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Using Monte Carlo simulation to assess uncertainty and variability of methamphetamine use and prevalence from wastewater analysis
- Source :
- International Journal of Drug Policy. 36:1-7
- Publication Year :
- 2016
- Publisher :
- Elsevier BV, 2016.
-
Abstract
- Background In recent years, methamphetamine (METH) has increased dramatically in China. However, little is known regarding the prevalence of METH use among the general population in China. Methods We provided a method to estimate the consumption and prevalence of METH in a city based on wastewater analysis. Monte Carlo simulations were employed to assess the uncertainty and variability of the consumption and prevalence rate in Beijing. Results METH consumption in Beijing based on Monte Carlo simulation varied between 1.3 and 5.2kg per day with a median of 2.6kg per day. In 2013, the 12-month prevalence of METH use was 0.58% (95% confidential interval 0.08–3.16) among the general population aged 15–64 years. A population-weight consumption map displayed the geographical differences in Beijing. Conclusions The proposed method dramatically improved the accuracy and reliability and can be used as a useful complementary tool to official methodologies for drug use monitoring. This report describes the first comprehensive study concerning the prevalence of METH among the general population in mainland China.
- Subjects :
- Adult
Male
Mainland China
China
Time Factors
Adolescent
Amphetamine-Related Disorders
Monte Carlo method
Population
Prevalence
Medicine (miscellaneous)
Poison control
Wastewater
010501 environmental sciences
01 natural sciences
Methamphetamine
Drug Users
Young Adult
03 medical and health sciences
chemistry.chemical_compound
0302 clinical medicine
Beijing
Environmental health
Humans
Medicine
Computer Simulation
030212 general & internal medicine
education
0105 earth and related environmental sciences
Consumption (economics)
education.field_of_study
business.industry
Health Policy
Uncertainty
Urban Health
Meth
Middle Aged
chemistry
Female
business
Monte Carlo Method
Water Pollutants, Chemical
Environmental Monitoring
Subjects
Details
- ISSN :
- 09553959
- Volume :
- 36
- Database :
- OpenAIRE
- Journal :
- International Journal of Drug Policy
- Accession number :
- edsair.doi.dedup.....7d1a564ec7b3ab59e5f4cb18664b06c9