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A comparison between wastewater-based drug data and an illicit drug use survey in a selected community
Accepted Manuscript Title: A comparison between wastewater-based drug data and an illicit drug use survey in a selected community Author: J.H.P. van Wel J. Kinyua A.L.N. van Nuijs S. Salvatore J.G. Bramness A. Covaci G. Van Hal PII: DOI: Reference:
S0955-3959(16)30095-0 http://dx.doi.org/doi:10.1016/j.drugpo.2016.04.003 DRUPOL 1765
To appear in:
International Journal of Drug Policy
Received date: Revised date: Accepted date:
24-7-2015 9-11-2015 4-4-2016
Please cite this article as: van Wel, J. H. P., Kinyua, J., van Nuijs, A. L. N., Salvatore, S., Bramness, J. G., Covaci, A., and Van Hal, G.,A comparison between wastewater-based drug data and an illicit drug use survey in a selected community, International Journal of Drug Policy (2016), http://dx.doi.org/10.1016/j.drugpo.2016.04.003 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
A comparison between wastewater-based drug data and an illicit drug use survey in a selected community
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JHP van Wel1, J Kinyua2, ALN van Nuijs2, S Salvatore3, JG Bramness3, A Covaci2, G Van
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Hal1
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Sciences, University of Antwerp, Belgium
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Department of Epidemiology and Social Medicine, Faculty of Medicine and Health Department of Pharmaceutical Sciences, Faculty of Medicine and Health Sciences,
University of Antwerp, Belgium
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Norwegian Centre for Addiction Research (SERAF), University of Oslo, Norway
Corresponding author
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Email: [email protected]
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Phone: 0032 32652521
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Universiteitsplein 1
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2610 Antwerpen, Belgium
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Manuscript details
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Word count abstract: 233
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Word count text: 4369
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Display Items (Figures and Tables): 3
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References: 31
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Key words: wastewater-based epidemiology, wastewater, survey, drug use, epidemiology
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Abstract
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Background
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Estimations of drug use are mostly based on population surveys that can suffer from response
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biases. The current study evaluates using wastewater-based epidemiology (WBE) for
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assessing illicit drug use by comparing wastewater data with that from a population survey.
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Methods
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Introductory letters (29,083) were sent to inhabitants of Lier, Belgium, asking them to
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participate in an online survey study. Participants were asked to indicate their drug use in the
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past week for a 12-week period (September-November 2014). Concomitant wastewater
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samples were collected from the associated wastewater treatment plant in four bi-weekly
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periods. Samples were analyzed using solid-phase extraction and liquid chromatography
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coupled to tandem mass spectrometry (LC-MS/MS).
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Results
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On average, 263 (1%) inhabitants filled out the questionnaire each week. According to the
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survey results, cannabis was the most used drug, followed by amphetamine, cocaine and
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methylenedioxymethamphetamine (MDMA). Wastewater data corroborated these results.
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Cocaine, amphetamine and MDMA showed a significant difference between days of the
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week. The four sampling periods differed significantly from each other for cocaine,
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amphetamine and methadone.
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Conclusion
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Observed drug consumption patterns from survey and wastewater data match national and
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international data. Wastewater analyses confirm that WBE can be reliably used to confirm
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patterns and trends in drug use. Future studies should focus on identifying the most opportune
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sampling period giving the most reliable estimates of drug use and use smaller, contained
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communities such as festivals or prisons if methodology allows.
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Introduction
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Based on survey studies an estimated 5.3% of European adults have used cannabis in the past
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year (EMCDDA, 2014). However, it has been questioned how reliable these results are since
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survey studies suffer from a number of methodological issues. Firstly, drug users are in
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general a challenging population to work with when it comes to survey research. The overall
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low number of current drug users decreases the chances of including them in a general
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population survey, thereby gathering too little data to make a reliable statement about drug
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use in that population. Also, drug users as a population may be less likely to fill out the
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surveys, for example because they are afraid of judicial consequences or because they live in
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a situation where they cannot be reached (i.e. not having a postal address). Furthermore, due
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to the work-intensive nature of population surveys, it can take several weeks to months from
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the starting point of a survey study until the results of a survey can be communicated.
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Considering the dynamic character of the drug market, use patterns could have changed
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during that time and new drugs and trends may have emerged, thereby decreasing the validity
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of the survey (Griffiths & Mounteney, 2010). However, one of the greatest issues with survey
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research is the possibility of reporting errors on a certain topic due to its sensitive nature, as is
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the case with questions on drug use (Tourangeau & Yan, 2007). This makes population
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surveys vulnerable to response biases since users may either under- or over-report their drug
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use.
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There are a number of options to either circumvent these issues concerning collecting
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data on drug use or to supplement the information collected from survey research. These
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include extrapolating from registered traffic accidents, hospital admissions or admission to
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addiction clinics as well as looking at police data on drug seizures and trafficking. However,
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none of these methods can give the full picture of actual drug consumption. Thus, there is a
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lack of data on current drug use in the general population and methods complementary to
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traditional studies are necessary. These methods should not only complement current
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measures of drug use in the population, but may also make it possible to combine both
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subjective and objective measures of drug use and thereby increase the accuracy of drug use
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epidemiology significantly. One of these potentially useful new approaches is analyzing wastewater to assess the
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use of illicit drugs in an area served by a wastewater treatment plant (WWTP). Hereby,
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wastewater is analyzed for the presence of drug target residues (DTRs): parent compounds
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and/or metabolites. DTRs end up in wastewater after drug use, metabolism and subsequent
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excretion. In the past 10-15 years, the field of wastewater-based epidemiology (WBE) has
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seen important improvements. Since its first application in 2005 (Zuccato et al., 2005),
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wastewater analysis techniques for DTRs have continued to be refined and extended and
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protocols for the correct handling and storage of wastewater samples have been developed
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(Castiglioni, Bijlsma, et al., 2013). WBE has a number of advantages over traditional survey
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methods of estimating drug use. The presence of DTRs can be measured in near real-time as
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time from sampling to data reporting takes approximately two weeks (anecdotal evidence).
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Thus, trends and changes in drug use can be detected faster and more accurately than with
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traditional survey-based techniques. Furthermore, since WBE is performed on the combined
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wastewater from a large number of households (i.e. the catchment area of a WWTP), none of
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DTRs in the wastewater can be traced back to a certain individual. This makes the method
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truly anonymous and, if done in large enough samples, without major ethical issues (Hall et
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al., 2012; Prichard, Hall, de Voogt, & Zuccato, 2014). Finally, the use of DTRs as objective
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indicators of drug use could eliminate the need for subjective reporting from the population if
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the goal is performing a quantitative measurement of drug use. However, as mentioned by
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Castiglioni, Thomas, Kasprzyk-Hordern, Vandam, & Griffiths (2013), research making a
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direct comparison between WBE data and traditional epidemiological indicators has been
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scarce. This is necessary in order to promote the use of WBE either as the sole or as an
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additional method for monitoring drug use in the general population. Previous research on
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combining WBE with other epidemiological methods has highlighted the need for using
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comparable populations while performing these studies (e.g. a WWTP and survey covering
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the same population) (Reid et al., 2012). This would require a rigorous approach whereby
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WBE and population surveys are conducted simultaneously. Therefore, in the study described
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here the aim was to compare the usefulness of WBE for assessing illicit drug use in a
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community by comparing the results of wastewater analysis with those from a concomitantly
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administered population survey.
