Modelling the amount of inputs needed for methamphetamine manufacture in Afghanistan.

BACKGROUND AND AIMS: The use and manufacture of methamphetamine has increased in Afghanistan in recent years. Recent research and reports have pointed to the ephedra plant, which grows wildly, as a key source of ephedrine used in the manufacture of methamphetamine. This paper aimed to estimate the relative efficiencies and scale of inputs required to manufacture methamphetamine in Afghanistan. METHODS: Monte Carlo simulations model of the amount of ephedra or cold medications needed to render a pure kilogram of methamphetamine in Afghanistan, accounting for uncertainty in ranges of key parameters informed from the literature and elsewhere. Final estimates were extrapolated to recent seizure totals. RESULTS: For dried ephedra, the median estimate is 196.8 kg (25th-75th percentiles 119.3-346.6 kg) needed to produce 1 kg of methamphetamine compared with 27.9 kg (25th-75th percentiles 21.9-36.8 kg) for cold medications. Nearly 2.7 t of methamphetamine were seized in Afghanistan in 2021. Assuming a purity range of 50%-90%, some 266-478 t of dried ephedra or 38-68 t of cold medication would need to have been processed. CONCLUSION: Simulated estimates show that considerable amounts of either ephedra or cold medication are needed to produce 1 kg of methamphetamine in Afghanistan. This raises questions about the plausibility of ephedra as the dominant source of Afghanistan's methamphetamine.

Optimal targeting of Hepatitis C virus treatment among injecting drug users to those not enrolled in methadone maintenance programs.

BACKGROUND: This work used mathematical modelling to explore effective policy for Hepatitis C virus (HCV) treatment in Australia in the context of methadone maintenance treatment (MMT). METHOD: We consider two models to depict HCV in the population of injecting drug users (IDU) within Australia. The first model considers the IDU population as a whole. The second model includes separate components for those that are or are not enrolled in MMT. The impact of different levels of HCV treatment and its allocation dependent on MMT status were then determined in terms of the steady state levels of each of these models. RESULTS: Although increasing levels of HCV treatment decrease chronic infection prevalence, initially numbers of acutely infected can rise. This is caused by the high rate of reinfection. We find that no matter the extent of HCV treatment, HCV prevalence cannot be eliminated without limiting risk behaviour. Assuming equal adherence to HCV therapy between MMT and non-MMT, over 84% of HCV treatment should be allocated to those not in MMT. Only if adherence to HCV therapy in non-MMT patients falls below 44% of that in MMT then treatment should be preferentially directed to those in MMT. CONCLUSIONS: Contrary to generally held beliefs regarding HCV treatment the majority of therapy should be allocated to those that are still actively injecting. This is due to rates of reinfection and to the high turnover of individuals in MMT. Higher adherence to HCV therapy in MMT would need to be achieved before this changed.