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Journal of Applied Nonlinear Dynamics
Miguel A. F. Sanjuan (editor), Albert C.J. Luo (editor)
Miguel A. F. Sanjuan (editor)

Department of Physics, Universidad Rey Juan Carlos, 28933 Mostoles, Madrid, Spain

Email: miguel.sanjuan@urjc.es

Albert C.J. Luo (editor)

Department of Mechanical and Industrial Engineering, Southern Illinois University Ed-wardsville, IL 62026-1805, USA

Fax: +1 618 650 2555 Email: aluo@siue.edu


A Mathematical Model for Analysing Smoking Dynamics and its Recovery Rates

Journal of Applied Nonlinear Dynamics 15(2) (2026) 291--302 | DOI:10.5890/JAND.2026.06.002

Swapnil Talele$^1$, Ravi Gor$^2$

$^1$ Department of Applied Mathematical Science, Actuarial Science & Analytics, Gujarat University, India

$^2$ Department of Mathematics, Gujarat University, India

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Abstract

Smoking is a leading cause of death due to its detrimental effects on various organs, leading to strokes, heart diseases, and other respiratory issues. This paper presents a mathematical model to examine the dynamics of smoking and the recovery rate within a community. The model employs a compartmental approach, consisting of five non-linear differential equations, to analyze these dynamics. Both the local and global stability of the model are investigated. Additionally, the next-generation matrix technique is utilized to perform an in-depth analysis based on the reproduction number $R_0$, which is calculated using Python. Several numerical simulations are conducted to illustrate the findings, highlighting the impact of various parameters on smoking dynamics and the effectiveness of intervention strategies.

References

  1. [1] Banerjee, S. (2021), Mathematical Modelling: Models, Analysis and Applications, Chapman and Hall/CRC.
  2. [2] WHO report on the global tobacco epidemic (2023), https://www.who.int/teams/health-promotion/tobacco-control/global-tobacco-report.
  3. [3] Sharomi, O. and Gumel, A.B. (2008), Curtailing smoking dynamics: a mathematical modelling approach, Applied Mathematics and Computation, 195(2), 475-499.
  4. [4] Zaman, G. (2011), Qualitative behavior of giving up smoking models, Bulletin of the Malaysian Mathematical Sciences Society, 34(2), 403-415.
  5. [5] Bhunu, C.P. and Mushayabasa, S. (2012), A theoretical analysis of smoking and alcoholism, Journal of Mathematical Modelling and Algorithms, 11, 387-408.
  6. [6] Alkhudhari, Z., Al-Sheikh, S., and Al-Tuwairqi, S. (2014), The effect of occasional smokers on the dynamics of a smoking model, International Mathematical Forum, 9(25), 1207-1222.
  7. [7] Yadav, A., Srivastava, P.K., and Kumar, A. (2015), Mathematical model for smoking: Effect of determination and education, International Journal of Biomathematics, 8(01), 1550001.
  8. [8] Fekede, B. and Mebrate, B. (2020), Sensitivity and mathematical model analysis on secondhand smoking tobacco, Journal of the Egyptian Mathematical Society, 28(1), 1-16.
  9. [9] Sofia, I.R. and Ghosh, M. (2022), Mathematical modeling of smoking habits in society, Stochastic Analysis and Applications, 1, 1-20.