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Methods
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Wastewater samples
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Sampling
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During autumn 2014, a bi-weekly sampling campaign was set up in the WWTP of Lier,
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Belgium. The selected WWTP has a design capacity of 30,600 inhabitant equivalents (data
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from www.aquafin.be, accessed 23-01-2015) and serves around 35,000 inhabitants. The city 4 Page 4 of 22
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of Lier was chosen for this study because the WWTP covered only the city of Lier, so that the
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data obtained from the wastewater study and the data from the survey study would cover the
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same population. Another advantage for choosing Lier is that it does not have a large
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commuter population, which again contributes to doing better comparisons. The sampling campaign resulted in data from four two-week periods (called sampling
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sessions), spanning 01 September 2014 until 30 November 2014. For each two-week period,
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24-h composite wastewater samples were collected daily. The composite sampling was done
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in a time-proportional manner with 10-min time intervals. All samples were collected in high-
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density polyethylene containers and stored at -20 ºC until analysis.
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Analytical methodology
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Wastewater samples were analysed according to previously validated and published methods
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(van Nuijs et al., 2009; van Nuijs et al., 2013; Kinyua et al., in press). Samples were first
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filtered through a glass filter (0.7 µm retention capacity) to remove solid particles. This was
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followed by a solid-phase extraction (SPE) procedure on Oasis MCX and Oasis HLB
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cartridges to concentrate analytes and remove interferences. Resulting extracts were analyzed
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by liquid chromatography coupled to tandem mass spectrometry. The DTRs of interest were
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cocaine, benzoylecgonine (BE, being the main human metabolite of cocaine (Jufer, Walsh, &
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Cone, 1998)), amphetamine, methamphetamine, methylenedioxymethamphetamine (MDMA),
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2-ethylidene-1,5-dimethyl-3,3-diphenylpyrrolidine (EDDP, as the specific metabolite of
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methadone), ketamine, 6-monoacetylmorphine (6-MAM, as the specific human metabolite of
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heroin), and 11-nor-9-carboxy-delta-9-tetrahydrocannabinol (THC-COOH, as the specific
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metabolite of cannabis). Further details about sample preparation, analysis and quality control
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are described elsewhere (van Nuijs et al., 2009; van Nuijs et al., 2013; Kinyua et al., in press).
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Measured concentrations (in ng/L) were multiplied by the flow rate of the sample (in L/day)
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to obtain mass loads (expressed in mg/day) for all DTRs. Correction factors (Castiglioni,
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Bijlsma, et al., 2013; Ort et al., 2014) were then applied to the mass loads for each DTR in
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order to calculate actual drug use and correct for differences in excretion patterns of illicit
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drugs (see table SI-1). This results in a value referred to as ‘drug consumption’ (expressed in
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mg/day).
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Surveys
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In August 2014, 29,083 introductory letters were sent out to the inhabitants of Lier above the
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age of 15 to inform them about the study and how they could participate. In order to preserve 5 Page 5 of 22
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the privacy of the participants, all the addresses were collected by employees of the city
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council and letters were sent using an external mailing company. At no point in data
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collection did the researchers have access to personal information about the participants,
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except that which they chose to divulge themselves. In the introductory letter, it was explained that a web-based survey would be made
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available during the same period as the wastewater sampling campaign (i.e. September 2014-
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November 2014) and the addressee was asked to fill out this questionnaire. Furthermore, it
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was made clear that although the weekly completion of the survey was preferred, every type
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of participation was allowed (e.g. once, twice or more times). Participants could choose to
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leave their e-mail address through which they would receive a reminder to fill out the
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questionnaire each week. While the focus of the survey was on the past-week use of illicit
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drugs (cannabis, cocaine, (meth)amphetamines, heroin, MDMA, ketamine, new psychoactive
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substances (NPS) or mephedrone), participants were also asked to indicate if they had used
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alcohol, tobacco or a number of pharmaceutical drugs such as codeine, methadone,
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dextroamphetamine (Dexedrine®) or methylphenidate (Concerta®, Ritalin®) in the past
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week. If the answer was “no” for all substances, they could click ahead to the end of the
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questionnaire. If the answer was “yes”, a page opened with further questions on the use of the
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selected substance, such as the number of days they used, the amount they used and in which
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way they had used it. In this way, the total duration of the questionnaire could vary between
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participants and between weeks, depending on the use pattern of each individual. The
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questions were partly taken from the validated Belgian Health Interview Survey and comply
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with guidelines for drug use questionnaires as mentioned in (Bühringer & Sassen, 2010).
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Ethical approval for the study was acquired from the Ethical Committee of the Social
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Sciences and Humanities of the University of Antwerp. Participants were offered the chance
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to win a prize if they participated in the study. This was checked by them filling out their e-
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mail address at the start of the questionnaire. In order to prevent persons who did not want to
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leave their personal data from not participating, this was not a required field for continuing to
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the actual survey. All participants were required to give consent by agreeing to an informed
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consent statement on the website prior to continuing to the actual survey.
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Statistics
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All data were analyzed using IBM SPSS version 22.0 for Windows. The data on self-reported
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drug use were summarized using means and standard deviation (SD). The calculated drug
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consumption (mg/day) from the wastewater data was identified in two ways: as (1) belonging 6 Page 6 of 22
to one of four sampling sessions or (2) as separate weekdays. In order to do this, drug
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consumption was averaged over sampling sessions and days of the week respectively (e.g. all
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data belonging to Monday were averaged and compared with all averaged data from
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Tuesdays). First, Shapiro-Wilk’s tests were done to check for normality of calculated illicit
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drug consumption. None of the tested substances were normally distributed or homogenous.
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Thus, separate Kruskal-Wallis tests were used to calculate whether a significant difference
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existed in drug consumption over the four sampling sessions or if there was a significant
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difference between weekdays. If significant, further post-hoc Dunn-Bonferroni tests would be
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employed to test for differences between two separate sampling sessions or between two
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separate weekday pairs. The α-criterion was set to 0.05.
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In order to correlate the survey data with the wastewater data, per week the yes-
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responses for each individual drug were summed and drug consumption (mg/day) was
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averaged for each week. Spearman rank correlations were then done to assess the relationship
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between survey and wastewater data.
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Results
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Surveys
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A total of 3425 questionnaires were collected over the 12 week survey period. This amounted
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to an average of 263 unique participants each week (response rate approximately 1%). A
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summary of responses (in percentages) can be found in Table 1. In week 10, there was a sharp
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decline in the number of participants. During this week, the program used to send automatic
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e-mails did not work properly and therefore less people received reminders to fill out the
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questionnaire. The average age of participants was 42.8 years. The overall male/female ratio
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was about 1:2. Over 95% of participants had completed at least high school education, which
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was expected since high school is compulsory in Belgium.
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--insert table 1--
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Wastewater analyses
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Shown in Figure 1 are the log10-transformed results of the calculated use of amphetamine
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(AMP), cocaine (using BE, its main human metabolite), methadone (using its main metabolite
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EDDP), MDMA and cannabis (using its main metabolite THC-COOH). No ketamine,
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methamphetamine or 6-MAM were detected in the samples and were not included in the
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statistical analyses. Cannabis is the most used drug in the city of Lier, followed by the
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stimulants amphetamine and cocaine. The level of MDMA was intermediate, while EDDP
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could be detected in the samples only at low levels.
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-- Insert figure 1 --The Kruskal-Wallis test showed significant differences between the four sample
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sessions for cocaine (χ2(3)=9.55, p<.05), amphetamine (χ2(3)=12.62, p<.05) and methadone
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(χ2(3)=16.85, p<.05). There were no differences between sample sessions for MDMA
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(χ2(3)=4.24, p=.24) or cannabis (χ2(3)=6.93, p=.07). Additional Dunn’s test post-hoc
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comparisons between sessions showed that for cocaine a significant difference was seen
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between sample session 2 and sample session 4 (p<.05), for amphetamine between sample
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session 2 and both sample sessions 3 (p<.05) and 4 (p<.05), and for methadone between
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sample sessions 1 and 2 (p=.05) and 1 and 4 (p<.05) (see also Figure SI-1).
