Main Article Content

Abstract

In this paper, psychoactive drug abuse and prevention in a host community is illustrated by a mathematical model, studying the human population into four groups: those who are at risk of being initiated into psychoactive drug abuse, those who are currently abusing psychoactive drugs, those who are undergoing treatment for psychoactive drug abuse, and those who give up drug abuse through willingness or therapy. The positivity and invariant region of the model are investigated. The basic reproduction number $R_drg$ was also obtained. The numerical simulations were performed using the computer software MATLAB. The dynamics of variables and the sensitivity of parameters are displayed graphically to demonstrate that treatment and willingness to stop drug abuse are effective ways to reduce the threat of psychoactive drug abuse in a host community.

Keywords

stability numerical simulation drug abuse reproductive number

Article Details

How to Cite
Fadugba, S., Elkaf, M., & Allali, K. (2024). ABUSE OF PSYCHOACTIVE DRUGS AND ITS PREVENTION IN A HOST COMMUNITY: MATHEMATICAL ANALYSIS. Journal of the Indonesian Mathematical Society, 30(3), 385–397. https://doi.org/10.22342/jims.30.3.1458.385-397

References

  1. ovett, Richard (24 September 2005). Coffee: The demon drink? (fee required), New Scientist (2518), Archived from the original on 24 October 2007, Retrieved 2007-11-19.
  2. Merlin, M.D. Archaeological evidence for the tradition of psychoactive plant use in the old world. Economic Botany, 57(3):295–323, 2003. doi 10.1663/0013-0001(2003)057[0295:AEFTTO]2.0.CO;2.
  3. Early Holocene coca chewing in northern Peru, 84(326):939–953, 2010.
  4. Coca leaves first chewed 8,000 years ago, says research, BBC News, December 2, 2010. Archived from the original on May 23, 2014.
  5. https://en.wikipedia.org/wiki/Psychoactive drug, accessed on 01-04-2020.
  6. https://qz.com/africa/1538843/nigeria-drug-abuse-14-million-adults-use-drugs/, accessed on 01-04-2020.
  7. https://www.crisaafrica.org/product/chapter-22-drug-abuse-in-nigeria-nature-extent-policy-formulation-and-role-of-the-national-drug-law-enforcement-agency-ndlea-by-a-o-odejide/,accessed on 01-04-2020.
  8. https://www.unodc.org/wdr2019/, accessed on 01-04-2020.
  9. Frenick, K. M. Differential susceptibility in drug use epidemics, African Institute for Mathematical Sciences, Structured Masters Degree, South Africa, 2018.
  10. Kalula, A. S. and Nyabadza, F. A theoretical model for substance abuse in the presence of treatment. South African Journal of Science, 108(3-4):1–12, 2012.
  11. Mushanyu, J. and Nyabadza, F., A risk-structured model for understanding the spread of drug abuse, International Journal of Applied and Computational Mathematics, 4(2):60, 2018.
  12. Fadugba, S., Ogunlade, T. and Ogunmiloro, O., Stability analysis and optimal control of
  13. vaccination and treatment of a SIR epidemiological deterministic model with relapse. International Journal of Mathematical Modelling & Computations, 8(1 (WINTER)):39-51, 2018.
  14. White, E. and Comiskey, C., Heroin epidemics, treatment and ode modelling. Mathematical Biosciences, 208(1):312–324, 2007.
  15. Nigeria-Central Intelligence Agency, https://www.cia.gov/library/publications/the-world-factbook/geos/ni.html, accessed on 18-04-2020.
  16. QuartzAfrica, A national survey has confirmed the massive scale of Nigeria’s drug problem, 2019.
  17. Drug Use in Nigeria 2018, UNODC drug on Nigeria, www.unodc.org, accessed on 18-04-2020.