Full length articleAssessing geographical differences in illicit drug consumption—A comparison of results from epidemiological and wastewater data in Germany and Switzerland
Introduction
The consumption of illicit drugs in a given population or community remains a partially hidden activity that cannot be directly measured nor totally unveiled. Traditionally, the nature, versatility and extent of this phenomenon are assessed through the use of indicators such as consumption surveys or descriptive statistics. The last decade has seen the emergence and refinement of wastewater-based epidemiology (WBE), which relies on quantitative measurement of specific biomarkers of illicit drug use in wastewater. Presented as a complementary approach to current surveillance methods (Amundsen and Reid, 2014, Been et al., 2015, Bramness et al., 2014, Reid et al., 2012, Reid et al., 2011), WBE has received much attention. Although further developments will most probably refine it in the near future, WBE already enables the gathering of unique spatio-temporal information about consumption (Ort et al., 2014). Nevertheless, information about consumers (e.g. age, sex, socio-economical status and history of drug use), crucial for policy makers, cannot be gathered by this approach, but requires the use of classical monitoring tools. Yet, these are also affected by some limitations such as the difficulty to obtain representative estimates, long study times, high costs and difficulties in reaching specific groups of regular users (Banta-Green and Field, 2011, Ort et al., 2014).
In general, estimating and monitoring drug use relies on direct and indirect methods (European Monitoring Centre for Drugs and Drug Addiction; EMCDDA, 2015a). The former are mainly based on general population surveys (GPS), where a representative sample of the population is questioned about illicit drug use. The latter rely on extrapolating information about drug use from other sources indirectly related to drug use such as police statistics, treatment data as well as WBE. Despite suffering from the abovementioned limitations, these methods provide a partial, yet informative perspective of the phenomenon. By bringing together different and complementary data sources, it is expected to obtain a more precise understanding of the dynamics of illicit drug use at the national level.
In this study, samples collected from different wastewater treatment plants (WWTP) in Germany and Switzerland (including Liechtenstein) were analysed. Estimates of the average daily consumption of illicit drugs were computed based on these measurements and pharmacokinetics data available in the literature. Results obtained from wastewater analysis were compared to data derived from GPS and consumption offences registered by police forces. The aim of this study was to evaluate geographical differences and formulate hypotheses explaining divergences in the data sets. The cities investigated in the context of this study are shown in Fig. 1. Focus was set on the use of cocaine, cannabis, heroin, amphetamine, methamphetamine, and 3,4-methylene-dioxymethamphetamine (MDMA or ecstasy).
Section snippets
Epidemiological data and police statistics
General population survey data included the reported prevalence of use during the 12-months prior to questioning with a focus on the investigated areas (see Fig. 1 and Table 1; Kraus et al., 2015, Kraus et al., 2014, Kraus et al., 2010a, Kraus et al., 2010b, Kraus et al., 2001; Social and Market Research Institute and Addiction Suisse, 2015). Reported substances were: cocaine, cannabis, amphetamine and amphetamine-type stimulants (ATS)—such as methamphetamine and MDMA (for Germany only) and
Population surveys
Estimates of last-year prevalence of cocaine, cannabis and ATS in the investigated cities are shown in Fig. 2, Fig. 3 and Table 4.
The highest prevalence for cocaine (2.8%) was measured for Berlin, with much lower levels in the other Federal States (0.4–0.8%). In Switzerland, Lausanne was highest (2.3%), followed by Lucerne (1.2), Geneva (1.0%), Zurich (0.9%) and Winterthur (0.9%). For cannabis, the highest prevalence in Germany were reported for Berlin (11%) and Dortmund/Dülmen (7.3%), with
Cocaine
In Germany, the overlap observed between prevalence, offences and wastewater data suggests that cocaine consumption is predominant in the cities of Dortmund and Berlin, although lower prevalence was reported in Dortmund. This difference, however, may be due to methodological differences between survey estimates in Dortmund (and other German cities) and capture/recapture estimates as applied in Berlin. Firstly, capture/recapture methods are less likely to produce underestimates, and secondly,
Conclusion
Because illicit drug consumption is a complex phenomenon, the indicators considered in this study can only provide a partial perspective of the phenomenon and all suffer from limitations and uncertainties. Survey data may be biased by differential responses due to stigmatisation and hidden behaviours, which are particularly pronounced for heroin and cocaine, whereas cannabis and other stimulants might be less affected. Offence data are obviously biased by law enforcement activities and
Role of funding source
Nothing to declare.
Contributors
CO and FB planned and designed the study with contributions from LBi, FZ, MPS, AB, FH, OD and PE. CO, FB and LBi organised the collection of the wastewater samples which were analysed by FB, LBi, LBe, JDB, AMBC and SC. FB, LK and FZ retrieved the epidemiological data used in the study. FB performed data analysis and interpreted the results with substantial contribution from all co-authors. FB, with contributions from LBi, drafted the manuscript, which was critically revised by all co-authors.
Conflict of interest
No conflict declared.
Acknowledgements
The authors would like to thank the personnel of the wastewater treatment plants for their collaboration in providing the samples. The authors would like to thank Philippe Hayot, from the Swiss Federal Statistical Office, and Gerhard Gmel and Luca Notari, from Addiction Suisse, for providing drug-related statistics. The University Jaume I acknowledges the financial support from Generalitat Valenciana (Group of Excellence Prometeo II 2014/023); ISIC 2012/16 and from the Spanish Ministry of
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