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Kruskal-Wallis tests showed significant differences between weekday scores for
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cocaine (χ2(6)=35.63, p<.001), MDMA (χ2(6)=38.43, p<.001), amphetamine (χ2(6)=13.11,
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p<.05) and cannabis (χ2(6)=14.42, p<.05), but not for methadone (χ2(3)=7.45, p=.28). For
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cannabis, these differences showed only in the comparison between Monday and Thursday
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(Dunn’s test p<.05). Cocaine, amphetamine and MDMA showed a typical party-drug profile,
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where on weekend days more was used than on weekdays (see Figure 2). Although initial
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Kruskal-Wallis testing was significant for amphetamine, post-hoc Dunn’s testing did not
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show a difference between weekdays for this drug. There were significant differences
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between Sunday and Tuesday ( p=.001) Wednesday (p=.001), Thursday (p<.001) and Friday
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(p<.05) for cocaine. For MDMA, significant differences were seen between Sunday and
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Wednesday (\p<.001), Thursday (p=.001) and Friday (p=.01), between Friday and Monday
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(p=.01) and between Monday and Wednesday (p<.001) and Thursday (p=.001).
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-- Insert figure 2 ---
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Survey data vs wastewater analyses
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Spearman’s rank correlation analyses were executed between all DTRs targeted in the
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wastewater analysis and the relevant survey items. There were no significant correlations
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between any of the calculated drug consumption values and the numbers of persons indicating
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having used that drug on the survey. However, a trend towards a negative correlation was
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found for MDMA (rs=.-72, p=-.07). No Spearman’s rank correlations could be calculated for
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methadone, heroin or ketamine, since either no one indicated having used these drugs in the
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surveys (methadone) or drug levels were non-existent or below the limit of quantification
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(ketamine and 6-MAM). 8 Page 8 of 22
Discussion
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The main goal of this study was to simultaneously conduct WBE and a population survey in
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order to perform correlation analyses on the data. In the survey part of the study, only a few
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people indicated they used any type of drug in the past week. The most prevalent illicit drug
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according to the survey results was cannabis, followed by cocaine, amphetamine and MDMA.
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None of the investigated correlations between drug use as measured by WBE and the
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population survey data were significant. Interestingly, the correlation between MDMA in
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wastewater and the indicated use in the survey approached significance in a negative
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direction. Thus, when an increase in the use of MDMA was seen through wastewater analysis,
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a decrease in the amount of responses on the questionnaires occurred. A possible explanation
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for this phenomenon could be that persons who used a certain drug were experiencing a
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hangover or Monday ‘low’. This might prevent them from filling out the survey the day(s)
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following use, thus leading to underreporting. Although there was no direct correlation
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between the survey data and wastewater data, the distribution of use patterns in the survey
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matches what was found in the wastewater. This reiterates that drug use patterns investigated
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through traditional methods match those found in wastewater. Potentially, WBE might be a
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better method than survey research to estimate the amount of drug use since it does not
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depend on response rates or honest responding. However, since wastewater can only give
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absolute numbers on drug use (i.e. how many mg of drug was used) and not on subjective data
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(how much or in what way someone uses), population surveys are still preferable if more in-
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depth knowledge is needed.
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Analyses of the wastewater data provided four interesting results, which will be
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discussed below.
First, results from the current study are in agreement with the results from national
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drug use surveys. As is the case in the rest of Belgium, cannabis is the most used drug,
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followed by amphetamine, cocaine and MDMA (Scientific Institute of Public Health, 2013).
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The levels of heroin, methamphetamine and ketamine were below the limit of quantification,
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thus their consumption in Lier is low to negligible. Results are further in accordance with
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those reported from other countries of the European Union as reported by the European
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Monitoring Centre for Drugs and Drug Abuse (EMCDDA, 2014), with the exception of
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cocaine and amphetamine, which are inverted. This might be due to differences in availability
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of both drugs in Belgium compared to that of the European Union in general. Second, it was demonstrated that drugs showed a different pattern of use throughout
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the week. Cocaine and MDMA use increased during the weekend, while cannabis and 9 Page 9 of 22
methadone did not show a week/weekend variation. Such differences between week and
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weekend days are consistent with previous data (Huerta-Fontela, Galceran, Martin-Alonso, &
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Ventura, 2008; Jaroslav et al., 2014; Reid, Langford, Mørland, & Thomas, 2011; van Nuijs et
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al., 2009). Further, these results confirm findings from sociological studies on drug use
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(Curran & Travill, 1997; Parrott, Lock, Conner, Kissling, & Thome, 2008; Verheyden,
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Hadfield, Calin, & Curran, 2002). As mentioned above, cannabis and methadone do not show
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a week vs. weekend pattern of use. This is not surprising, since both cannabis and methadone
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are drugs typically taken multiple times per week (Douaihy, Kelly, & Sullivan, 2013;
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Perkonigg et al., 1999).
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Third, the current study also illustrates one of the weaknesses of WBE. From the
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results shown here, it can be seen that patterns of drug use can differ significantly over the
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course of several weeks. Since WBE aims to be able to give accurate descriptions of drug use
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in a population, variations in drug levels as a consequence of uncontrollable variables should
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be taken into account. In this study, conclusions on overall drug use based on choosing one
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sampling session over the other could differ significantly. Thus, this study illustrates the point
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made by Ort et al. (2014) that for future sampling campaigns it is wiser not to pick a random
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week of the year, but instead use at least 56 random stratified samples. Future studies should
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focus on what the most advantageous method of sampling is with regard to the timeframe in
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which sampling takes place as well as how long of a period it should be. For example, using
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continuous sampling on a certain day of the week could reduce uncertainty about the results
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from WBE by 5-10%, according to Castiglioni et al.(2013). Nevertheless, large variations
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between weeks can also be indicative of true variations in drug use thus results such as these
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should not be disregarded too quickly.
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Related to the above, a fourth point that this study illustrates is that WBE is sensitive
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enough to detect abnormal events. Previous studies have shown that increasing levels of illicit
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drugs during and after a big event are picked up by wastewater analyses (Bijlsma, Serrano,
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Ferrer, Tormos, & Hernández, 2014; Jiang, Lee, Fang, Tu, & Liang, 2015). However, those
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studies were always carried out with the aim of finding such differences and might therefore
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be more sensitive to finding them. In trying to explain the increase in the use of amphetamine
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and cocaine during sampling session 2 we discovered that at the same time, two significant
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events were taking place (a reunion party held in a club and a regional event). This could
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explain why the weekend peaks during sampling session 2 were higher than during the other
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weeks. Thus, caution should be exerted in choosing the period of analysis or data collection
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since a large event occurring at the same time as the sampling period might cause 10 Page 10 of 22
misinterpretation of data on illicit drug use among the inhabitants of a certain region. An
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increase in measured drug consumption could have three reasons; 1) an increase in drug
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consumption by the inhabitants, 2) an increase in persons who consume drugs in the region
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(i.e. an increased number of visitors) or 3) a combination of the two. Therefore, researchers
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should be careful interpreting drug consumption in a population from data corrected using
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solid population estimates. Senta et al (Senta, Gracia-Lor, Borsotti, Zuccato, & Castiglioni,
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2015) have been working on a method to assess fluctuating population sizes which would
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solve this issue.
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Unfortunately, response rates to the surveys were very low and as such are a major
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limitation to interpreting the survey data alone as well as the comparison between WBE and
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survey data. Despite applying a number of proven techniques to improve survey response
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such as including incentives for participation and sending out personalized missives (Cook,
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Heath, & Thompson, 2000), only a small number of people could be motivated to participate
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in the survey (approximately 1% of the eligible population). Our data are in agreement with
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the national data on drug use in that the percentage of users is quite low and cannabis is the
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most used drug. Numbers of recent drug use in Belgium in adults aged 15-64 range from
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2.6% for cannabis (in the past 30 days) to 0.8% for any drug other than cannabis (in the past
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year) (Scientific Institute of Public Health, 2013) and this matches our results. However, the
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small amount of participants remains a limitation to the interpretation of the data from the
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survey study.
