Acta Scientific Medical Sciences (ASMS)(ISSN: 2582-0931)

Research Article Volume 8 Issue 1

Assembly of Single Substance Use Epidemiological Models

Sean SK Yap, Wei Jun Choy, Rick YH Tan and Maurice HT Ling*

School of Applied Science, Temasek Polytechnic, Singapore

*Corresponding Author: Maurice HT Ling, School of Applied Science, Temasek Polytechnic, Singapore.

Received: December 05, 2023; Published: December 21, 2023

Abstract

Substance use/abuse is a public health concern with a long history and mathematical modelling is an important tool to study its epidemiology. Recently, a study showed that adding 2 processes into a 6-compartment model with 15 processes can drastically affect the conclusions, illustrating the importance of a more complete but complicated model. A systematic review in 2022 presented 24 ordinary differential equations (ODE) models of substance use/abuse epidemiology. This study aims to assemble these 24 ODE models, for single substance use only, by stepwise analysis and assembly. Multiple substance uses and comorbidities are deemed out of scope. The assembled model consists of 11 compartments [(i) susceptible without or refusing health education (S), (ii) susceptible with or accepted health education (C), (iii) light drug users (L), (iv) heavy drug users (H), (v) users under in-patient treatment (Ti), (vi) users under out-patient treatment (To), (vii) users in remission (Re), (viii) drug sellers (D), (ix) susceptible who matured (M), (x) users who quit permanently (Q), and (xi) removed (R)] with 42 processes and 40 parameters. We present the assembled model, SubstanceUseModel, as a Python command-line script where model parameters can be changed using command-line arguments, to improve its usability. This can form the basis for further model development in the field.

 Keywords: Substance Use Epidemiology; Substance Abuse Epidemiology; Ordinary Differential Equations (ODE) Models; 5th Order Dormand-Prince; Python Command-line tool

