Structured information is now available on patterns and trends in drug consumption in Europe, which permits triangulation of data from different sources and consideration of methodological limitations. Opioid drugs continue to place a burden on the drug treatment system, although both new heroin entrants and injecting show declines. More than 450 new psychoactive substances are now monitored by the European early warning system with 31 new synthetic cathinones and 30 new synthetic cannabinoid receptor agonists notified in 2014.

The most recent data provided by European countries are presented, including data on drug use, drug‐related morbidity and mortality, treatment demand, drug markets and new psychoactive substances, with data tables provided and methodological information. A number of key results are highlighted for illustrative purposes. Drug prevalence estimates from national surveys since 2012 (last year prevalence of use among the 15–34 age band) range from 0.4% in Turkey to 22.1% in France for cannabis, from 0.2% in Greece and Romania to 4.2% in the United Kingdom for cocaine, from 0.1% in Italy and Turkey to 3% in the Czech Republic and the United Kingdom for ecstasy, and from 0.1% or less in Romania, Italy and Portugal to 2.5% in Estonia for amphetamine. Declining trends in new HIV detections among people who inject drugs are illustrated, in addition to presentation of a breakdown of NPS reported to the EU early warning system, which have risen exponentially from fewer than 20 a year between 2005 and 2008, to 101 reported in 2014.

The European reporting system formally covers all 28 European Union (EU) Member States, Norway and Turkey and incorporates multiple indicators alongside an early warning system (EWS) on uncontrolled new psychoactive substances (NPS). While epidemiological information is based largely on registries, surveys and other routine data reported annually, the EWS collects case‐based data on an ongoing basis. The 2015 reporting exercise is centred primarily on a set of standardized reporting tools.

A central task for the European Monitoring Centre for Drugs and Drug Addiction (EMCDDA) is to produce an annual report of the latest data available on drug demand and drug supply in Europe. This paper is intended to facilitate a better understanding of, and easier access to, the main quantitative European level data sets available in 2015.

Introduction The European Monitoring Centre for Drugs and Drug Addiction (EMCDDA) was established to provide a technical reference point for collating and disseminating information on the European drug situation. Details on the role and activities of the agency can be found in Griffiths et al. 1. A central task for the agency is to produce an annual report of the latest data available on drug use in Europe. This reporting exercise is primarily based on a set of standardized reporting tools, which have been refined during the 20 years in which the system has been operational. Here an overview of the information available in 2015, together with links to data tables and methodological details, is provided. Some illustrative results from the most recent reporting exercise are also included (Tables 1 and 2, Fig. 1 and 2). It is not, however, the purpose of this paper to provide an analysis of the European drug situation, which can be found in the EMCDDA European Drug Report: Trends and Developments 2. Table 1. Subset of national data available in the European Monitoring Centre for Drugs and Drug Addiction (EMCDDA) 2015 data collection. Opioids Problem opioid use estimate Treatment demand indicator, primary drug Clients in substitution treatment Opioids clients as % of treatment demands % opioids clients injecting (main route of administration) All entrants First‐time entrants Previously treated entrants All entrants First‐time entrants Previously treated entrants Country Cases per 1000 % (count) % (count) % (count) % (count) % (count) % (count) Count Belgium – 30.8 (2816) 13 (416) 39 (2024) 20.1 (547) 14.1 (57) 21.5 (420) 17 482 Bulgaria – 88.8 (1744) 79.3 (211) 95.2 (954) 73.8 (876) 68.8 (141) 74.4 (585) 3563 Czech Republic 1.5–1.5 17.2 (1681) 7.8 (362) 25.6 (1319) 89.4 (1493) 86.9 (312) 90.1 (1 181) 3500 Denmark – 17.5 (663) 7.1 (102) 26.3 (502) 33.9 (193) 23 (20) – 7600 Germany 2.8–3.4 37.1 (29 891) 13.7 (3217) – – – – 77 300 Estonia – 92.9 (403) 81 (102) 98.6 (284) 84.8 (339) 90.2 (92) 83 (235) 1166 Ireland – 51.3 (4451) 29.7 (1032) 66.8 (3291) 41.3 (1762) 33.7 (344) 43.6 (1362) 9640 Greece 2.0–2.6 69.3 (3367) 54.9 (1145) 80 (2194) 36.8 (1227) 32.8 (372) 39.1 (850) 9973 Spain 1.7–2.6 26.8 (13 333) 11.4 (2866) 43.7 (10 050) 17.8 (2195) 11 (295) 19.6 (1859) 69 111 France – 43.1 (15 641) 27.1 (2690) 53.5 (11 275) 14.2 (1836) 6.8 (172) – 163 000 Croatia 3.2–4.0 80.4 (6315) 24 (270) 90 (5992) 73.7 (4581) 42.6 (104) 75.1 (4446) 6357 Italy 3.8–4.9 54.7 (18 072) 37.2 (4782) 65.7 (13 290) 57 (9678) 44.4 (1906) 61.3 (7772) 94 376 Cyprus 1.2–2.1 26.5 (270) 7.7 (37) 43.8 (232) 48.1 (126) 40 (14) 49.3 (112) 180 Latvia 4.1–9.7 52.1 (783) 19.7 (104) 69.6 (679) 63.7 (495) 84.6 (88) 60.5 (407) 328 Lithuania 2.3–2.4 86.8 (1918) 62.8 (214) 91.9 (1 671) – 100 (140) – 592 Luxembourg 5.0–7.6 50.2 (145) 42.1 (8) 49.8 (116) 48.2 (68) 28.6 (2) 47 (54) 1254 Hungary 0.4–0.5 5.9 (236) 2.1 (54) 13.6 (160) 70.1 (157) 60.4 (32) 71.8 (112) 786 Malta 6.5–7.7 74.8 (1352) 33.7 (67) 79.9 (1285) 61.8 (816) 54.2 (32) 62.2 (784) 1078 Netherlands 1.1–1.5 10.2 (1195) 5.1 (343) 17 (852) 4.6 (51) 5.4 (16) 4.3 (35) 8185 Austria 4.9–5.1 52 (1537) 29.5 (361) 67.9 (1176) 43.4 (536) 31.1 (100) 47.8 (436) 16 989 Poland 0.4–0.7 26.4 (724) 8.2 (91) 39.3 (621) 58 (391) 43.4 (36) 60.3 (349) 1725 Portugal – 54.3 (1634) 27.3 (380) 77.6 (1254) 15.9 (238) 11.2 (38) 17.3 (200) 24 027 Romania – 48.8 (802) 33.6 (240) 63.3 (543) 84.5 (622) 84.8 (189) 84.8 (420) 387 Slovenia 4.3–5.8 81.5 (234) 60.6 (57) 91.7 (176) 48.7 (113) 36.8 (21) 52.3 (91) 4065 Slovakia 1.0–2.5 24.7 (558) 16 (185) 34.1 (363) 66.8 (367) 48.4 (89) 76.4 (272) 408 Finland 3.8–4.5 64.2 (706) 40.4 (65) 69.2 (619) 81.6 (567) 73 (46) 82.5 (504) 2439 Sweden – 27.3 (7760) 17.2 (2211) 35.7 (5549) 59.6 (140) 33.3 (11) 63.9 (129) 3425 United Kingdom 7.9–8.4 50.3 (49 871) 19.7 (6813) 66.6 (42 636) 34.5 (16 871) 22.5 (1484) 36.3 (15 191) 172 513 Turkey 0.2–0.5 76.3 (5542) 68 (2540) 85.1 (3002) 39.7 (2201) 29.3 (745) 48.5 (1456) 28 656 Norway 1.9–3.1 26.9 (2 266) – – – – – 7055 European Union – 41 (168 102) 18.7 (28 425) 57.1 (109 107) 38.2 (46 285) 28.4 (6153) 43.3 (37 806) 701 449 EU, Turkey and Norway – 41.3 (175 910) 19.9 (30 965) 57.6 (112 109) 38.3 (48 486) 28.5 (6898) 43.5 (39 262) 737 160 Year and method of estimate for problem opioid use vary between countries. The treatment demand indicator monitors entrants into treatment within a given year. Cocaine Prevalence estimates Treatment demand indicator, primary drug General population School population Cocaine clients as % of treatment demands % cocaine clients injecting (main route of administration) Life‐time, adults (15–64) Last 12 month, young adults (15–34) Life‐time, students (15–16) All entrants First‐time entrants Previously treated entrants All entrants First‐time entrants Previously treated entrants Country % % % % (count) % (count) % (count) % (count) % (count) % (count) Belgium – 2.0 2 15.6 (1430) 15.2 (488) 15.9 (825) 6 (83) 1.3 (6) 7.1 (57) Bulgaria 0.9 0.3 4 0 (0) 2.6 (7) 0.3 (3) 0 (0) 0 (0) 0 (0) Czech Republic 0.4 0.3 1 0.2 (19) 0.3 (12) 0.1 (7) 11.1 (2) 16.7 (2) 0 (0) Denmark 5.2 2.4 2 5.1 (193) 5.8 (84) 5.2 (99) 10.1 (17) 0 (0) – Germany 3.4 1.6 3 5.9 (4788) 5.6 (1322) – – – – Estonia – 1.3 2 0 (0) 0 (0) 0 (0) – – – Ireland 6.8 2.8 3 7.8 (680) 9.2 (320) 6.6 (324) 1.7 (11) 0.3 (1) 2.9 (9) Greece 0.7 0.2 1 5.1 (250) 5.9 (122) 4.6 (127) 19.8 (49) 12.4 (15) 27 (34) Spain 10.3 3.3 3 39.2 (19 497) 40.2 (10 142) 38.5 (8855) 2 (365) 1 (95) 3 (260) France 5.4 2.3 4 6.4 (2311) 4.1 (411) 7.5 (1573) 9.9 (192) 4.1 (16) – Croatia 2.3 0.9 2 1.5 (119) 2.6 (29) 1.3 (84) 0.9 (1) 0 (0) 1.2 (1) Italy 4.2 1.3 1 25.8 (8529) 31.4 (4037) 22.2 (4492) 3.5 (289) 2.9 (114) 4 (175) Cyprus 1.3 0.6 4 12.2 (124) 9.3 (45) 14.7 (78) 5.8 (7) 0 (0) 9.3 (7) Latvia 1.5 0.3 4 0.3 (5) 0.8 (4) 0.1 (1) 0 (0) 0 (0) 0 (0) Lithuania 0.9 0.3 2 0.6 (14) 1.8 (6) 0.3 (5) – – – Luxembourg – – – 17.3 (50) 10.5 (2) 18 (42) 39.1 (18) – 39 (16) Hungary 0.9 0.4 2 2 (81) 2.4 (60) 1.4 (17) 8.9 (7) 8.3 (5) 5.9 (1) Malta 0.5 – 4 14.4 (260) 32.2 (64) 12.2 (196) 25.6 (65) 11.3 (7) 30.2 (58) Netherlands 5.2 2.4 2 26.5 (3113) 22.2 (1494) 32.3 (1619) 0.3 (8) 0.3 (4) 0.3 (4) Austria 2.2 1.2 – 10.2 (301) 11.8 (145) 9 (156) 7.6 (18) 2.7 (3) 12.2 (15) Poland 0.9 0.3 3 2.4 (67) 1.9 (21) 2.8 (44) 6.3 (4) 4.8 (1) 7.3 (3) Portugal 1.2 0.4 4 12.9 (388) 17.2 (239) 9.2 (149) 4.1 (14) 1.9 (4) 7.7 (10) Romania 0.3 0.2 2 0.7 (11) 1.3 (9) 0.2 (2) – – – Slovenia 2.1 1.2 3 3.5 (10) 6.4 (6) 2.1 (4) 30 (3) 16.7 (1) 50 (2) Slovakia 0.6 0.4 1 0.6 (13) 0.4 (5) 0.8 (8) 8.3 (1) 0 (0) 14.3 (1) Finland 1.7 0.6 1 0.1 (1) 0 (0) 0 (0) 100 (1) – – Sweden – 1.2 1 0.8 (236) 1.2 (151) 0.5 (85) 6.3 (2) 0 (0) 18.2 (2) United Kingdom 9.5 4.2 2 12.9 (12 756) 17.1 (5888) 10.7 (6851) 1.7 (204) 0.5 (29) 2.6 (175) Turkey – – – 1.1 (81) 1.1 (41) 1.1 (40) 0 (0) 0 (0) 0 (0) Norway 4.2 2.2 1 0.9 (79) – – – – – European Union 4.6 1.9 – 13.5 (55 246) 16.5 (25 113) 13.4 (25 646) 2.8 (1361) 1.3 (303) 3.6 (830) EU, Turkey and Norway – – – 13 (55 406) 16.2 (25 154) 13.2 (25 686) 2.8 (1361) 1.3 (303) 3.6 (830) Prevalence estimates for the general population are derived from representative national surveys. The year and method of survey varies by country. Prevalence estimates for the school population are taken from national school surveys or the ESPAD project. Amphetamines Prevalence estimates Treatment demand indicator, primary drug General population School population Amphetamines clients as % of treatment demands % amphetamines clients injecting (main route of administration) Life‐time, adults (15–64) Last 12 month, young adults (15–34) Life‐time, students (15–16) All entrants First‐time entrants Previously treated entrants All entrants First‐time entrants Previously treated entrants Country % % % % (count) % (count) % (count) % (count) % (count) % (count) Belgium – – 2 10.1 (925) 9.1 (292) 11 (574) 13.3 (118) 5.3 (15) 17.7 (97) Bulgaria 1.2 1.3 5 4.7 (93) 10.9 (29) 1.8 (18) 0 (0) 0 (0) 0 (0) Czech Republic 1.1 0.7 2 70.3 (6865) 74.2 (3431) 66.7 (3434) 78.6 (5365) 72.6 (2473) 84.5 (2892) Denmark 6.6 1.4 2 9.5 (358) 10.3 (149) 8.9 (170) 3.1 (9) 0 (0) – Germany 3.1 1.8 4 14.9 (12 026) 18.7 (4365) – – – – Estonia – 2.5 3 3 (13) 5.6 (7) 1.4 (4) 76.9 (10) 57.1 (4) 100 (4) Ireland 4.5 0.8 2 0.6 (52) 0.9 (32) 0.4 (18) 5.9 (3) 9.7 (3) 0 (0) Greece 0.1 0.1 2 0.2 (12) 0.3 (7) 0.2 (5) 0 (0) 0 (0) 0 (0) Spain 3.8 1.2 2 1 (512) 1.2 (307) 0.8 (186) 0.6 (3) 0.7 (2) 0.6 (1) France 2.2 0.7 4 0.3 (98) 0.2 (22) 0.3 (60) 22.5 (18) 15.8 (3) – Croatia 2.6 1.6 1 0.9 (69) 2 (22) 0.7 (46) 0 (0) 0 (0) 0 (0) Italy 1.8 0.1 1 0.2 (51) 0.3 (37) 0.1 (14) 2 (1) 2.9 (1) 0 (0) Cyprus 0.7 0.4 4 2.6 (26) 1.7 (8) 3.4 (18) 7.7 (2) 0 (0) 11.1 (2) Latvia 2.2 0.6 4 15.1 (227) 21 (111) 11.9 (116) 68.2 (152) 64.2 (70) 71.9 (82) Lithuania 1.2 0.5 3 3.4 (76) 10 (34) 1.9 (34) – – – Luxembourg – – – 0 (0) 0 (0) 0 (0) – – – Hungary 1.8 1.2 6 11.6 (461) 11.6 (297) 11 (130) 15.3 (68) 11.3 (33) 24.2 (30) Malta 0.3 – 3 0.2 (4) 0 (0) 0.2 (4) 25 (1) – 25 (1) Netherlands 3.1 – 1 6.5 (760) 6.6 (445) 6.3 (315) 0.6 (4) 0.5 (2) 0.7 (2) Austria 2.5 0.9 – 3.4 (102) 4.7 (58) 2.5 (44) 1.2 (1) 2 (1) 0 (0) Poland 2.9 1.4 4 25.9 (711) 25.8 (287) 26.5 (419) 10.8 (76) 3.9 (11) 15.7 (65) Portugal 0.5 0.1 3 0.1 (2) 0.1 (1) 0.1 (1) 0 (0) 0 (0) – Romania 0.1 0.0 2 0.5 (8) 1 (7) 0 (0) – – – Slovenia 0.9 0.8 2 0.7 (2) 1.1 (1) 0.5 (1) – – – Slovakia 0.5 0.3 1 43.2 (978) 46.4 (535) 39.9 (425) 31.8 (300) 27.1 (142) 38 (154) Finland 2.3 1.6 – 11 (121) 11.8 (19) 10.8 (97) 76.7 (89) 52.6 (10) 81.9 (77) Sweden – 1.3 0 0.4 (112) 0 (6) 0.7 (105) 78.3 (83) 80 (4) 78 (78) United Kingdom 11.1 1.5 1 2.7 (2725) 3.1 (1058) 2.6 (1656) 24 (607) 13 (125) 31.1 (482) Turkey 0.1 0.1 2 0 (0) 0 (0) 0 (0) – – – Norway 3.7 1.1 1 13.1 (1 104) – – – – – European Union 3.5 1.0 – 6.7 (27 389) 7.6 (11 567) 4.1 (7894) 47 (6910) 41.9 (2899) 53.6 (3967) EU, Turkey and Norway – – – 6.7 (28 493) 7.4 (11 567) 4.1 (7894) 47 (6910) 41.9 (2899) 53.6 (3967) Ecstasy Prevalence estimates Treatment demand indicator, primary drug General population School population Ecstasy clients as % of treatment demands Life‐time, adult (15–64) Last 12 month, young adult (15–34) Life‐time, students (15–16) All entrants First‐time entrants Previously treated entrants Country % % % % (count) % (count) Belgium – – 2 0.5 (43) 0.7 (23) 0.4 (19) Bulgaria 2.0 2.9 4 0.1 (1) 0 (0) 0.1 (1) Czech Republic 5.1 3.0 3 0.1 (8) 0.1 (4) 0.1 (4) Denmark 2.3 0.7 1 0.3 (13) 0.5 (7) 0.3 (5) Germany 2.7 0.9 2 – – – Estonia – 2.3 3 0 (0) 0 (0) 0 (0) Ireland 6.9 0.9 2 0.5 (43) 0.8 (27) 0.3 (16) Greece 0.4 0.4 2 0.2 (8) 0.2 (5) 0.1 (3) Spain 4.3 1.5 2 0.3 (134) 0.4 (103) 0.1 (29) France 4.2 2.3 3 0.5 (186) 0.2 (22) 0.6 (122) Croatia 2.5 0.5 2 0.3 (27) 0.6 (7) 0.3 (19) Italy 1.8 0.1 1 0.2 (55) 0.2 (23) 0.2 (32) Cyprus 0.9 0.3 3 0.1 (1) 0 (0) 0.2 (1) Latvia 2.7 0.8 4 0.2 (3) 0.4 (2) 0.1 (1) Lithuania 1.3 0.3 2 0 (1) 0 (0) 0.1 (1) Luxembourg – – – 0.3 (1) 0 (0) 0.4 (1) Hungary 2.4 1.0 4 1.7 (69) 1.7 (43) 2 (23) Malta 0.7 – 3 1.2 (22) 3.5 (7) 0.9 (15) Netherlands 6.2 3.1 4 0.6 (67) 0.8 (55) 0.2 (12) Austria 2.3 1.0 – 0.8 (23) 1.1 (13) 0.6 (10) Poland 1.1 0.3 2 0.2 (6) 0.1 (1) 0.3 (5) Portugal 1.3 0.6 3 0.2 (5) 0.4 (5) 0 (0) Romania 0.7 0.4 2 0.1 (1) 0.1 (1) 0 (0) Slovenia 2.1 0.8 2 0 (0) 0 (0) 0 (0) Slovakia 1.9 0.9 0 0.1 (2) 0.1 (1) 0.1 (1) Finland 1.8 1.1 2 0.3 (3) 0.6 (1) 0.2 (2) Sweden – 1.0 1 0 (3) 0 (1) 0 (1) United Kingdom 9.3 3.0 2 0.3 (325) 0.7 (232) 0.1 (92) Turkey 0.1 0.1 2 0.8 (55) 1.1 (41) 0.4 (14) Norway 2.3 1.0 1 0 (0) – – European Union 3.6 1.4 – 0.3 (1050) 0.4 (583) 0.2 (415) EU, Turkey and Norway – – – 0.3 (1105) 0.4 (624) 0.2 (429) Cannabis Prevalence estimates Treatment demand indicator, primary drug General population School population Cannabis clients as % of treatment demands Life‐time, adults (15–64) Last 12 months, young adults (15–34) Life‐time, students (15–16) All entrants First‐time entrants Previously treated entrants Country % % % % (count) % (count) % (count) Belgium 14.3 11.2 21 33.6 (3077) 54.3 (1744) 23.1 (1201) Bulgaria 7.5 8.3 22 3.9 (77) 4.5 (12) 1.8 (18) Czech Republic 22.8 21.6 42 11 (1077) 16.5 (763) 6.1 (314) Denmark 35.6 17.6 18 63.4 (2397) 72.6 (1048) 55.5 (1061) Germany 23.1 11.1 19 36.3 (29 252) 56.1 (13 138) – Estonia – 13.6 24 3.7 (16) 12.7 (16) 0 (0) Ireland 25.3 10.3 18 28.9 (2511) 47 (1631) 16 (790) Greece 8.9 3.2 8 21.5 (1045) 35.4 (737) 11 (302) Spain 30.4 17.0 28 29.9 (14 869) 43.6 (10 982) 14.8 (3402) France 40.9 22.1 39 44.1 (16 020) 62.5 (6 206) 32.3 (6804) Croatia 15.6 10.5 18 13.3 (1047) 58.4 (658) 5.7 (381) Italy 21.7 8.0 16 17.4 (5766) 28 (3 593) 10.7 (2173) Cyprus 9.9 4.2 7 56.8 (579) 80.5 (388) 35.3 (187) Latvia 12.5 7.3 24 27.3 (411) 51.4 (272) 14.3 (139) Lithuania 10.5 5.1 20 2.9 (65) 11.7 (40) 1.3 (23) Luxembourg – – – 31.1 (90) 47.4 (9) 30.5 (71) Hungary 8.5 5.7 19 61 (2429) 70 (1787) 43.4 (511) Malta 4.3 – 10 7.9 (142) 25.1 (50) 5.7 (92) Netherlands 25.7 13.7 27 47.8 (5613) 56.7 (3826) 35.7 (1787) Austria 14.2 6.6 14 30 (887) 50.6 (620) 15.4 (267) Poland 12.2 8.1 23 33.4 (914) 51.6 (575) 20.3 (321) Portugal 9.4 5.1 16 26.8 (806) 48.4 (674) 8.2 (132) Romania 1.6 0.6 7 17 (279) 27.3 (195) 7.9 (68) Slovenia 15.8 10.3 23 12.5 (36) 31.9 (30) 3.1 (6) Slovakia 10.5 7.3 16 24.6 (557) 32 (369) 16.6 (177) Finland 18.3 11.2 12 14.6 (161) 34.2 (55) 10.8 (97) Sweden – 7.1 5 13.2 (3763) 22.4 (2881) 5.7 (882) United Kingdom 29.9 11.2 22 26.8 (26 618) 48.6 (16 775) 15.3 (9771) Turkey 0.7 0.4 4 12.7 (920) 17.5 (653) 7.6 (267) Norway 23.3 12.0 5 20.3 (1705) – – European