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This study is the first attempt to combine WBE and survey-based epidemiology using
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the same timeline. Due to the low number of completed population surveys, the comparison
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of wastewater data to population survey data proved to be difficult. This is a major limitation
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to the comparison between wastewater results and population surveys in this study. A possible
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reason for the low response rate might be that this study employed an online questionnaire.
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However, it is unlikely that the used medium is to blame since recent studies have shown
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online surveys to have similar response rates to paper-and-pen surveys (see (Greenlaw &
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Brown-welty, 2009; van Gelder, Bretveld, & Roeleveld, 2010) for a review). Worldwide a
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declining trend has been seen in the willingness of persons to participate in survey research
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and this might also be at work here (McCluskey & Topping, 2011). Furthermore, it might be
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possible that when inhabitants were informed of the participation of their city in the
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wastewater study, they felt unwilling to give out more information through surveys than that
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which was already gathered through wastewater. Concern about the use of wastewater
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research has been reported previously (Hall et al., 2012) and, in our case, might have led to 11 Page 11 of 22
non-participation. Therefore, future studies combining wastewater and survey research should
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be careful about exactly what to communicate to participating cities about the study to make
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sure such bias does not occur. A way to possibly increase response rates in a future study
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could be to embed the questions about drug use within a study on general health, where the
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topic might become less threatening to talk about (Tourangeau & Yan, 2007). This adds the
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advantage of personalized interviewing, which usually gathers a higher response rate.
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While it is important to combine WBE and survey research to make a good estimation
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of their quality and accuracy, the low response rates indicate that it might be too difficult to
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do so in a relatively small city (population ±35,000) such as the one used in this study. One
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solution might be to perform a similar study in smaller communities such as festivals or
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schools. However, several ethical considerations should then be considered because the
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smaller the catchment area gets, the more difficult it is to guarantee anonymity and thus the
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chances of adverse consequences for the inhabitants of a small community increase (Hall et
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al., 2012; Prichard et al., 2014). Furthermore, the technology behind WBE has not progressed
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far enough to make a reliable estimate of drug use when drug use in a sample is low and
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populations small (Ort, Lawrence, Rieckermann, & Joss, 2010), leading to unreliable results.
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The current study also illustrates how a body of government or a research institute
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could use WBE to make an assessment of drug use in the general population. For example,
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from our results, it can be deduced that the opioid replacement program probably is effective
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since no heroin could be found in the wastewater while methadone use was detected. Policy
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makers could potentially use this information to instigate more focused prevention programs
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or health care interventions or evaluate their current programs. Another possible use of WBE
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could be as an evaluation tool for drug policy. This could be done by performing repeated
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wastewater sampling, and thereby investigating whether following a policy alteration, a
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change in drug use as reflected in the amount of DTR present in wastewater occurs.
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In conclusion, the study discussed in this paper is instrumental in providing support for
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the usefulness of WBE in the estimation of illicit drug use. Declining response rates to
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population surveys might lead to decreases in the reliability of such surveys, especially in
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regard to sensitive topics such as drug use. The data on illicit drug consumption through
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wastewater analysis indicate that WBE can be reliably used to confirm patterns and trends in
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drug use. Future studies on the methodology of WBE should focus on identifying the most
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ideal timeframes in which sampling should take place in order to use the most opportune
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period giving the most reliable estimates of drug use. In order to carry out rigorous ecological
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comparisons between WBE data and survey data on illicit drug use, research should focus on 12 Page 12 of 22
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smaller, contained communities such as festivals or prisons while keeping in mind several
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ethical considerations and methodological constrictions. This study also illustrates how WBE
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can be used to inform policy makers about drug use in the general population.
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Acknowledgements
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The study is supported by funding from the European Union Seventh Framework Programme
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for research, technological development and demonstration under grant agreement number
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317205. AvN is thankful for the financial support from the FWO (Research Foundation
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Flanders). All authors would like to thank the inhabitants and the council of the city of Lier
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for their cooperation in the study. Alain Vandelannoote and the complete team of WWTP Lier
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(Aquafin) are greatly acknowledged for their help in the sampling of wastewater samples.
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Supplementary information is available
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Figure 1: Drug consumption per drug in mg/day (log10 transformed). Grey, vertical lines indicate weekends. Figure 2: Boxplots showing differences between different days of the week for A) Used MDMA (mg/day), B) Used cocaine (mg/day), C) Used amphetamine (mg/day) and D) Used
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cannabis (mg/day)
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Conflict of interest statement We wish to confirm that there are no known conflicts of interest associated with this publication and there has been no significant financial support for this work that could have influenced its outcome. We confirm that the manuscript has been read and approved by all named authors and that there are no other persons who satisfied the criteria for authorship but are not listed. We further confirm that the order of authors listed in the manuscript has been approved by all of us.
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We confirm that we have given due consideration to the protection of intellectual property associated with this work and that there are no impediments to publication, including the timing of publication, with respect to intellectual property. In so doing we confirm that we have followed the regulations of our institutions concerning intellectual property.
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We understand that the Corresponding Author is the sole contact for the Editorial process (including Editorial Manager and direct communications with the office). He/she is responsible for cmmunicating with the other authors about progress, submissions of revisions and final approval of proofs. We confirm that we have provided a current, correct email address which is accessible by the Corresponding Author and which has been configured to accept email from the International Journal of Drug Policy.
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Week Participants Average Gender Cannabis Cocaine MDMA Amphetamine (#) (#) age (yrs) (M/F) (%) (%) (%) (%) 325 43.3 119/206 1.2 0.3 0.0 0.0 1 307 42.3 114/193 1.6 1.0 0.3 0.7 2 306 42.5 113/193 1.0 0.7 0.3 0.3 3 296 41.9 110/186 2.7 0.3 0.0 0.3 4 297 42.4 97/200 1.0 0.0 0.3 0.3 5 268 42.3 91/177 0.7 0.0 0.0 0.0 6 269 42.5 91/178 1.1 0.4 0.0 0.4 7 257 43.3 98/159 1.2 0.0 0.0 0.4 8 236 43.4 90/146 2.1 0.0 0.0 0.0 9 87 41.5 34/53 0.0 0.0 0.0 0.0 10 273 43 102/171 1.5 0.4 0.4 0.7 11 251 43.7 88/163 1.2 0.0 0.0 0.4 12 253 44 94/159 1.2 0.8 0.4 0.0 13 263 42.8 95/168 1.3 0.3 0.1 0.3 Average
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Table 1: Percentage of participants indicating past week drug use (by answering ‘yes’ on the
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Highlights (for review)
Highlights
Confirmation of week vs weekends pattern of use for party drugs ecstasy, cocaine, amphetamine
Ordering of drugs according to use; amphetamine (1), cocaine (2), cannabis (3), MDMA (4), methadone (6), ketamine (7 (=absent)) matches national and international survey data Large regional events can be picked up retrospectively in wastewater data.