References

  1. Lo TW., et al. “Substance Abuse and Public Health: A Multilevel Perspective and Multiple Responses”. International Journal of Environmental Research and Public Health7 (2020): 2610.
  2. Tang AK., et al. “Clinical Characteristics of Cough Mixture Abusers Referred to Three Substance Abuse Clinics in Hong Kong: aA Retrospective Study”. East Asian Archives of Psychiatry4 (2012): 154-159.
  3. Wazaify M., et al. “Doping in Gymnasiums in Amman: The Other Side of Prescription and Nonprescription Drug Abuse”. Substance Use and Misuse10 (2014): 1296-1302.
  4. Perelló M., et al. “Changes in Prescription Drug Abuse During the COVID-19 Pandemic Evidenced in the Catalan Pharmacies”. Frontiers in Public Health 11 (2023): 1116337.
  5. Cunliffe J., et al. “Nonmedical Prescription Psychiatric Drug Use and the Darknet: A Cryptomarket Analysis”. The International Journal on Drug Policy 73 (2019): 263-272.
  6. Nath A., et al. “Substance Abuse Amongst Adolescents: An Issue of Public Health Significance”. Cureus11 (2022): e31193.
  7. Mansoor K., et al. “Prevalence of Substance Abuse Among Trauma Patients in Rural West Virginia”. Cureus3 (2023): e36468.
  8. Abate SM., et al. “Prevalence and Risk Factors of Psychoactive Substance Abuse Among Students in Ethiopia: A Systematic Review and Meta-Analysis”. Annals of Medicine and Surgery 70 (2021): 102790.
  9. Alenazi I., et al. “Prevalence, Knowledge, and Attitude Toward Substance Abuse, Alcohol Intake, and Smoking Among Male High School Students in Riyadh, Saudi Arabia”. Cureus1 (2023): e33457.
  10. Olanrewaju JA., et al. “An Assessment of Drug and Substance Abuse Prevalence: A Cross-Sectional Study Among Undergraduates in Selected Southwestern Universities in Nigeria. The Journal of International Medical Research10 (2022): 3000605221130039.
  11. Chapagain K., et al. “Exploring the Prevalence and Correlates of Substance Abuse Amongst the Adolescents of Dharan, Eastern Nepal”. Journal of Nepal Health Research Council2 (2020): 263-267.
  12. Bryson EO. “The Opioid Epidemic and the Current Prevalence of Substance Use Disorder in Anesthesiologists”. Current Opinion in Anaesthesiology3 (2018): 388-392.
  13. Mackintosh DR and Stewart GT. “A Mathematical Model of a Heroin Epidemic: Implications for Control Policies”. Journal of Epidemiology and Community Health4 (1979): 299-304.
  14. Wang W., et al. “A Scoping Review of Drug Epidemic Models”. International Journal of Environmental Research and Public Health4 (2022): 2017.
  15. Tang AY and Ling MH. “Relapse Processes are Important in Modelling Drug Epidemic”. Acta Scientific Medical Sciences6 (2022): 177-182.
  16. Njagarah JBH and Nyabadza F. “Modelling the Role of Drug Barons on the Prevalence of Drug Epidemics”. Mathematical Biosciences and Engineering3 (2013): 843-860.
  17. Knolle H. “Incidence and Prevalence of Illegal Drug Use in Switzerland in the 1980s and Early 1990s: An Analytical Study”. Substance Use and Misuse10 (1997): 1349-1368.
  18. Caulkins JP., et al. “Optimal Timing of Use Reduction vs. Harm Reduction in a Drug Epidemic Model”. International Journal of Drug Policy Analysis6 (2009): 480-487.
  19. Caulkins JP., et al. “When in a Drug Epidemic Should the Policy Objective Switch from Use Reduction to Harm Reduction?” European Journal of Operational Research1 (2010): 308-318.
  20. White E and Comiskey C. “Heroin Epidemics, Treatment and ODE Modelling”. Mathematical Biosciences1 (2007): 312-324.
  21. Mulone G and Straughan B. “A Note on Heroin Epidemics”. Mathematical Biosciences2 (2009): 138-141.
  22. Nyabadza F and Hove-Musekwa SD. “From Heroin Epidemics to Methamphetamine Epidemics: Modelling Substance Abuse in a South African Province”. Mathematical Biosciences2 (2010): 132-140.
  23. Wang X., et al. “Dynamics of a Heroin Epidemic Model with Very Population”. Applied Mathematics6 (2011): 732-738.
  24. Kalula AS and Nyabadza F. “A Theoretical Model for Substance Abuse in the Presence of Treatment”. South African Journal of Science3/4 (2012): 654.
  25. Nyabadza F., et al. “Modelling the Dynamics of Crystal Meth (‘Tik’) Abuse in the Presence of Drug-Supply Chains in South Africa”. Bulletin of Mathematical Biology1 (2013): 24-48.
  26. Muroya Y., et al. “Complete Global Analysis of an SIRS Epidemic Model with Graded Cure and Incomplete Recovery Rates”. Journal of Mathematical Analysis and Applications2 (2014): 719-732.
  27. Mushanyu J., et al. “Modelling the Trends of Inpatient and Outpatient Rehabilitation for Methamphetamine in the Western Cape Province of South Africa”. BMC Research Notes1 (2015): 797.
  28. Yang J., et al. “Global Dynamics of a Heroin Epidemic Model with Age Structure and Nonlinear Incidence”. International Journal of Biomathematics3 (2016): 1650033.
  29. Mushanyu J., et al. “Modelling Drug Abuse Epidemics in the Presence of Limited Rehabilitation Capacity”. Bulletin of Mathematical Biology12 (2016): 2364-2389.
  30. Wangari IM and Stone L. “Analysis of a Heroin Epidemic Model with Saturated Treatment Function”. Journal of Applied Mathematics (2017): 1-21.
  31. Mushanyu J., et al. “On the Role of Imitation on Adolescence Methamphetamine Abuse Dynamics”. Acta Biotheoretica1 (2017): 37-61.
  32. Ma M., et al. “Dynamics of Synthetic Drugs Transmission Model with Psychological Addicts and General Incidence Rate”. Physica A: Statistical Mechanics and its Applications 491 (2018): 641-649.
  33. Li J and Ma M. “The Analysis of a Drug Transmission Model with Family Education and Public Health Education”. Infectious Disease Modelling 3 (2018): 74-84.
  34. Naowarat S and Kumat N. “The Role of Family on the Transmission Model of Methamphetamine”. Journal of Physics: Conference Series 1039 (2018): 012036.
  35. Su S., et al. “Estimates of the National Trend of Drugs Use During 2000-2030 in China: A Population-Based Mathematical Model”. Addictive Behaviors 93 (2019): 65-71.
  36. Memarbashi R and Pourhossieni M. “Global Dynamic of a Heroin Epidemic Model”. UPB Scientific Bulletin, Series A: Applied Mathematics and Physics 81 (2019): 115-126.
  37. Liu L and Liu X. “Mathematical Analysis for an Age-Structured Heroin Epidemic Model”. Acta Applicandae Mathematicae1 (2019): 193-217.
  38. Saha S., et al. “Synthetic Drugs Transmission: Stability Analysis and Optimal Control”. Letters in Biomathematics2 (2019): 1-31.
  39. Duan XC., et al. “Coinfection Dynamics of Heroin Transmission and HIV Infection in a Single Population”. Journal of Biological Dynamics1 (2020): 116-142.
  40. Dormand JR and Prince PJ. “A Family of Embedded Runge-Kutta Formulae”. Journal of Computational and Applied Mathematics1 (1980): 19-26.
  41. Ling MH. “COPADS IV: Fixed Time-Step ODE Solvers for a System of Equations Implemented as a Set of Python Functions”. Advances in Computer Science: an International Journal3 (2016): 5-11.
  42. Ling MHT. “SeqProperties: A Python Command-Line Tool for Basic Sequence Analysis”. Acta Scientific Microbiology6 (2020): 103-106.
  43. Ling MH. “Island: A Simple Forward Simulation Tool for Population Genetics”. Acta Scientific Computer Sciences2 (2019): 20-22.
  44. Ling MH. “AdvanceSyn Toolkit: An Open Source Suite for Model Development and Analysis in Biological Engineering”. MOJ Proteomics and Bioinformatics4 (2020): 83‒86.
  45. Liu TT and Ling MH. “BactClass: Simplifying the Use of Machine Learning in Biology and Medicine”. Acta Scientific Medical Sciences11 (2020): 43-47.
  46. Seemann T. “Ten Recommendations for Creating Usable Bioinformatics Command Line Software”. GigaScience1 (2013): 15.

Citation

Citation: Maurice HT Ling., et al. “Assembly of Single Substance Use Epidemiological Models”.Acta Scientific Medical Sciences 8.1 (2024): 43-50.

Copyright

Copyright: © 2024 Maurice HT Ling., et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.




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