Fractal–fractional age-structure study of omicron SARS-CoV-2 variant transmission dynamics

Addai, Emmanuel; Zhang, Lingling; Asamoah, Joshua Kiddy K.; Preko, Ama Kyerewaa; Arthur, Yarhands Dissou

doi:10.1016/j.padiff.2022.100455

Cited by 10 publications

(7 citation statements)

References 54 publications

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“…Some scholar investigate the impact of self-isolation, quarantine, and contact tracing on the stopping and control of the COVID-19 pandemic using data from the New York population [25] . On the other hand, fractional differential equations play a fundamental role in the distribution of the COVID-19 pandemic [26] , [27] , so there are numerous methods to solve them [28] , [29] , [30] , [31] .…”

Section: Introductionmentioning

confidence: 99%

Analysis, predicting, and controlling the COVID-19 pandemic in Iraq through SIR model

Khalaf¹,

Flayyih²

2023

Results in Control and Optimization

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Section: Introductionmentioning

confidence: 99%

Analysis, predicting, and controlling the COVID-19 pandemic in Iraq through SIR model

Khalaf¹,

Flayyih²

2023

Results in Control and Optimization

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“…In [19], the authors studied the dynamics and sensitivity analysis of pine wilt disease with asymptomatic carriers using the ABC fractal-fractional operators, and found that eliminating beetles might significantly lower the number of infections. A new fractal-fractional age-structure model for the omicron SARS-CoV-2 variant under the Caputo-Fabrizio fractional order derivative was investigated by [20]. For many applications of fractal-fractional operators, see [21] and references therein.…”

Section: Introductionmentioning

confidence: 99%

Dynamics of Age-Structure Smoking Models with Government Intervention Coverage under Fractal-Fractional Order Derivatives

et al. 2023

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The rising tide of smoking-related diseases has irreparably damaged the health of both young and old people, according to the World Health Organization. This study explores the dynamics of the age-structure smoking model under fractal-fractional (F-F) derivatives with government intervention coverage. We present a new fractal-fractional model for two-age structure smokers in the Caputo–Fabrizio framework to emphasize the potential of this operator. For the existence-uniqueness criterion of the given model, successive iterative sequences are defined with limit points that are the solutions of our proposed age-structure smoking model. We also use the functional technique to demonstrate the proposed model stability under the Ulam–Hyers condition. The two age-structure smoking models are numerically characterized using the Newton polynomial. We observe that in Groups 1 and 2, a change in the fractal-fractional orders has a direct effect on the dynamics of the smoking epidemic. Moreover, testing the inherent effectiveness of government interventions shows a considerable impact on potential, occasional, and temporary smokers when the fractal-fractional order is 0.95. It is the view that this study will contribute to the applicability of the schemes, the rich dynamics of the fractal, and the fractional perspective of future predictions.

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“…Modelling of real world problems can be solved using resulting equations and the process is called Mathematical modelling. Researchers have used the idea of mathematical modelling to solve problems in different fields such as infectious disease in Covid-19 [1,5,6], Malaria [20], Hepatitis B virus [21]. Not only in infectious disease but also in ecology relating to Lotka-Volterra model such as Holling-Tanner model [2][3][4].…”

Section: Introductionmentioning

confidence: 99%

Mathematical model and stability analysis of university-PhD-postdoc-industry migration and unemployment in south Africa

Adeniji¹,

Adeniyi²,

Shatalov³

2023

J. Math. Computer Sci.

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Unemployment poses to be a threat in many countries which has been a long age battle with the human race. Our study considers Africa (South Africa to be precise) and focuses on the academic and industry sectors, with PhD graduates and postdoctoral research fellows as key participants. The movement of PhD graduates and postdocs between academia and industry, and its impact (increase or decrease) in unemployment within the sectors was investigated. For the population of University, PhDs, Postdocs, and industry compartments, a model was developed. The primary objectives investigates the model by analyzing the stability at the University-PhD-Postdoc-Industry free equilibrium, University-PhD-Postdoc-Industry equilibrium, determine the recruitment number R UE and understand how to mitigate migrations within the University and Industry compartments. Our findings help to understand the cause and effects of migration, and aims to manage the migration of PhD graduates and Postdocs moving into the Industry while the university suffers research capacities.

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Fractal–fractional age-structure study of omicron SARS-CoV-2 variant transmission dynamics

Cited by 10 publications

References 54 publications

Analysis, predicting, and controlling the COVID-19 pandemic in Iraq through SIR model

Analysis, predicting, and controlling the COVID-19 pandemic in Iraq through SIR model

Dynamics of Age-Structure Smoking Models with Government Intervention Coverage under Fractal-Fractional Order Derivatives

Mathematical model and stability analysis of university-PhD-postdoc-industry migration and unemployment in south Africa

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