Meaningful correlations between survey and wastewater results difficult since the
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number of survey responses was very low
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S0955-3959(16)30095-0 http://dx.doi.org/doi:10.1016/j.drugpo.2016.04.003 DRUPOL 1765
To appear in:
International Journal of Drug Policy
Received date: Revised date: Accepted date:
24-7-2015 9-11-2015 4-4-2016
Please cite this article as: van Wel, J. H. P., Kinyua, J., van Nuijs, A. L. N., Salvatore, S., Bramness, J. G., Covaci, A., and Van Hal, G.,A comparison between wastewater-based drug data and an illicit drug use survey in a selected community, International Journal of Drug Policy (2016), http://dx.doi.org/10.1016/j.drugpo.2016.04.003 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
A comparison between wastewater-based drug data and an illicit drug use survey in a selected community
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JHP van Wel1, J Kinyua2, ALN van Nuijs2, S Salvatore3, JG Bramness3, A Covaci2, G Van
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Hal1
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Sciences, University of Antwerp, Belgium
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Department of Epidemiology and Social Medicine, Faculty of Medicine and Health Department of Pharmaceutical Sciences, Faculty of Medicine and Health Sciences,
University of Antwerp, Belgium
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Norwegian Centre for Addiction Research (SERAF), University of Oslo, Norway
Corresponding author
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Email: [email protected]
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Phone: 0032 32652521
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Universiteitsplein 1
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2610 Antwerpen, Belgium
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Manuscript details
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Word count abstract: 233
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Word count text: 4369
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Display Items (Figures and Tables): 3
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References: 31
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Key words: wastewater-based epidemiology, wastewater, survey, drug use, epidemiology
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Abstract
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Background
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Estimations of drug use are mostly based on population surveys that can suffer from response
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biases. The current study evaluates using wastewater-based epidemiology (WBE) for
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assessing illicit drug use by comparing wastewater data with that from a population survey.
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Methods
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Introductory letters (29,083) were sent to inhabitants of Lier, Belgium, asking them to
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participate in an online survey study. Participants were asked to indicate their drug use in the
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past week for a 12-week period (September-November 2014). Concomitant wastewater
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samples were collected from the associated wastewater treatment plant in four bi-weekly
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periods. Samples were analyzed using solid-phase extraction and liquid chromatography
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coupled to tandem mass spectrometry (LC-MS/MS).
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Results
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On average, 263 (1%) inhabitants filled out the questionnaire each week. According to the
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survey results, cannabis was the most used drug, followed by amphetamine, cocaine and
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methylenedioxymethamphetamine (MDMA). Wastewater data corroborated these results.
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Cocaine, amphetamine and MDMA showed a significant difference between days of the
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week. The four sampling periods differed significantly from each other for cocaine,
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amphetamine and methadone.
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Conclusion
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Observed drug consumption patterns from survey and wastewater data match national and
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international data. Wastewater analyses confirm that WBE can be reliably used to confirm
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patterns and trends in drug use. Future studies should focus on identifying the most opportune
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sampling period giving the most reliable estimates of drug use and use smaller, contained
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communities such as festivals or prisons if methodology allows.
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Introduction
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Based on survey studies an estimated 5.3% of European adults have used cannabis in the past
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year (EMCDDA, 2014). However, it has been questioned how reliable these results are since
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survey studies suffer from a number of methodological issues. Firstly, drug users are in
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general a challenging population to work with when it comes to survey research. The overall
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low number of current drug users decreases the chances of including them in a general
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population survey, thereby gathering too little data to make a reliable statement about drug
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use in that population. Also, drug users as a population may be less likely to fill out the
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surveys, for example because they are afraid of judicial consequences or because they live in
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a situation where they cannot be reached (i.e. not having a postal address). Furthermore, due
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to the work-intensive nature of population surveys, it can take several weeks to months from
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the starting point of a survey study until the results of a survey can be communicated.
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Considering the dynamic character of the drug market, use patterns could have changed
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during that time and new drugs and trends may have emerged, thereby decreasing the validity
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of the survey (Griffiths & Mounteney, 2010). However, one of the greatest issues with survey
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research is the possibility of reporting errors on a certain topic due to its sensitive nature, as is
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the case with questions on drug use (Tourangeau & Yan, 2007). This makes population
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surveys vulnerable to response biases since users may either under- or over-report their drug
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use.
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There are a number of options to either circumvent these issues concerning collecting
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data on drug use or to supplement the information collected from survey research. These
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include extrapolating from registered traffic accidents, hospital admissions or admission to
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addiction clinics as well as looking at police data on drug seizures and trafficking. However,
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none of these methods can give the full picture of actual drug consumption. Thus, there is a
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lack of data on current drug use in the general population and methods complementary to
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traditional studies are necessary. These methods should not only complement current
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measures of drug use in the population, but may also make it possible to combine both
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subjective and objective measures of drug use and thereby increase the accuracy of drug use
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epidemiology significantly. One of these potentially useful new approaches is analyzing wastewater to assess the
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use of illicit drugs in an area served by a wastewater treatment plant (WWTP). Hereby,
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wastewater is analyzed for the presence of drug target residues (DTRs): parent compounds
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and/or metabolites. DTRs end up in wastewater after drug use, metabolism and subsequent
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excretion. In the past 10-15 years, the field of wastewater-based epidemiology (WBE) has
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seen important improvements. Since its first application in 2005 (Zuccato et al., 2005),
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wastewater analysis techniques for DTRs have continued to be refined and extended and
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protocols for the correct handling and storage of wastewater samples have been developed
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(Castiglioni, Bijlsma, et al., 2013). WBE has a number of advantages over traditional survey
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methods of estimating drug use. The presence of DTRs can be measured in near real-time as
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time from sampling to data reporting takes approximately two weeks (anecdotal evidence).
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Thus, trends and changes in drug use can be detected faster and more accurately than with
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traditional survey-based techniques. Furthermore, since WBE is performed on the combined
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wastewater from a large number of households (i.e. the catchment area of a WWTP), none of
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DTRs in the wastewater can be traced back to a certain individual. This makes the method
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truly anonymous and, if done in large enough samples, without major ethical issues (Hall et
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al., 2012; Prichard, Hall, de Voogt, & Zuccato, 2014). Finally, the use of DTRs as objective
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indicators of drug use could eliminate the need for subjective reporting from the population if
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the goal is performing a quantitative measurement of drug use. However, as mentioned by
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Castiglioni, Thomas, Kasprzyk-Hordern, Vandam, & Griffiths (2013), research making a
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direct comparison between WBE data and traditional epidemiological indicators has been
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scarce. This is necessary in order to promote the use of WBE either as the sole or as an
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additional method for monitoring drug use in the general population. Previous research on
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combining WBE with other epidemiological methods has highlighted the need for using
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comparable populations while performing these studies (e.g. a WWTP and survey covering
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the same population) (Reid et al., 2012). This would require a rigorous approach whereby
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WBE and population surveys are conducted simultaneously. Therefore, in the study described
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here the aim was to compare the usefulness of WBE for assessing illicit drug use in a
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community by comparing the results of wastewater analysis with those from a concomitantly
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administered population survey.
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Methods
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Wastewater samples
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Sampling
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During autumn 2014, a bi-weekly sampling campaign was set up in the WWTP of Lier,
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Belgium. The selected WWTP has a design capacity of 30,600 inhabitant equivalents (data
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from www.aquafin.be, accessed 23-01-2015) and serves around 35,000 inhabitants. The city 4 Page 4 of 22
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of Lier was chosen for this study because the WWTP covered only the city of Lier, so that the
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data obtained from the wastewater study and the data from the survey study would cover the
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same population. Another advantage for choosing Lier is that it does not have a large
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commuter population, which again contributes to doing better comparisons. The sampling campaign resulted in data from four two-week periods (called sampling
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sessions), spanning 01 September 2014 until 30 November 2014. For each two-week period,
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24-h composite wastewater samples were collected daily. The composite sampling was done
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in a time-proportional manner with 10-min time intervals. All samples were collected in high-
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density polyethylene containers and stored at -20 ºC until analysis.
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Analytical methodology
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Wastewater samples were analysed according to previously validated and published methods
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(van Nuijs et al., 2009; van Nuijs et al., 2013; Kinyua et al., in press). Samples were first
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filtered through a glass filter (0.7 µm retention capacity) to remove solid particles. This was
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followed by a solid-phase extraction (SPE) procedure on Oasis MCX and Oasis HLB
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cartridges to concentrate analytes and remove interferences. Resulting extracts were analyzed
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by liquid chromatography coupled to tandem mass spectrometry. The DTRs of interest were
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cocaine, benzoylecgonine (BE, being the main human metabolite of cocaine (Jufer, Walsh, &
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Cone, 1998)), amphetamine, methamphetamine, methylenedioxymethamphetamine (MDMA),
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2-ethylidene-1,5-dimethyl-3,3-diphenylpyrrolidine (EDDP, as the specific metabolite of
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methadone), ketamine, 6-monoacetylmorphine (6-MAM, as the specific human metabolite of
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heroin), and 11-nor-9-carboxy-delta-9-tetrahydrocannabinol (THC-COOH, as the specific
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metabolite of cannabis). Further details about sample preparation, analysis and quality control
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are described elsewhere (van Nuijs et al., 2009; van Nuijs et al., 2013; Kinyua et al., in press).
