Integrating environmental and self-report data to refine cannabis prevalence estimates in a major urban area of Switzerland (2016)

Background: Cannabis consumption is a topical subject because of discussions about reviewing current regulations. In this context, having a more comprehensive approach to assess and monitor prevalence and consumption is highly relevant. The objective of this work was to refine current estimates about prevalence of cannabis use by combining self-report data and results derived from wastewater analysis.
Methods Self-report data was retrieved from surveys conducted in Switzerland and Europe. Wastewater samples were collected at the wastewater treatment plant of Lausanne, western Switzerland, over a 15 months period. The occurrence of 11-nor-9-carboxy-delta-9-tetrahydrocannabinol (THC-COOH), a specific metabolite of delta-9-tetrahydrocannabinol (THC), was monitored. Bayesian hierarchical models were used to estimate consumption, prevalence and number of cannabis users in the investigated area.
Results: According to survey data, 12-months prevalence in western Switzerland was estimated to 6.2% of the population aged 15 or older, with an estimated daily cannabis consumption of 8.1 g day^-1.1000 inhab^-1 (at 11.2% purity). The integrative model comprising self-report and wastewater data substantially reduced the uncertainty in the estimates and suggested a last-year prevalence of 9.4%, with a daily cannabis consumption of 14.0 g day^-1.1000 inhab^-1.
Conclusion: Although in the same order of magnitude, consumption and prevalence estimates obtained with the integrative model were 78% and 52% higher compared to self-report figures, respectively. Interestingly, these figures are similar to discrepancies observed when comparing self-reported alcohol consumption and sales or tax data. The suggested integrative model allowed to account for known sources of uncertainty and provided refined estimates of cannabis prevalence in a major urban area of Switzerland.