Union 23.3 11.7 – 29.4 (120 504) 45.5 (69 074) 16.2 (30 977) EU, Turkey and Norway – – – 28.9 (123 129) 44.8 (69 727) 16.1 (31 244) Other indicators Drug‐induced death (aged 15–64) HIV diagnoses attributed to injecting drug users (ECDC) Injecting drug use estimate Syringes distributed through specialized programmes Country Cases per million population (count) Cases per million population (count) Cases per 1 000 population Count Belgium 10.5 (77) 1.5 (17) 2.5–4.8 907 504 Bulgaria 4.3 (21) 4.5 (33) – 431 568 Czech Republic 5.1 (37) 0.6 (6) 5.9–6.0 6 181 134 Denmark 60 (218) 2.3 (13) – – Germany 17.6 (956) 1.2 (100) – – Estonia 126.8 (111) 54.5 (72) 4.3–10.8 2 183 933 Ireland 58.5 (177) 3.9 (18) – 360 041 Greece – 22.4 (248) 0.6–0.9 429 517 Spain 12.2 (383) 3.1 (145) 0.3–0.4 2 684 251 France 6.8 (283) 1 (67) – – Croatia 16.8 (48) 0 (0) 0.3–0.6 273 972 Italy 8.9 (343) 2.7 (162) – – Cyprus 4.9 (3) 0 (0) 0.2–0.5 0 Latvia 8.1 (11) 38 (77) 7.3–11.7 341 421 Lithuania 27.1 (54) 20.9 (62) – 168 943 Luxembourg 29.7 (11) 9.3 (5) 4.5–6.9 191 983 Hungary 4.6 (31) 0.1 (1) 0.8 435 817 Malta 10.4 (3) 7.1 (3) – 357 691 Netherlands 10.2 (113) 0.3 (5) 0.2–0.2 – Austria 24.2 (138) 2.5 (21) – 4 762 999 Poland 7.6 (207) 1 (39) – – Portugal 3.0 (21) 7.4 (78) – 950 652 Romania 2.2 (30) 7.4 (149) – 2 051 770 Slovenia 19.9 (28) 1 (2) – 513 272 Slovakia 6.5 (25) 0 (0) – 321 339 Finland 54.3 (191) 0.6 (3) 4.1–6.7 3 834 262 Sweden 69.7 (426) 0.8 (8) – 229 362 United Kingdom 44.6 (1 858) 1.8 (112) 2.9–3.2 9 457 256a Turkey 4.4 (224) 0.1 (4) – – Norway 69.6 (232) 1.6 (8) 2.2–3.0 3 011 000 European Union 17.3 (5804) 2.9 (1446) – – EU, Turkey and Norway 16 (6260) 2.5 (1458) – – Injecting drug use estimates are derived by indirect methods, with year of estimate varying between countries. aData refer to Scotland and Wales (2013) and Northern Ireland (2012). Seizures Heroin Cocaine Amphetamines Ecstasy Quantity seized Number of seizures Quantity seized Number of seizures Quantity seized Number of seizures Quantity seized Number of seizures Country kg Count kg Count kg Count Tablets (kg) Count Belgium 1182 2431 6486 3653 216 3085 37 152 (–) 1338 Bulgaria 157 32 20 – 193 8 4169 (29) – Czech Republic 5 38 36 106 70 495 5061 (0.04) 114 Denmark 14 461 681 2286 341 2167 7706 (–) 590 Germany 270 3065 1315 3622 1339 12 801 480 839 (–) 2233 Estonia 0 2 2 47 28 290 3341 (0.2) 92 Ireland 61 690 66 366 23 114 465 083 (–) 464 Greece 235 2158 706 437 16 81 34 579 (0.4) 47 Spain 291 6502 26 701 38 033 497 3471 154 732 (–) 2301 France 570 – 5612 – 501 – 414 800 (–) – Croatia 10 167 9 171 13 414 0 (0.9) 170 Italy 882 2560 4966 6031 103 128 4713 (17) 136 Cyprus 0.7 16 3 105 1 38 504 (0.1) 14 Latvia 0.7 288 1 34 46 744 60 (0.003) 18 Lithuania 13 100 3 12 71 97 54 (0.5) 13 Luxembourg 4 127 1 103 5 6 13 (–) 3 Hungary 6 32 8 117 75 586 17 664 (2) 181 Malta 1 51 4 115 0 3 30 375 (–) 45 Netherlandsa 750 – 10 000 – 681 – – – Austria 80 346 25 992 29 859 5768 (–) 119 Poland 49 – 21 – 685 – 45 997 (–) – Portugal 55 792 2440 1108 5 48 2160 (1) 80 Romania 112 273 53 75 0 42 27 506 (0.04) 142 Slovenia 7 339 3 196 16 273 922 (0.9) 53 Slovakia 0.2 73 1 23 4 634 47 (–) 17 Finland 0.2 113 5 205 91 3 149 121 600 (–) 795 Sweden 6 485 81 1452 677 4 541 26 919 (16) 743 United Kingdoma 831 10 648 3324 18 569 1491 6515 1 173 100 (–) 3716 Turkey 13 480 6096 450 863 1242 132 4 441 217 (–) 4274 Norway 55 1192 188 1086 514 7229 7298 (3) 411 European Union 5593 31 789 62 573 77 858 7217 40 589 3 064 864 (68) 13 424 EU, Turkey and Norway 19 128 39 077 63 211 79 807 8973 47 950 7 513 379 (71) 18 109 Amphetamines includes amphetamine and methamphetamine. aSeizures data refer to 2012. Seizures (continued) Cannabis resin Herbal cannabis Cannabis plants Quantity seized Number of seizures Quantity seized Number of seizures Quantity seized Number of seizures Country kg Count kg Count Plants (kg) Count Belgium 4275 5529 14 882 23 900 396 758 (–) 1212 Bulgaria 5 9 579 69 18 126 (24) 11 Czech Republic 1 28 735 875 73 639 (–) 361 Denmark 3292 11 030 394 1896 – (5634) 645 Germany 1770 5638 4827 28 875 107 766 (–) 2026 Estonia 109 24 51 524 – (16) 42 Ireland 677 367 1102 1770 6309 (–) 427 Greece 8 143 20 942 6743 23 008 (0) 599 Spain 319 257 180 342 16 298 172 341 176 879 (–) 2305 France 70 918 – 4758 – 141 374 (–) – Croatia 5 359 1047 4171 3 957 (–) 213 Italy 36 347 5261 28 821 5701 894 862 (–) 1227 Cyprus 1 16 99 849 403 (–) 62 Latvia 106 28 29 412 – (344) 31 Lithuania 1 088 11 124 199 – (–) – Luxembourg 8 81 11 832 8 (–) 6 Hungary 5 103 863 2040 5307 (–) 196 Malta 1 71 10 85 27 (–) 3 Netherlandsa 2200 – 12 600 – 1 218 000 (–) – Austria 130 1512 1432 8270 – (196) 327 Poland 208 – 1243 – 69 285 (–) – Portugal 8681 3087 96 559 8462 (–) 354 Romania 25 284 165 1799 8835 (110) 79 Slovenia 0.5 73 810 3 673 9515 (–) 212 Slovakia 0.0 21 81 1307 1039 (–) 32 Finland 122 1467 285 6167 23 000 (63) 3409 Sweden 1 160 6 937 928 9221 – (–) – United Kingdoma 13 432 17 360 13 243 148 746 555 625 (–) 15 846 Turkey 94 279 5331 180 101 60 742 – (–) 3706 Norway 2283 11 875 491 5444 – (159) 386 European Union 463 832 239 781 126 455 431 024 3 742 184 (6 387) 29 625 EU, Turkey and Norway 560 394 256 987 307 047 497 210 3 742 184 (6 546) 33 717 aSeizures data refer to 2012, apart from the number of cannabis plants seized in the Netherlands, which refers