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Measured concentrations (in ng/L) were multiplied by the flow rate of the sample (in L/day)
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to obtain mass loads (expressed in mg/day) for all DTRs. Correction factors (Castiglioni,
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Bijlsma, et al., 2013; Ort et al., 2014) were then applied to the mass loads for each DTR in
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order to calculate actual drug use and correct for differences in excretion patterns of illicit
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drugs (see table SI-1). This results in a value referred to as ‘drug consumption’ (expressed in
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mg/day).
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Surveys
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In August 2014, 29,083 introductory letters were sent out to the inhabitants of Lier above the
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age of 15 to inform them about the study and how they could participate. In order to preserve 5 Page 5 of 22
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the privacy of the participants, all the addresses were collected by employees of the city
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council and letters were sent using an external mailing company. At no point in data
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collection did the researchers have access to personal information about the participants,
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except that which they chose to divulge themselves. In the introductory letter, it was explained that a web-based survey would be made
156
available during the same period as the wastewater sampling campaign (i.e. September 2014-
158
November 2014) and the addressee was asked to fill out this questionnaire. Furthermore, it
159
was made clear that although the weekly completion of the survey was preferred, every type
160
of participation was allowed (e.g. once, twice or more times). Participants could choose to
161
leave their e-mail address through which they would receive a reminder to fill out the
162
questionnaire each week. While the focus of the survey was on the past-week use of illicit
163
drugs (cannabis, cocaine, (meth)amphetamines, heroin, MDMA, ketamine, new psychoactive
164
substances (NPS) or mephedrone), participants were also asked to indicate if they had used
165
alcohol, tobacco or a number of pharmaceutical drugs such as codeine, methadone,
166
dextroamphetamine (Dexedrine®) or methylphenidate (Concerta®, Ritalin®) in the past
167
week. If the answer was “no” for all substances, they could click ahead to the end of the
168
questionnaire. If the answer was “yes”, a page opened with further questions on the use of the
169
selected substance, such as the number of days they used, the amount they used and in which
170
way they had used it. In this way, the total duration of the questionnaire could vary between
171
participants and between weeks, depending on the use pattern of each individual. The
172
questions were partly taken from the validated Belgian Health Interview Survey and comply
173
with guidelines for drug use questionnaires as mentioned in (Bühringer & Sassen, 2010).
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Ethical approval for the study was acquired from the Ethical Committee of the Social
174 175
Sciences and Humanities of the University of Antwerp. Participants were offered the chance
176
to win a prize if they participated in the study. This was checked by them filling out their e-
177
mail address at the start of the questionnaire. In order to prevent persons who did not want to
178
leave their personal data from not participating, this was not a required field for continuing to
179
the actual survey. All participants were required to give consent by agreeing to an informed
180
consent statement on the website prior to continuing to the actual survey.
181 182
Statistics
183
All data were analyzed using IBM SPSS version 22.0 for Windows. The data on self-reported
184
drug use were summarized using means and standard deviation (SD). The calculated drug
185
consumption (mg/day) from the wastewater data was identified in two ways: as (1) belonging 6 Page 6 of 22
to one of four sampling sessions or (2) as separate weekdays. In order to do this, drug
187
consumption was averaged over sampling sessions and days of the week respectively (e.g. all
188
data belonging to Monday were averaged and compared with all averaged data from
189
Tuesdays). First, Shapiro-Wilk’s tests were done to check for normality of calculated illicit
190
drug consumption. None of the tested substances were normally distributed or homogenous.
191
Thus, separate Kruskal-Wallis tests were used to calculate whether a significant difference
192
existed in drug consumption over the four sampling sessions or if there was a significant
193
difference between weekdays. If significant, further post-hoc Dunn-Bonferroni tests would be
194
employed to test for differences between two separate sampling sessions or between two
195
separate weekday pairs. The α-criterion was set to 0.05.
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In order to correlate the survey data with the wastewater data, per week the yes-
196
responses for each individual drug were summed and drug consumption (mg/day) was
198
averaged for each week. Spearman rank correlations were then done to assess the relationship
199
between survey and wastewater data.
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Results
202
Surveys
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A total of 3425 questionnaires were collected over the 12 week survey period. This amounted
204
to an average of 263 unique participants each week (response rate approximately 1%). A
205
summary of responses (in percentages) can be found in Table 1. In week 10, there was a sharp
206
decline in the number of participants. During this week, the program used to send automatic
207
e-mails did not work properly and therefore less people received reminders to fill out the
208
questionnaire. The average age of participants was 42.8 years. The overall male/female ratio
209
was about 1:2. Over 95% of participants had completed at least high school education, which
210
was expected since high school is compulsory in Belgium.
211
--insert table 1--
212
Wastewater analyses
213
Shown in Figure 1 are the log10-transformed results of the calculated use of amphetamine
214
(AMP), cocaine (using BE, its main human metabolite), methadone (using its main metabolite
215
EDDP), MDMA and cannabis (using its main metabolite THC-COOH). No ketamine,
216
methamphetamine or 6-MAM were detected in the samples and were not included in the
217
statistical analyses. Cannabis is the most used drug in the city of Lier, followed by the
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stimulants amphetamine and cocaine. The level of MDMA was intermediate, while EDDP
219
could be detected in the samples only at low levels.
220
-- Insert figure 1 --The Kruskal-Wallis test showed significant differences between the four sample
221
sessions for cocaine (χ2(3)=9.55, p<.05), amphetamine (χ2(3)=12.62, p<.05) and methadone
223
(χ2(3)=16.85, p<.05). There were no differences between sample sessions for MDMA
224
(χ2(3)=4.24, p=.24) or cannabis (χ2(3)=6.93, p=.07). Additional Dunn’s test post-hoc
225
comparisons between sessions showed that for cocaine a significant difference was seen
226
between sample session 2 and sample session 4 (p<.05), for amphetamine between sample
227
session 2 and both sample sessions 3 (p<.05) and 4 (p<.05), and for methadone between
228
sample sessions 1 and 2 (p=.05) and 1 and 4 (p<.05) (see also Figure SI-1).
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Kruskal-Wallis tests showed significant differences between weekday scores for
229
cocaine (χ2(6)=35.63, p<.001), MDMA (χ2(6)=38.43, p<.001), amphetamine (χ2(6)=13.11,
231
p<.05) and cannabis (χ2(6)=14.42, p<.05), but not for methadone (χ2(3)=7.45, p=.28). For
232
cannabis, these differences showed only in the comparison between Monday and Thursday
233
(Dunn’s test p<.05). Cocaine, amphetamine and MDMA showed a typical party-drug profile,
234
where on weekend days more was used than on weekdays (see Figure 2). Although initial
235
Kruskal-Wallis testing was significant for amphetamine, post-hoc Dunn’s testing did not
236
show a difference between weekdays for this drug. There were significant differences
237
between Sunday and Tuesday ( p=.001) Wednesday (p=.001), Thursday (p<.001) and Friday
238
(p<.05) for cocaine. For MDMA, significant differences were seen between Sunday and
239
Wednesday (\p<.001), Thursday (p=.001) and Friday (p=.01), between Friday and Monday
240
(p=.01) and between Monday and Wednesday (p<.001) and Thursday (p=.001).
