Significant changes in preference of illicit drug use in a population of Hanoi, Vietnam-A 6-year wastewater study (2018-2023).
Tran Thi Thanh Hue, Hieu K T Ngo, Zhe Wang, Nguyen Thi Kieu Anh, Vũ Ngân Bình, Ngo Quang Trung, Pham Quoc Chinh, Hai Thanh Luong, Qiuda Zheng, Wayne Hall, Phong K Thai
Addiction (Abingdon, England) July 23, 2025 DOI: 10.1111/add.70147 via PubMed
Summary
AI-generated from the abstractMethamphetamine use in Hanoi, Vietnam, declined significantly from a peak of 359.2 to 125.6 mg/day/1000 people between 2018 and 2023, while ketamine use rose from 149.7 to 465.9 mg/day/1000 people, becoming the most commonly used illicit drug. Cocaine and heroin remained low, and MDMA was stable. After COVID-19 restrictions eased, cocaine and codeine consumption showed statistically significant declines, whereas ketamine and heroin increased slightly but not significantly. Wastewater analysis of a canal serving over 430,000 people reveals a dynamic drug market shifting toward synthetic substances, with ketamine overtaking methamphetamine as the most used drug by end of 2022.
Study at a glance
| Characteristics | Longitudinal observational study Peer reviewed |
|---|---|
| Population | Population served by a sewage canal in Hanoi, Vietnam (>430,000 people) |
| Duration | Six-year period (2018-2023) |
| Topics | Ketamine |
| Keywords | Covid‐19 pandemic Cocaine Heroin Methamphetamine |
| Citations | 2 |
| Key finding | Illicit drug use in Hanoi shifted from methamphetamine to ketamine as the most prevalent drug between 2018 and 2023, with ketamine use increasing and methamphetamine use decreasing significantly. |
Abstract
Illicit drug use causes great harm and economical loss to society, yet there is limited understanding of its prevalence in the population in low-income countries like Vietnam where survey resources are scarce. In this study, we used wastewater analysis as a cost-effective monitoring tool to measure illicit drug use in a population of Hanoi, Vietnam, a low-income country in Southeast Asia. This is a longitudinal observational study. Wastewater samples were collected at a sewage canal serving > 430 000 people, in Hanoi, Vietnam, over a six-year period (2018-2023). Drug biomarkers for amphetamine, methamphetamine, 3,4-Methylenedioxymethamphetamine (MDMA), ketamine, morphine, codeine and benzoylecgonine were measured using liquid chromatography-tandem mass spectrometry via direct injection. The results were used to back-estimate per capita drug consumption. Together with an evaluation of general temporal trend, an interrupted time series analysis using segmented linear regression was conducted to examine the potential changes in drug use associated with the post-COVID-19 restriction. There was a statistically significant decrease in methamphetamine use, with annual averages declining from a peak value of 359.2 to 125.6 mg/day/1000 people between 2018 and 2023 (P < 0.001). In contrast, ketamine use increased statistically significantly, rising from 149.7 to 465.9 mg/day/1000 people over the study period (P < 0.001), making it the most commonly used illicit drug. Cocaine and heroin use levels remained relatively low, while MDMA use was relatively stable over time. In the post-COVID-19 restriction period, declines were observed in methamphetamine, MDMA, cocaine and codeine consumption; however, only cocaine [Coefficient (standard error, SE) = -1.9 (0.9), P = 0.034] and codeine [Coefficient (SE) = -42.4 (12.4), P = 0.001] showed statistically significant downward trends. In contrast, ketamine and heroin consumption exhibited slight but non-significant increases, suggesting limited disruption during the post-restriction period. Wastewater analysis shows that the market of illicit drugs in Vietnam is dynamic and shifting toward synthetic drugs. Methamphetamine replaced heroin as the substance with the highest estimated per capita use in Vietnam from 2018 to 2020 and was subsequently overtaken by ketamine by the end of 2022. Wastewater analysis can provide information on population use of multiple substances, including changes due to different factors in a cost-effective way, which is essential in data-poor countries.