to 2013. Table 2. Subset of European‐level estimates available in the EMCDDA 2015 reporting exercise. Last year prevalence in the EU, Norway and Turkey (%) of age group 15–34 Drug group No. of countries Year of data Min 25th percentile Median 75th percentile Max Cannabis 28 2004–2013 0.4 6.375 9.3 11.4 22.1 Cocaine 27 2004–2013 0.2 0.35 1.2 2.1 4.2 Amphetamines 26 2004–2013 0 0.425 0.85 1.375 2.5 Ecstasy 27 2004–2013 0.1 0.45 0.9 1.3 3.1 Estimates of the prevalence of problem drug use in the EU, Norway and Turkey. Rate per 1000 population. Injecting drug users (IDU) and high‐risk opioid users (HROU) Population No of countries Year of data Min 25th percentile Median 75th percentile Max IDU 14 2004–2013 0.22 0.5125 2.76 5.41 9.22 HROU 21 2007–2013 0.48 1.49 2.36 4.91 8.06 Drug‐related deaths in the EU, Norway and Turkey. Rate per 1 000 000 population aged 15–64 No of countries Year of data Min 25th percentile Median 75th percentile Max 29 2010–2013 2 7 11 30 127 HIV notifications attributed to injecting drug use in the EU, Norway and Turkey. Rate per 1 000 000 population. Source ECDC No of countries Year of data Min 25th percentile Median 75th percentile Max 30 2013 0 1 2 6 55 Entrants into specialized treatment centres in the EU, Norway and Turkey, by drug. Rate per 100 000 population (15–64) Drug No. of countries Year of data Min 25th percentile Median 75th percentile Max Opioids 30 2011–13 2.7 18.7 38.8 57.2 469.8 Cocaine 30 2011–13 0.0 0.4 4.0 19.6 90.4 Amphetamines 30 2011–13 0.0 1.5 2.5 7.6 95.5 Cannabis 30 2011–13 1.6 6.4 27.3 50.3 95.0 Other substances 30 2011–13 0.2 1.8 4.1 9.7 98.9 Not known/missing substances 30 2011–13 0.0 0.0 0.4 6.4 64.3 Total number of reported entrants 30 2011–13 10.1 59.1 112.0 158.0 637.3 Number of seizures in the EU, Norway and Turkey. Rate per 100 000 population (15–64) No. of countries Year of data Min 25th percentile Median 75th percentile Max Cannabis resin 27 2013 0.2 2 12 42 575 Herbal cannabis 27 2013 1 30 60 158 549 Cannabis plants 27 2013 0.2 3 6 12 97 Heroin 27 2013 0.2 3 8 22 36 Cocaine 27 2013 1 2 12 26 121 Amphetamine 27 2013 0.03 0.5 6 17 92 Methamphetamine 27 2013 0.01 1 2 6 128 Ecstasy 27 2013 0.4 1 4 12 23 LSD 27 2013 0.01 0.2 0.3 1 8 Quantity seized in the EU, Norway and Turkey. Rate per 100 000 population (15–64) No. of countries Year of data Min 25th percentile Median 75th percentile Max Cannabis resin (kg) 30 2013 0.001 0.2 6 58 1018 Herbal cannabis (kg) 30 2013 1 6 12 36 358 Cannabis plants (no. of plants) 30 2013 2 89 287 670 10 995 Heroin (kg) 30 2013 0.0001 0.1 1 2 27 Cocaine (kg) 30 2013 0.04 0.2 1 9 90 Amphetamine (kg) 30 2013 0.0002 0.1 1 2 10 Methamphetamine (kg) 30 2013 0.0001 0.05 0.1 0.5 6 Ecstasy (tablets) 30 2013 1 70 222 886 22 047 LSD (units) 30 2013 0.01 2 5 40 176 Potency in the EU (% THC)/purity (% pure substance)/mg of ecstasy No. of countries Year of data Samples analysed Min 25th percentile Median 75th percentile Max Cannabis resin (% THC) 26 2013 7246 3 10 12 15 22 Herbal cannabis (% THC) 26 2013 19 277 2 7 9 10 13 Heroin (%) 26 2013 3245 6 13 17 23 42 Cocaine (%) 26 2013 9190 20 33 40 50 75 Amphetamine (%) 26 2013 12 248 5 9 14 19 47 Methamphetamine (%) 26 2013 2431 7 31 37 66 89 Ecstasy (mg/tablet) 26 2013 188 632 34 77 84 98 144 Retail price of drugs in the EU (euros per gram or euros per tablet for ecstasy) No. of countries Year of data Min 25th percentile Median 75th percentile Max Cannabis resin 27 2013 3 8 10 13 21 Herbal cannabis 27 2013 5 8 9 11 25 Heroin 27 2013 25 33 38 58 158 Cocaine 27 2013 47 52 57 70 103 Amphetamine 27 2013 8 10 11 19 63 Methamphetamine 27 2013 10 13 15 42 80 Ecstasy 27 2013 3 5 7 10 24 Figure 1 Open in figure viewer PowerPoint Newly diagnosed HIV cases related to injecting drug use: trends in number of cases. Source: European Centre for Disease Prevention and Control Figure 2 Open in figure viewer PowerPoint Number and categories of new psychoactive substances notified to the EU Early Warning System The European drug information system is explicitly multi‐method and multi‐source. While much has been conducted to improve data quality and comparability, the methodological and practical difficulties of monitoring drug use, and in generating cross‐national comparisons, are considerable and well known 3. The European system attempts to overcome these difficulties, as far as it is possible, through the incorporation of a wide range of information sources, triangulating data, utilizing feedback from national experts and by including methodological and contextual information. None the less, caution is required in the interpretation of data and in particular when single measures between countries are compared. As some important information domains for policy purposes are not covered by quantitative reporting instruments, expert opinions are utilized in the annual reporting exercise, while noting the limitations and difficulties of this approach. The focus of this paper is, however, on the most recent drug‐related quantitative data sets provided by European countries. The reporting system formally covers all 28 European Union (EU) Member States, Norway and Turkey, and incorporates multiple indicators alongside an early warning system (EWS) on uncontrolled new psychoactive substances (NPS) 4. While epidemiological information is based