241
-- Insert figure 2 ---
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242 243
Survey data vs wastewater analyses
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Spearman’s rank correlation analyses were executed between all DTRs targeted in the
245
wastewater analysis and the relevant survey items. There were no significant correlations
246
between any of the calculated drug consumption values and the numbers of persons indicating
247
having used that drug on the survey. However, a trend towards a negative correlation was
248
found for MDMA (rs=.-72, p=-.07). No Spearman’s rank correlations could be calculated for
249
methadone, heroin or ketamine, since either no one indicated having used these drugs in the
250
surveys (methadone) or drug levels were non-existent or below the limit of quantification
251
(ketamine and 6-MAM). 8 Page 8 of 22
Discussion
253
The main goal of this study was to simultaneously conduct WBE and a population survey in
254
order to perform correlation analyses on the data. In the survey part of the study, only a few
255
people indicated they used any type of drug in the past week. The most prevalent illicit drug
256
according to the survey results was cannabis, followed by cocaine, amphetamine and MDMA.
257
None of the investigated correlations between drug use as measured by WBE and the
258
population survey data were significant. Interestingly, the correlation between MDMA in
259
wastewater and the indicated use in the survey approached significance in a negative
260
direction. Thus, when an increase in the use of MDMA was seen through wastewater analysis,
261
a decrease in the amount of responses on the questionnaires occurred. A possible explanation
262
for this phenomenon could be that persons who used a certain drug were experiencing a
263
hangover or Monday ‘low’. This might prevent them from filling out the survey the day(s)
264
following use, thus leading to underreporting. Although there was no direct correlation
265
between the survey data and wastewater data, the distribution of use patterns in the survey
266
matches what was found in the wastewater. This reiterates that drug use patterns investigated
267
through traditional methods match those found in wastewater. Potentially, WBE might be a
268
better method than survey research to estimate the amount of drug use since it does not
269
depend on response rates or honest responding. However, since wastewater can only give
270
absolute numbers on drug use (i.e. how many mg of drug was used) and not on subjective data
271
(how much or in what way someone uses), population surveys are still preferable if more in-
272
depth knowledge is needed.
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Analyses of the wastewater data provided four interesting results, which will be
273 274
discussed below.
First, results from the current study are in agreement with the results from national
275 276
drug use surveys. As is the case in the rest of Belgium, cannabis is the most used drug,
277
followed by amphetamine, cocaine and MDMA (Scientific Institute of Public Health, 2013).
278
The levels of heroin, methamphetamine and ketamine were below the limit of quantification,
279
thus their consumption in Lier is low to negligible. Results are further in accordance with
280
those reported from other countries of the European Union as reported by the European
281
Monitoring Centre for Drugs and Drug Abuse (EMCDDA, 2014), with the exception of
282
cocaine and amphetamine, which are inverted. This might be due to differences in availability
283
of both drugs in Belgium compared to that of the European Union in general. Second, it was demonstrated that drugs showed a different pattern of use throughout
284 285
the week. Cocaine and MDMA use increased during the weekend, while cannabis and 9 Page 9 of 22
methadone did not show a week/weekend variation. Such differences between week and
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weekend days are consistent with previous data (Huerta-Fontela, Galceran, Martin-Alonso, &
288
Ventura, 2008; Jaroslav et al., 2014; Reid, Langford, Mørland, & Thomas, 2011; van Nuijs et
289
al., 2009). Further, these results confirm findings from sociological studies on drug use
290
(Curran & Travill, 1997; Parrott, Lock, Conner, Kissling, & Thome, 2008; Verheyden,
291
Hadfield, Calin, & Curran, 2002). As mentioned above, cannabis and methadone do not show
292
a week vs. weekend pattern of use. This is not surprising, since both cannabis and methadone
293
are drugs typically taken multiple times per week (Douaihy, Kelly, & Sullivan, 2013;
294
Perkonigg et al., 1999).
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Third, the current study also illustrates one of the weaknesses of WBE. From the
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results shown here, it can be seen that patterns of drug use can differ significantly over the
297
course of several weeks. Since WBE aims to be able to give accurate descriptions of drug use
298
in a population, variations in drug levels as a consequence of uncontrollable variables should
299
be taken into account. In this study, conclusions on overall drug use based on choosing one
300
sampling session over the other could differ significantly. Thus, this study illustrates the point
301
made by Ort et al. (2014) that for future sampling campaigns it is wiser not to pick a random
302
week of the year, but instead use at least 56 random stratified samples. Future studies should
303
focus on what the most advantageous method of sampling is with regard to the timeframe in
304
which sampling takes place as well as how long of a period it should be. For example, using
305
continuous sampling on a certain day of the week could reduce uncertainty about the results
306
from WBE by 5-10%, according to Castiglioni et al.(2013). Nevertheless, large variations
307
between weeks can also be indicative of true variations in drug use thus results such as these
308
should not be disregarded too quickly.
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Related to the above, a fourth point that this study illustrates is that WBE is sensitive
309 310
enough to detect abnormal events. Previous studies have shown that increasing levels of illicit
311
drugs during and after a big event are picked up by wastewater analyses (Bijlsma, Serrano,
312
Ferrer, Tormos, & Hernández, 2014; Jiang, Lee, Fang, Tu, & Liang, 2015). However, those
313
studies were always carried out with the aim of finding such differences and might therefore
314
be more sensitive to finding them. In trying to explain the increase in the use of amphetamine
315
and cocaine during sampling session 2 we discovered that at the same time, two significant
316
events were taking place (a reunion party held in a club and a regional event). This could
317
explain why the weekend peaks during sampling session 2 were higher than during the other
318
weeks. Thus, caution should be exerted in choosing the period of analysis or data collection
319
since a large event occurring at the same time as the sampling period might cause 10 Page 10 of 22
misinterpretation of data on illicit drug use among the inhabitants of a certain region. An
321
increase in measured drug consumption could have three reasons; 1) an increase in drug
322
consumption by the inhabitants, 2) an increase in persons who consume drugs in the region
323
(i.e. an increased number of visitors) or 3) a combination of the two. Therefore, researchers
324
should be careful interpreting drug consumption in a population from data corrected using
325
solid population estimates. Senta et al (Senta, Gracia-Lor, Borsotti, Zuccato, & Castiglioni,
326
2015) have been working on a method to assess fluctuating population sizes which would
327
solve this issue.
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Unfortunately, response rates to the surveys were very low and as such are a major
328
limitation to interpreting the survey data alone as well as the comparison between WBE and
330
survey data. Despite applying a number of proven techniques to improve survey response
331
such as including incentives for participation and sending out personalized missives (Cook,
332
Heath, & Thompson, 2000), only a small number of people could be motivated to participate
333
in the survey (approximately 1% of the eligible population). Our data are in agreement with
334
the national data on drug use in that the percentage of users is quite low and cannabis is the
335
most used drug. Numbers of recent drug use in Belgium in adults aged 15-64 range from
336
2.6% for cannabis (in the past 30 days) to 0.8% for any drug other than cannabis (in the past
337
year) (Scientific Institute of Public Health, 2013) and this matches our results. However, the
338
small amount of participants remains a limitation to the interpretation of the data from the
339
survey study.
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This study is the first attempt to combine WBE and survey-based epidemiology using
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the same timeline. Due to the low number of completed population surveys, the comparison
342
of wastewater data to population survey data proved to be difficult. This is a major limitation
343
to the comparison between wastewater results and population surveys in this study. A possible
344
reason for the low response rate might be that this study employed an online questionnaire.
