Qualitative analysis and stability of a mathematical model for the spread of obesity

Obesity is the excessive accumulation of fat mass that negatively affects quality of life at multiple levels: health (physical and mental), society, economy, etc. It is a dangerous epidemic that affects developed and developing countries alike. In this article, we propose a continuous-time dynamic epidemiological model that describes the transmission of obesity within an infected population. By using the Routh-Hurwitz criteria and constructing Lyapunov functions, we obtain the local and global stability of the equilibrium both in the presence and absence of disease. We perform a sensitivity analysis to determine the contribution and impact of each model parameter on the basic reproduction number $$R_{0}$$ . Finally, the theoretical results are illustrated by numerical simulation via Matlab.

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Publication Details

Journal
Discover Public Health
Published
2026-06-16
DOI
https://doi.org/10.1186/s12982-026-02184-7
Primary Topic
Mathematical and Theoretical Epidemiology and Ecology Models
Type
article
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article

Qualitative analysis and stability of a mathematical model for the spread of obesity

Mohamed Belam, Abderrahim Labzai, Abdelbar El Mansouri
Discover Public Health
Mathematical and Theoretical Epidemiology and Ecology Models
article

Qualitative analysis and stability of a mathematical model for the spread of obesity

Mohamed Belam, Abderrahim Labzai, Abdelbar El Mansouri
article en

Abstract

Obesity is the excessive accumulation of fat mass that negatively affects quality of life at multiple levels: health (physical and mental), society, economy, etc. It is a dangerous epidemic that affects developed and developing countries alike. In this article, we propose a continuous-time dynamic epidemiological model that describes the transmission of obesity within an infected population. By using the Routh-Hurwitz criteria and constructing Lyapunov functions, we obtain the local and global stability of the equilibrium both in the presence and absence of disease. We perform a sensitivity analysis to determine the contribution and impact of each model parameter on the basic reproduction number $$R_{0}$$ . Finally, the theoretical results are illustrated by numerical simulation via Matlab.

Discover Public HealthVol. 23(1)
University of Hassan II Casablanca (MA)
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Openalex Percentile: Top 6%
Mathematical and Theoretical Epidemiology and Ecology Models
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