Wastewater-based epidemiology is increasingly being used as a tool to monitor drug use trends. To minimize costs, studies have typically monitored a small number of days. However, cycles of drug use may display weekly and seasonal trends that affect the accuracy of monthly or annual drug use estimates based on a limited number of samples. This study aimed to rationalize sampling methods for minimizing the number of samples required while maximizing information about temporal trends. A range of sampling strategies were examined: (i) targeted days (e.g., weekends), (ii) completely random or stratified random sampling, and (iii) a number of sampling strategies informed by known weekly cycles in drug use data. Using a time-series approach, analysis was performed for four drugs (MDMA, methamphetamine, cocaine, methadone) collected through a continuous sampling program over 14 months. Results showed, for drugs with weekly cycles (MDMA, methamphetamine and cocaine in this sample), sampling strategies which made use of those weekly cycles required fewer samples to obtain similar information as sampling 5 days per week and had better accuracy than stratified random sampling techniques.

Item Type:	Refereed Article
Keywords:	wastewater, time series, MDMA, cocaine, methamphetamine, methadone, monitoring scheme, sampling strategy, epidemiology, drug use, representative sampling.
Research Division:	Mathematical Sciences
Research Group:	Statistics
Research Field:	Biostatistics
Objective Division:	Expanding Knowledge
Objective Group:	Expanding Knowledge
Objective Field:	Expanding Knowledge in the Mathematical Sciences
UTAS Author:	Humphries, MA (Mrs Melissa Humphries)
UTAS Author:	Bruno, R (Associate Professor Raimondo Bruno)
UTAS Author:	Holland, BR (Associate Professor Barbara Holland)
ID Code:	108233
Year Published:	2016
Web of Science® Times Cited:	6
Deposited By:	Mathematics and Physics
Deposited On:	2016-04-14
Last Modified:	2017-11-03
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