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A study of fractional optimal control of overweight and obesity in a community and its impact on the diagnosis of diabetes

Year 2024, Volume: 4 Issue: 4, 514 - 543, 30.12.2024
https://doi.org/10.53391/mmnsa.1555670

Abstract

Obesity and diabetes are diseases that are increasing every year in the world and their control is an important problem faced by health systems. In this work, we present an optimal control problem based on a model for overweight and obesity and its impact on the diagnosis of diabetes using fractional order derivatives in the Caputo sense. The controls are defined with the objective of controlling the evolution of an individual with normal weight to overweight and that overweight leads to chronic obesity. We show the existence of optimal control using Pontryagin’s maximum principle. We perform a study of the global sensitivity for the model using Sobol's index of first, second and total order using the polynomial chaos expansion (PCE) with two techniques, ordinary least squares (OLS) and least angle regression (LAR) to find the polynomial coefficients, and two sampling methods, Monte Carlo and Sobol. With the obtained results, we find that among the parameters with the greatest influence are those we used in the definition of the control system. We have that the best results are achieved when we activate the three controls. However, when we only activate two controls, it shows better results in preventing a person with normal weight from becoming overweight by controlling weight gain due to social pressure and the evolution from overweight to obesity. All strategies significantly reduce the number of cases diagnosed with diabetes over time.

References

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Year 2024, Volume: 4 Issue: 4, 514 - 543, 30.12.2024
https://doi.org/10.53391/mmnsa.1555670

Abstract

References

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  • [2] Chong, B., Jayabaskaran, J., Kong, G., Chan, Y.H., Chin, Y.H., Goh, R. et al. Trends and predictions of malnutrition and obesity in 204 countries and territories: an analysis of the Global Burden of Disease Study 2019. eClinicalMedicine Part of The Lancet, 57, 101850, (2023).
  • [3] Hu, K. and Staiano, A.E. Trends in obesity prevalence among children and adolescents aged 2 to 19 years in the US from 2011 to 2020. JAMA Pediatrics, 176(10), 1037-1039, (2022).
  • [4] Ong, K.L., Stafford, L.K., McLaughlin, S.A., Boyko, E.J., Vollset, S.E., Smith, A.E. et al. Global, regional, and national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: a systematic analysis for the Global Burden of Disease Study 2021. The Lancet, 402(10397), 203-234.
  • [5] Nuttall, F.Q. Body mass index: obesity, BMI, and health: a critical review. Nutrition Today, 50(3), 117-128, (2015).
  • [6] Bentout, S., Djilali, S. and Atangana, A. Bifurcation analysis of an age-structured prey–predator model with infection developed in prey. Mathematical Methods in the Applied Sciences, 45(3), 1189-1208, (2022).
  • [7] Bentout, S. and Djilali, S. Asymptotic profiles of a nonlocal dispersal SIR epidemic model with treat-age in a heterogeneous environment. Mathematics and Computers in Simulation, 203, 926-956, (2023).
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  • [18] Paudel, L.P. Mathematical modeling on the obesity dynamics in the southeastern region and the effect of intervention. Universal Journal of Mathematics and Applications, 7(3), 41-52, (2019).
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  • [22] Moya, E.M.D., Pietrus, A., Bernard, S. and Nuiro, S.P. A mathematical model with fractional order for obesity with positive and negative interactions and its impact on the diagnosis of diabetes. Journal of Mathematical Sciences and Modelling, 6(3), 133-149, (2023).
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  • [29] Monteiro, N.Z. and Mazorche, S.R. Fractional derivatives applied to epidemiology. Trends in Computational and Applied Mathematics, 22(2), 157-177, (2021).
  • [30] Vellappandi, M., Kumar, P. and Govindaraj, V. Role of fractional derivatives in the mathematical modeling of the transmission of Chlamydia in the United States from 1989 to 2019. Nonlinear Dynamics, 111, 4915–4929, (2023).
  • [31] Inc, M., Acay, B., Berhe, H.W., Yusuf, A., Khan, A. and Yao, S.W. Analysis of novel fractional COVID-19 model with real-life data application. Results in Physics, 23, 103968, (2021).
  • [32] Wang, H., Jahanshahi, H., Wang, M.K., Bekiros, S., Liu, J. and Aly, A.A. A Caputo–Fabrizio fractional-order model of HIV/AIDS with a treatment compartment: Sensitivity analysis and optimal control strategies. Entropy, 23(5), 610, (2021).
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  • [34] Baba, B.A. and Bilgehan, B. Optimal control of a fractional order model for the COVID–19 pandemic. Chaos, Solitons & Fractals, 144, 110678, (2021).
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  • [36] Pinto, C.M.A. and Carvalho, A.R.M. Diabetes mellitus and TB co-existence: Clinical implications from a fractional order modelling. Applied Mathematical Modelling, 68, 219-243, (2019).
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There are 75 citations in total.

Details

Primary Language English
Subjects Biological Mathematics, Calculus of Variations, Mathematical Aspects of Systems Theory and Control Theory
Journal Section Research Articles
Authors

Erick Manuel Delgado Moya 0000-0001-5937-5374

Ranses Alfonso Rodriguez 0000-0001-8821-6401

Alain Pietrus 0009-0005-8064-4950

Séverine Bernard 0000-0001-8493-9821

Publication Date December 30, 2024
Submission Date September 25, 2024
Acceptance Date December 23, 2024
Published in Issue Year 2024 Volume: 4 Issue: 4

Cite

APA Delgado Moya, E. M., Alfonso Rodriguez, R., Pietrus, A., Bernard, S. (2024). A study of fractional optimal control of overweight and obesity in a community and its impact on the diagnosis of diabetes. Mathematical Modelling and Numerical Simulation With Applications, 4(4), 514-543. https://doi.org/10.53391/mmnsa.1555670


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