largely on registries, surveys and other routine data and is reported annually, the EWS collects case‐based data on an ongoing basis. Data availability and coverage vary by country and not all data reported comply with the formal EU reporting standards. These issues are reviewed regularly and detailed within the reporting exercise. There is variation in reporting capacity between countries, and the role of the agency is to work at the European level, which necessarily incorporates a range of national circumstances and provision. Numerical data collected in the annual reporting exercise are published in the EMCDDA Statistical Bulletin, which is updated annually and includes detailed methodological information 5. The handling of numerical and statistical information is governed by a formal statistical code of practice 6. Much of the data and analyses are provided through a network of focal points (Reitox), which coordinate national expert networks responsible for submitting and checking data 7.

Data on drug use In addition to examining studies published in the scientific or grey literature, two approaches are used to provide data to comment directly on drug use in Europe (prevalence). The first of these is based on surveys of the general and school populations, with priority given to those carried out at national level. In surveys of both the general population and school students across European countries, a relatively high degree of standardization has been achieved and representative probabilistic samples are utilized. Surveys are generally regarded as a poor tool for reporting on low prevalence and highly stigmatized behaviours such as heroin use or injection 3. To address this, prevalence estimates based on statistical models are also collected. Common approaches include: simple multiplier methods; capture–recapture methods; and extrapolation via multivariate indicator methods 8. Twenty‐eight countries have reported a national population survey since 2004, with 16 new surveys becoming available since 2012. Prevalence estimates are based on standard periods of time, with priority given to last 12 months prevalence, although life‐time and last 30‐day estimates are also available. Estimates are available for three age bands (15–64, 15–34 and 15–24 years). The surveys reported are subject to the range of sampling and non‐sampling errors common to the method 9, 10. In addition, despite considerable improvement in comparability over time, including the general adoption of questions from a model questionnaire, differences still exist in the methodology used by countries, reporting intervals vary and cultural and contextual factors may result in differences in response and non‐response bias 10. Survey data and accompanying methodological information are available for all countries (http://www.emcdda.europa.eu/data/stats2015). In the 16 new surveys reported since 2012, last‐year cannabis prevalence rates for the 15–34 age group ranged from 0.4% in Turkey to 22.1% in France. Of the 15 surveys reporting on last‐year use of illicit stimulants among the 15–34 age group, prevalence rates for cocaine ranged from 0.2% in Greece and Romania to 4.2% in the United Kingdom; rates for amphetamine ranged from 0.1% or less in Romania, Italy and Portugal to 2.5% in Estonia; and rates for ecstasy ranged from 0.1% in Italy and Turkey to 3% in the Czech Republic and the United Kingdom. With respect to school survey data, in addition to national stand‐alone surveys, two coordinated reporting exercises are important. Data on cannabis use and other health variables are available from the Health Behaviour in School‐aged Children (HBSC) survey instrument 11 and data on use of a wider range of substance‐related variables are available through the European School Survey Project on Alcohol and Other Drugs (ESPAD) exercise 12, which now provides a time–series dating back to 1995, with the next report becoming available in 2016. In the results from the last ESPAD survey (2011), one in four 15–16‐year‐old school students reported ever using an illicit drug, mainly cannabis, but with considerable intercountry variation 13. Complementing the survey data, estimates of drug use from statistical modelling can be found at http://www.emcdda.europa.eu/activities/hrdu, accompanied by overviews of the different approaches used. Although there has been an increase in the number of estimates available, there is no single method that is applied in all countries. Even where a standard methodological approach, such as capture–recapture, is used the sources of data on which the estimate are based often differ and it remains difficult to compare results across countries. The data set is most complete for estimates of opioid use, although some countries also report other estimates, including drug injection. Since 2012, 13 countries have produced estimates of high‐risk opioid use and nine countries have produced estimates of injecting drug use. Prevalence estimates of high‐risk opioid use produced since 2012 range from 1.26 cases per 1000 population in the Netherlands to 6.97 cases per 1000 population in Malta (aged 15–64). Estimates of injecting drug use produced since 2012 range from 0.29 cases per 1000 population in Cyprus to 9.2 cases per 1000 population in Latvia (aged 15–64).

