Use of illicit stimulant drugs in Finland: a wastewater study in ten major cities.

Estimations of drug use at the national level are generally based on various sources of information, such as drug seizures, socio-scientific studies, toxicological data and hospital records. Nevertheless, all of these approaches have limitations that cannot be overcome, even if conclusions are drawn from combined data retrieved from different sources. Drug epidemiology through wastewater analysis has the potential to provide unique perspectives, internationally comparable data, and up-to-date information on the use of both traditional illicit drugs and new psychoactive substances (NPSs). In Finland, no large-scale studies on regional illicit drug consumption, based on a wastewater approach, have been reported. In this study, 24-h influent composite samples were collected during two 1-week study periods from ten different wastewater treatment plants in May and November-December 2012. The cities included in the study represent the geographical areas throughout Finland and cover 40% of the Finnish population. The samples were analyzed with an in-house validated, ultra high-performance liquid-chromatography mass spectrometric (UHPLC-MS/MS) method for various common illicit drugs and some NPS type stimulant drugs. The results were also compared with available statistics, information on drug seizures and laboratory-confirmed toxicological data, as well as other studies available based on wastewater analysis. The data show that illicit stimulant drug use is more common in the larger cities of Southern Finland. Amphetamine was the most commonly used drug in all 10 cities during both collection periods (excluding the collection period in May in Lappeenranta). Cocaine consumption remains very low in Finland in comparison to other European countries; it was concentrated in the biggest cities in Southern Finland. This study shows interesting temporal and spatial differences in drug use in Finland, as well as the possibilities of using wastewater analytics to reveal local hotspots of NPS consumption.