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Opium dependence and the potential impact of changes in treatment coverage level: A dynamic modeling study.

Hosein RafiemaneshAfarin Rahimi-MovagharAli Akbar HaghdoostAlireza NorooziJaleh GholamiBita VahdaniAmin AfsharMohammad SalehiKoorosh Etemad
Published in: Health promotion perspectives (2021)
Background : The most common drug, illegally used in Iran is opium. The treatment of people with substance use disorder is one of the most important strategies in reducing its burden. The aim of this study was to investigate the effect of different increasing and decreasing opium treatment coverage on the patterns of abstinence, transition to heroin dependence and mortality, over 30 years. Methods: This study was a dynamic compartmental modeling conducted in three stages: 1) presenting a conceptual model of opium dependence treatment in Iran, 2) estimating model's parameters value, and 3) modeling of opium dependence treatment and examining the outcomes for different treatment coverage scenarios. The input parameters of the model were extracted from the literature, and secondary data analysis, which were finalized in expert panels. Results: The number of opium dependence will increase from 1180550 to 1522063 [28.93% (95% CI: 28.6 to 29.2)] over 30 years. With a 25% decrease in coverage compared to the status quo, the number of deaths will increase by 459 cases [3.28% (95% CI: 0.91 to 5.7)] in the first year, and this trend will continue to be 2989 cases [15.63% (95% CI: 13.4 to 17.9)] in the 30th year. A 25% increase in treatment coverage causes a cumulative decrease of heroin dependence by 14451 cases [10.1% (95% CI: 9.5 to 10.8)] in the first decade. Conclusion: The modeling showed that the treatment coverage level reduction has a greater impact than the coverage level increase in the country and any amount of reduction in the coverage level, even to a small extent, may have a large negative impact in the long run.
Keyphrases
  • cardiovascular disease
  • combination therapy
  • data analysis
  • metabolic syndrome
  • risk factors
  • skeletal muscle
  • climate change
  • risk assessment
  • weight loss
  • cardiovascular events
  • adipose tissue
  • human health