayed M.; Akgül, Ali

doi:10.1016/j.rinp.2023.106726

Cited by 8 publications

(5 citation statements)

References 31 publications

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“…The second key measure emphasized in our research is enhancing vaccination, particularly through targeted vaccination of specific at‐risk populations using ring vaccination strategies. Implementing ring vaccination strategies can effectively prevent infection, reduce the severity of the disease, and control the spread of the epidemic, which is one of the cost‐effective strategies 13,15,35,36 . Therefore, increasing vaccination coverage for monkeypox is indispensable for epidemic prevention and control, which requires the cooperation and efforts of the government, medical institutions, the public, and the media.…”

Section: Discussionmentioning

confidence: 99%

“…Currently, there are various mathematical models available for infectious diseases. Among these models, the classic susceptible–exposed–infected–recovered (SEIR) model, based on epidemiological principles, has played a significant role in studying disease transmission and developing public health policies for infectious diseases, such as COVID‐19, monkeypox, hepatitis B, and influenza 8–17 . The SEIR model and its modifications can describe the dynamic spread of infectious diseases in a population, including changes in population size at different stages (incubation, infection, and recovery), as well as key information about the speed and duration of disease transmission.…”

Section: Introductionmentioning

confidence: 99%

“…Among these models, the classic susceptible-exposed-infected-recovered (SEIR) model, based on epidemiological principles, has played a significant role in studying disease transmission and developing public health policies for infectious diseases, such as COVID-19, monkeypox, hepatitis B, and influenza. [8][9][10][11][12][13][14][15][16][17] The SEIR model and its modifications can describe the dynamic spread of infectious diseases in a population, including changes in population size at different stages (incubation, infection, and recovery), as well as key information about the speed and duration of disease transmission. Moreover, by adjusting the parameters of the model (such as vaccination coverage rates and effective contact rates), it is possible to simulate the impact of different intervention measures on the speed and scope of disease transmission, which provides valuable insights for public health decisionmaking.…”

mentioning

confidence: 99%

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Simulating the impact of optimized prevention and control measures on the transmission of monkeypox in the United States: A model‐based study

Cao,

Fang,

Chen

et al. 2024

Journal of Medical Virology

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This study aimed to develop a modified susceptible‐exposed–infected–recovered (SEIR) model to evaluate monkeypox epidemics in the United States and explore more optimized prevention and control measures. To further assess the impact of public health measures on the transmission of monkeypox, different intervention scenarios were developed based on the classic SEIR model, considering reducing contact, enhancing vaccination, diagnosis delay, and environmental transmission risk, respectively. We evaluated the impact of different measures by simulating their spread in different scenarios. During the simulation period, 8709 people were infected with monkeypox. The simulation analysis showed that: (1) the most effective measures to control monkeypox transmission during the early stage of the epidemic were reducing contact and enhancing vaccination, with cumulative infections at 51.20% and 41.90% of baseline levels, respectively; (2) shortening diagnosis time would delay the peak time of the epidemic by 96 days; and (3) the risk of environmental transmission of monkeypox virus was relatively low. This study indirectly proved the effectiveness of the prevention and control measures, such as reducing contact, enhancing vaccination, shortening diagnosis time, and low risk of environmental transmission, which also provided an important reference and containment experience for nonepidemic countries.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Simulating the impact of optimized prevention and control measures on the transmission of monkeypox in the United States: A model‐based study

Cao,

Fang,

Chen

et al. 2024

Journal of Medical Virology

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“…It may also be noted that the method we propose in this article is not limited to only first-order IVPs and can be used for finding approximate solutions to differential systems expressed in higher-order ODEs. It is also worth noting that the importance of differential equations cannot be denied as such equations appear almost in every field of science and engineering, for example see [3,4,14,15,21,24,25,29,32,37,44,48,52,54] and many of the references cited therein.…”

Section: Introductionmentioning

confidence: 99%

Optimizing A-stable hyperbolic fitting for time efficiency: exploring constant and variable stepsize approaches

Baleanu,

Qureshi,

Soomro

et al. 2024

J. Math. Computer Sci.

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This paper proposes an optimal time-efficient numerical method for solving the initial value problems (IVPs) of ordinary differential equations (ODEs) that is both A-stable and hyperbolically fitted. The method is designed to handle both constant and variable step sizes, making it highly adaptable to different types of ODEs. The methodology proposed herein leverages the optimization of an off-grid point, derived from the predominant term of the local truncation error, to enhance both accuracy and stability in the solution of stiff ODEs. This approach incorporates a variable step size control, predicated upon the error estimation furnished by the embedded pair, and aims to minimize computational expenses while concurrently safeguarding both precision and stability. Furthermore, the stability domain of the proposed method is demonstrated to be optimal, signifying it encompasses the maximal conceivable set of step sizes wherein the method retains its stability. Other important measures including zero-stability, consistency, and convergence are also discussed theoretically and confirmed experimentally. Numerical experiments consisting of the Duffing system, sinusoidal stiff system, periodic orbit system, two-body system, Lorenz system, and the system for catenary equation demonstrate that the proposed method is highly competitive in terms of accuracy and efficiency, and outperforms several existing methods for solving stiff ODEs with both constant and variable step sizes.

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“…A stochastic modeling approach to understand the cross-infection hypothesis in the MPX dynamics was presented in [18]. Recently, some novel mathematical assessment with optimal intervention to curtail the recent outbreak has been carried out in [19,20].…”

Section: Introductionmentioning

confidence: 99%

Mathematical modeling and analysis of monkeypox 2022 outbreak with the environment effects using a Cpauto fractional derivative

Li,

Samreen,

Ullah

et al. 2023

Phys. Scr.

Self Cite

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Monkeypox is a serious global challenge to human health after the COVID-19 pandemic. Although this infection is not new, still many variations have been noticed in its epidemiology. Numerous approaches have been applied to analyze the dynamics of this infection. In this study, we present a mathematical model to study various epidemiological aspects of monkeypox. Transmission from human to animal, human to human, and through the environment (surface) are considered while formulating the proposed model. The model is constructed based on a classical system of seven nonlinear differential equations. Further, the classical epidemic model is reconstructed using the standard Caputo derivative to examine the dynamical aspects of monkeypox disease in the presence of memory effects. Initially, the necessary mathematical properties of the fractional model are carried out. The model exhibits three equilibrium points: monkeypox-free equilibrium, infected animal-free endemic equilibrium, and coexistence equilibrium. Additionally, we give a thorough theoretical analysis that considers solution positivity and stability results of equilibriums of the Caputo monkeypox model. Furthermore, the parameters of the proposed model are estimated using the nonlinear least square method from the reported cases of monkeypox in the United States in a recent outbreak in 2022. Finally, the numerical solution of the model is carried out using the well-known Adams-Bashforth-Moulton scheme and simulation is performed to explore the role of memory index and various preventing measures on the disease incidence.

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Mathematical assessment of Monkeypox with asymptomatic infection: Prediction and optimal control analysis with real data application

Cited by 8 publications

References 31 publications

Simulating the impact of optimized prevention and control measures on the transmission of monkeypox in the United States: A model‐based study

Simulating the impact of optimized prevention and control measures on the transmission of monkeypox in the United States: A model‐based study

Optimizing A-stable hyperbolic fitting for time efficiency: exploring constant and variable stepsize approaches

Mathematical modeling and analysis of monkeypox 2022 outbreak with the environment effects using a Cpauto fractional derivative

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