Treatment data Historically, the European approach has been to use data on those entering treatment as a proxy indicator for the characteristics of those experiencing drug problems in the population. When combined with other information, these data also provide a window on the European treatment system. Within these data, a distinction is made between those entering drug treatment for the first time and those returning to treatment, with estimates provided for first treatment entrants and all treatment entrants (both repeat and new entries). All countries provide data on treatment demand using an established European protocol, although coverage varies both by country and by treatment type. The data set is most complete for specialized drug treatment services. These limitations are generally well understood, and supporting contextual and methodological information to facilitate interpretation can be found on the EMCDDA website (http://www.emcdda.europa.eu/activities/tdi). In 2013, there were reports of 461 000 Europeans entering treatment for a drug‐related problem, of whom 174 000 entered treatment for the first time in their lives. Data on these treatment entrants can be found at http://www.emcdda.europa.eu/data/stats2015, along with methodological notes and information on coverage. The most recent analysis of treatment data highlights the burden that opioid drugs continue to place on the drug treatment system, although both heroin entrants and injecting have declined in importance. In 2013, opioids—mainly heroin—were reported as a ‘primary drug’ by only 20% of those entering treatment for the first time, with new‐to‐treatment heroin clients more than halving in number since 2007. Data are also available from all countries on opiate substitution treatment, with the introduction of national registers in a growing number of countries improving data quality in this area. An estimated 737 000 opioid users received substitution treatment in 2013, with more than two‐thirds (69%) of substitution clients receiving methadone. Information on national drug treatment systems can be found at http://www.emcdda.europa.eu/responses/treatment‐overviews. For a limited number of countries, data are also available on the number of syringes distributed annually by specialist programmes (see Appendix 2).

Data on drug‐related morbidity and mortality With regard to drug‐related morbidity and mortality, there are two main areas in which significant amounts of quantitative data are available at the European level. The first area is infectious diseases associated with drug use, where the data available refer principally—but not only—to cases of drug‐related human immunodeficiency virus (HIV) and hepatitis C virus (HCV) infections. Drug‐related mortality is the second area; here the data refer principally—but not only—to unintentional drug overdose deaths. In both these domains considerable contextual and supplementary information is available that, for reasons of brevity, is not described here (http://www.emcdda.europa.eu/activities/drd and http://www.emcdda.europa.eu/activities/drid). Drug use, principally through injecting, continues to play an important role in the transmission of blood‐borne infections in Europe. Two main data sources are available on this topic. National notification data from annual HIV case reports, where route of transmission is known, are compiled by the European Centre on Disease Prevention and Control (ECDC) 14 and WHO–Europe 15. In addition, studies and ongoing surveillance exercises conducted among people who inject drugs (PWID), who are tested for HIV and/or hepatitis B and C, are reported annually (prevalence of antibodies, or other specific markers in the case of hepatitis B). In 2013, 30 countries reported on new diagnoses of HIV among samples of PWID. Since 2012, 10 countries have provided data from new national studies on hepatitis C antibody prevalence among PWID. For methodological reasons, principally under‐reporting, national notification data on hepatitis C are not currently regarded as sufficiently reliable to be included in the reporting exercise. Interpreting study data in this area is complicated by the challenges of sampling. None the less, the data have proved useful in providing a broad overview of the situation, including regional variation in levels and trends, and by drawing attention to important developments, for example, the recent HIV outbreaks among PWID experienced by Greece and Romania 16 (see Fig. 1). Among all HIV cases notified in Europe where the route of transmission is known, the percentage attributable to injecting drug use has remained below 8% for the last decade. Provisional figures for the number of new HIV diagnoses in Europe in 2013 show 1458 newly reported cases, compared with 1974 in 2012. In 2013, population‐based rates of newly reported HIV diagnoses attributed to injecting drug use ranged from 0 in Cyprus, Croatia and Slovakia to 54.5 per million population in Estonia. In countries such as Spain and Portugal that have experienced high rates of infection in the past, rates of newly reported HIV diagnoses continue to decline. Hepatitis C antibody levels among national samples of PWID in 2012–13 ranged from 13.8% in Malta to 84.3% in Portugal. Drug use is one of the major causes of avoidable mortality among young people in Europe, both directly through overdose and indirectly through drug‐related diseases, accidents, violence and suicide. All countries report on drug‐induced deaths (overdoses and poisonings attributed directly to use of drugs). Data are derived from general mortality registries with an operative criteria based on selected codes from the WHO ICD‐10, and special registries where the operative criteria consist of the classes of deaths that should be extracted. Additional notes and methodological information are available at http://www.emcdda.europa.eu/activities/drd. Interpreting overdose data is complicated by a range of factors, including systematic under‐reporting in some countries and process‐induced delays in reporting. In 2013, 5804 drug‐induced deaths were reported in Europe among adults aged 15–64, although this figure includes some interpolated data points where reporting delays occurred. National estimates of drug‐induced mortality rates vary considerably, from 2.2 per million population in Romania to 70 per million in Norway and Sweden, and 127 per million in Estonia.