345
However, it is unlikely that the used medium is to blame since recent studies have shown
346
online surveys to have similar response rates to paper-and-pen surveys (see (Greenlaw &
347
Brown-welty, 2009; van Gelder, Bretveld, & Roeleveld, 2010) for a review). Worldwide a
348
declining trend has been seen in the willingness of persons to participate in survey research
349
and this might also be at work here (McCluskey & Topping, 2011). Furthermore, it might be
350
possible that when inhabitants were informed of the participation of their city in the
351
wastewater study, they felt unwilling to give out more information through surveys than that
352
which was already gathered through wastewater. Concern about the use of wastewater
353
research has been reported previously (Hall et al., 2012) and, in our case, might have led to 11 Page 11 of 22
non-participation. Therefore, future studies combining wastewater and survey research should
355
be careful about exactly what to communicate to participating cities about the study to make
356
sure such bias does not occur. A way to possibly increase response rates in a future study
357
could be to embed the questions about drug use within a study on general health, where the
358
topic might become less threatening to talk about (Tourangeau & Yan, 2007). This adds the
359
advantage of personalized interviewing, which usually gathers a higher response rate.
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While it is important to combine WBE and survey research to make a good estimation
360
of their quality and accuracy, the low response rates indicate that it might be too difficult to
362
do so in a relatively small city (population ±35,000) such as the one used in this study. One
363
solution might be to perform a similar study in smaller communities such as festivals or
364
schools. However, several ethical considerations should then be considered because the
365
smaller the catchment area gets, the more difficult it is to guarantee anonymity and thus the
366
chances of adverse consequences for the inhabitants of a small community increase (Hall et
367
al., 2012; Prichard et al., 2014). Furthermore, the technology behind WBE has not progressed
368
far enough to make a reliable estimate of drug use when drug use in a sample is low and
369
populations small (Ort, Lawrence, Rieckermann, & Joss, 2010), leading to unreliable results.
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The current study also illustrates how a body of government or a research institute
370
could use WBE to make an assessment of drug use in the general population. For example,
372
from our results, it can be deduced that the opioid replacement program probably is effective
373
since no heroin could be found in the wastewater while methadone use was detected. Policy
374
makers could potentially use this information to instigate more focused prevention programs
375
or health care interventions or evaluate their current programs. Another possible use of WBE
376
could be as an evaluation tool for drug policy. This could be done by performing repeated
377
wastewater sampling, and thereby investigating whether following a policy alteration, a
378
change in drug use as reflected in the amount of DTR present in wastewater occurs.
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In conclusion, the study discussed in this paper is instrumental in providing support for
379 380
the usefulness of WBE in the estimation of illicit drug use. Declining response rates to
381
population surveys might lead to decreases in the reliability of such surveys, especially in
382
regard to sensitive topics such as drug use. The data on illicit drug consumption through
383
wastewater analysis indicate that WBE can be reliably used to confirm patterns and trends in
384
drug use. Future studies on the methodology of WBE should focus on identifying the most
385
ideal timeframes in which sampling should take place in order to use the most opportune
386
period giving the most reliable estimates of drug use. In order to carry out rigorous ecological
387
comparisons between WBE data and survey data on illicit drug use, research should focus on 12 Page 12 of 22
388
smaller, contained communities such as festivals or prisons while keeping in mind several
389
ethical considerations and methodological constrictions. This study also illustrates how WBE
390
can be used to inform policy makers about drug use in the general population.
391
Acknowledgements
393
The study is supported by funding from the European Union Seventh Framework Programme
394
for research, technological development and demonstration under grant agreement number
395
317205. AvN is thankful for the financial support from the FWO (Research Foundation
396
Flanders). All authors would like to thank the inhabitants and the council of the city of Lier
397
for their cooperation in the study. Alain Vandelannoote and the complete team of WWTP Lier
398
(Aquafin) are greatly acknowledged for their help in the sampling of wastewater samples.
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Supplementary information is available
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The
information
contains
one
figure
and
table.
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13 Page 13 of 22
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van Nuijs, A. L. N., Tarcomnicu, I., Bervoets, L., Blust, R., Jorens, P. G., Neels, H., & Covaci, A. (2009). Analysis of drugs of abuse in wastewater by hydrophilic interaction liquid chromatography-tandem mass spectrometry. Analytical and Bioanalytical Chemistry, 395(3), 819–828. http://doi.org/10.1007/s00216-009-3017-0 van Nuijs, A., Pecceu, B., Theunis, L., Dubois, N., Charlier, C., Jorens, P. G., … Covaci, A. (2009). Spatial and temporal variations in the occurrence of cocaine and benzoylecgonine in waste- and surface water from Belgium and removal during wastewater treatment. Water Research, 43(5), 1341–1349. http://doi.org/10.1016/j.watres.2008.12.020 Verheyden, S. L., Hadfield, J., Calin, T., & Curran, H. V. (2002). Sub-acute effects of MDMA (+/-3,4-methylenedioxymethamphetamine, “ecstasy”) on mood: evidence of gender differences. Psychopharmacology, 161(1), 23–31. http://doi.org/10.1007/s00213001-0995-9 Zuccato, E., Chiabrando, C., Castiglioni, S., Calamari, D., Bagnati, R., Schiarea, S., & Fanelli, R. (2005). Cocaine in surface waters: a new evidence-based tool to monitor community drug abuse. Environmental Health, 4, 11. http://doi.org/10.1186/Received
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Figure 1: Drug consumption per drug in mg/day (log10 transformed). Grey, vertical lines indicate weekends. Figure 2: Boxplots showing differences between different days of the week for A) Used MDMA (mg/day), B) Used cocaine (mg/day), C) Used amphetamine (mg/day) and D) Used
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Conflict of interest statement We wish to confirm that there are no known conflicts of interest associated with this publication and there has been no significant financial support for this work that could have influenced its outcome. We confirm that the manuscript has been read and approved by all named authors and that there are no other persons who satisfied the criteria for authorship but are not listed. We further confirm that the order of authors listed in the manuscript has been approved by all of us.
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We confirm that we have given due consideration to the protection of intellectual property associated with this work and that there are no impediments to publication, including the timing of publication, with respect to intellectual property. In so doing we confirm that we have followed the regulations of our institutions concerning intellectual property.
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We understand that the Corresponding Author is the sole contact for the Editorial process (including Editorial Manager and direct communications with the office). He/she is responsible for cmmunicating with the other authors about progress, submissions of revisions and final approval of proofs. We confirm that we have provided a current, correct email address which is accessible by the Corresponding Author and which has been configured to accept email from the International Journal of Drug Policy.
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Week Participants Average Gender Cannabis Cocaine MDMA Amphetamine (#) (#) age (yrs) (M/F) (%) (%) (%) (%) 325 43.3 119/206 1.2 0.3 0.0 0.0 1 307 42.3 114/193 1.6 1.0 0.3 0.7 2 306 42.5 113/193 1.0 0.7 0.3 0.3 3 296 41.9 110/186 2.7 0.3 0.0 0.3 4 297 42.4 97/200 1.0 0.0 0.3 0.3 5 268 42.3 91/177 0.7 0.0 0.0 0.0 6 269 42.5 91/178 1.1 0.4 0.0 0.4 7 257 43.3 98/159 1.2 0.0 0.0 0.4 8 236 43.4 90/146 2.1 0.0 0.0 0.0 9 87 41.5 34/53 0.0 0.0 0.0 0.0 10 273 43 102/171 1.5 0.4 0.4 0.7 11 251 43.7 88/163 1.2 0.0 0.0 0.4 12 253 44 94/159 1.2 0.8 0.4 0.0 13 263 42.8 95/168 1.3 0.3 0.1 0.3 Average
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Table 1: Percentage of participants indicating past week drug use (by answering ‘yes’ on the
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Highlights (for review)
Highlights
Confirmation of week vs weekends pattern of use for party drugs ecstasy, cocaine, amphetamine
Ordering of drugs according to use; amphetamine (1), cocaine (2), cannabis (3), MDMA (4), methadone (6), ketamine (7 (=absent)) matches national and international survey data Large regional events can be picked up retrospectively in wastewater data.
Meaningful correlations between survey and wastewater results difficult since the
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number of survey responses was very low
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