Detections of new psychoactive substances The EWS on NPS operates under a specific legal basis (Council Decision 2005/387/JHA) and is intended to provide the capacity to identify and respond to uncontrolled new substances that may pose a similar risk to public health as drugs controlled under the international conventions 1 (a description of the mechanism can be found at http://www.emcdda.europa.eu/activities/action‐on‐new‐drugs). When substances are judged to meet certain criteria, a formal risk assessment exercise is conducted under the auspices of the EMCDDA scientific committee 17. The results of this inform a political decision‐making process that can result in the control of a substance across the EU. Since 2008, this area has witnessed considerable growth and is the subject of both policy and public attention. It should be noted that the EWS collects case‐based data and that while epidemiological data on the use of these substances are emerging, they are currently weak. A total of 101 new substances were reported to the EU EWS in 2014 (Fig. 2). This brings the number of substances being monitored by the system to more than 450. In 2014, synthetic cathinones 2 (31 substances) and synthetic cannabinoid receptor agonists 3 (30 substances) were the two substance categories with the highest number of notifications. It is of note that the availability of synthetic cannabinoids was only first reported to the EWS in 2008 18. In 2014, six new psychoactive substances were formally risk‐assessed, and each of these substances had been associated with reports of drug‐related harm, including hospitalizations and deaths. These were: 25I‐NBOMe, a substituted phenethylamine with hallucinogenic effects; AH‐7921, a synthetic opioid with properties similar to morphine; MDPV, a synthetic cathinone derivative closely related to pyrovalerone; methoxetamine an arylcyclohexylamine closely related to ketamine; 4′‐DMAR, a psychostimulant structurally related to the controlled drugs 4‐methylaminorex and aminorex; and MT‐45, a synthetic opioid with analgesic potency similar to morphine. In October 2014, 25I‐NBOMe, AH‐7921, MDPV and methoxetamine were subjected to control measures throughout Europe. 4 At the time of writing, a decision is still pending on 4′‐DMAR and MT‐45. Detailed risk assessment reports, which include analysis and toxicological data, are available for all these substances 4.

Market data In addition to information on use and harms, at the European level, quantitative data from law enforcement, criminal justice and forensic science sources are also available. The most comprehensive data sets are in the areas of: number and volume of drug seizures, with more than 1 million seizures reported annually; the price and purity or potency of retail level drugs; and the number of drug‐related offences. The interpretation of these data is complicated by many factors, which include national policies and policing priorities and data quality issues. Currently, improving the quality of data in this area is regarded at the European level as a developmental priority 19. Summary and national tables can be found in Appendix 2 and at http://www.emcdda.europa.eu/data/stats2015.

National and cumulative European estimates In Table 1, national data is provided which allows countries to be compared across a subset of top‐level drug related demand and supply areas. A link is provided to methodological and other information important for interpretation. In addition to the provision of disaggregated data, the EMCDDA is required to provide European summary estimates and a subset of these can be found in Table 2. This task is as important from a policy perspective as it is challenging from a methodological one. Summary estimates can provide an overall characterization of the available data for monitoring both supply and demand, and the opportunity, at an aggregated level, to differentiate by substance. They are also useful for global level comparisons. The interpretation of these estimates must, however, be informed by an understanding of the methodological difficulties inherent in their construction. These include not only comparability issues as already discussed, but also the problem for some measures of missing data and that estimates may be based on data that is not collected contemporaneously. This is particularly the case for surveys which are not usually conducted on an annual basis, and therefore reporting years will necessarily vary.

The European data in an international context The European system for data collection was established to create a knowledge base on drugs information for the EU countries. The approach, however, is clearly influenced by historical, national and international developments 20. The European data therefore contain many of the elements found in other national and international reporting systems. A review of global addiction data sources with comments on their relative strengths and weakness is provided by Gowing et al. 21. It is worth noting, in particular, that the reporting mechanism supporting the United Nations (UN) drug conventions (Annual Report Questionnaire) covers the main information domains for both demand and supply data included in the European data set. Other regional monitoring systems and national data sets exist which are, to a greater or lesser extent, comparable with the EU model; see Griffiths & Mounteney 20 for a discussion. The United States and Australia stand out as countries in which developed and relatively comprehensive monitoring capacity exists. With respect to monitoring the emergence of NPS, by international standards the European system was an early development in this area and has, to some extent, become a model for other data collection mechanisms. At the international level this work is now encompassed in the Global Smart Programme (globalsmart@unodc.org), and in the United States, the National Institutes on Drug Abuse (NIDA) has recently replaced its long‐standing Community Epidemiology Work Group (CEWG) with a new National Drug Early Warning System (NDEWS), which is intended to enhance monitoring and reporting capacity in this area (http://www.drugabuse.gov/drugs‐abuse/emerging‐trends).

Conclusion During the last 20 years the EU has invested in establishing drug monitoring capacity, with the aspiration of enabling the drug situation to be better understood and comparisons to be made between countries. This paper is intended to facilitate a better understanding of, and easier access to, the main quantitative European‐level data sets available in 2015. The methodological issues and data limitations that must necessarily inform any analysis in this area are acknowledged here but not explored in detail. We would argue that with sensitivity to these issues the data available do permit an informed understanding of the European drug situation and provide insight into regional and country differences. The EU reporting system is, however, a child of its time. The system was established at a time when a main policy driver was the need to respond to the diffusion of injecting heroin use and related public health problems. The current EU drug situation is more complex, with stimulants and synthetic substances playing a greater part. It is likely, therefore, that the development of new data sources as well as the exploitation of big data and use of data mining techniques will be required. In 2015 some limited information are available, for example, on acute drug‐related emergencies. This data source has much potential to help to enhance understanding of drug‐related morbidity 22. In addition, multi‐country wastewater analysis studies 23 and exploratory internet monitoring approaches are increasing insight into drug consumption and drug market trends. Novel information sources such as these remain developmental, but are likely to become more important in the future. Finally, an obvious advantage of the EU approach is that countries have been working over the last two decades to harmonize their approach to data collection. More broadly, we note that the number of international bodies collecting information on aspects of drug use has prompted calls for more system wide coherence. We would therefore concur with the conclusions of Gowing et al. 21 that there is an ‘urgent need to review the quality of data on which global estimates are made and coordinate efforts to arrive at a more consistent approach’ (p. 918). We would argue that the European experience highlights not only the challenges that this entails but also the considerable potential over the longer term to provide a more robust understanding of an increasingly global, dynamic and complex drug situation.

Declaration of interests None.

Acknowledgements This paper summarizes those data made available through the EMCDDA 2015 reporting exercise. The authors would like to acknowledge that this information set is only possible due to the work of many contributors. Importantly among these, we would note the invaluable contributions made by the Reitox network of National Focal Points and the associated technical expert working groups, input from other EU agencies, particularly the European Centre for Disease Control and Europol, the ESPAD and SCORE collaborations, the European Commission and staff of the EMCDDA.