DISRUPTING DRUG PROBLEMS IN FORTITUDE VALLEY. By Professor Lorraine Mazerolle and the Griffith-UQ DPMP Team

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1 DISRUPTING DRUG PROBLEMS IN FORTITUDE VALLEY By Professor Lorraine Mazerolle and the Griffith-UQ DPMP Team

2 Collaborators Professor Lorraine Mazerolle (UQ) Professor Paul Mazerolle (Griffith) Dr Matthew Manning (Griffith) Patricia Ferguson (UQ) Dr Gentry White (UQ)

3 Research Goals Model the relative impacts of a local-level drug law enforcement partnership (LEAPS) and a drug education campaign (Ice-Breaker) on reported drug and nuisance incidents in an entertainment district Assess the differential effects of LEAPS and drug education campaigns both inside and outside licensed premises Examine the elements of the law enforcement intervention that hold most promise Assess the impact of LEAPS on reported violent incidents Examine attitudes and perceptions of place managers and young people about police and the Icebreaker Education Campaign

4 Fortitude Valley Licensed premises density: 136 licensed premises with 15 clubs, 16 pubs Density is 15 times the Queensland average N of violent crimes = 5,862 N of murders = 10 Estimated patron population = 60,000/weekend Resident population = 5,388 57% of residents are aged % are couples with no children 70% never married 28% born overseas

6 Liquor Enforcement And Proactive Strategies (LEAPS) Started December 2004 present Third Party Partnership (TPP) initiative led by the Queensland Police (Estimated cost is $160,000 per year) Partners include local council, fire and rescue, workplace health and safety, victuallers, outreach workers LEAPS was a response to escalating drug problems in Brisbane Central Police District Seeks to make licensed premises safer for patrons, staff and security

7 LEAPS Intervention includes a mixture of: (1) Frequent proactive strategies 60% Safety audits (noise level, CCTV requirements, security/patron ratio education, signage, glass management, security registers, fire exits, etc) Educating security personnel (2) Enforcement 40% Citing venues for regulatory breaches Provide evidence in liquor tribunals (e.g. Using LEAPS data to make a case to revoke licenses for troublesome locations)

8 Ice-Breaker Campaign August 2007 State-wide education campaign ($264,000) Media: Methamphetamines ( ice ) Amphetamine-type substances (speed, ecstasy) Posters N at university and licensed premises bathrooms = 1,500 N at bus stop shelters = 70 N scrolling torch lights at 7/11 stores = 177 Print (street press, magazines) = 9

9 Ice-Breaker Campaign

encouraging communication Media: Parents booklet sent to every household Television advertisements (6

10 National Drugs Education Campaign August 2007 coincided with IceBreaker Campaign Advertised the negative consequences of drug use Emphasized the importance of family relationships, providing support and encouraging communication Media: Parents booklet sent to every household Television advertisements (6 versions) Print, posters, postcards in bus shelters, washrooms, etc Online advertising Available in 16 languages

11 National Drugs Campaign 2007

12 Data Interventions Law enforcement partnership (LEAPS Dec 2004) Education campaigns (Queensland Ice-Breaker & National Drugs Campaign August 2007) Monthly reported crime incidents ( ) N = 156 time points LEAPS at month 108; Education at month 140 Drug offences and public nuisance in (1) licensed premises (2) streets & footpaths (3) Valley Totals

13 Average Reported Incidents per Month Valley total Licensed premises Streets & footpaths Drug offences* (57%) Public nuisance^ (77%) * Includes possession, trafficking, produce, sell/supply, and other drug offences ^ Includes disobey move-on direction, resist/hinder/incite/ obstruct, fare evasion and public nuisance offences

serial dependence Allows the researcher to model and remove the

14 Interrupted Time Series Analysis R software package Assesses the magnitude and direction of an intervention Accounts for the serial dependence Allows the researcher to model and remove the effects of noise that may be present in time series observations

Drug Offences in Fortitude Valley Model 1 (1,0,2)(1,0,0) parameter estimate s.e. t p-value β0 1.

025 0.20 0.84 β4-0.023 0.017-1.33 0.18 β5 0.019 0.017 1.14 0.26 φ1 0.507 1.635 0.31 0.

15 Drug Offences in Fortitude Valley Model 1 (1,0,2)(1,0,0) parameter estimate s.e. t p-value β *** β *** β β β β φ θ θ s(φ1 ) R2 = 0.76

Public Nuisance in Fortitude Valley Model 4 (7,0,0)(0,0,0) parameter Estimate s.e. t p-value β0 6.653 0.180 36.

46 0.65 β5-0.059 0.177-0.33 0.74 φ1 0.470 0.081 5.79 0.00 *** φ2 0.070 0.088 0.79 0.43 φ3 0.042 0.089 0.47 0.

17 Public Nuisance in Fortitude Valley Model 4 (7,0,0)(0,0,0) parameter Estimate s.e. t p-value β *** β * β β *** β β φ *** φ φ φ φ ** φ * φ R2 = 0.89

Drug Offences on Streets, Footpaths Model 2 (5,0,1)(1,0,1) parameter estimate s.e. t p-value β0 1.961 0.021 95.27 0.

019 0.024 0.36 0.72 φ1 0.320 0.363 0.88 0.37 φ2 0.158 0.137 1.15 0.25 φ3-0.205 0.098-2.09 0.04 * φ4 0.096 0.105 0.

19 Drug Offences on Streets, Footpaths Model 2 (5,0,1)(1,0,1) parameter estimate s.e. t p-value β *** β *** β β β β φ φ φ * φ φ θ s(φ1) s(θ1) R2 =0.79

Public Nuisance on Streets, Footpaths Model 5 (7,0,0)(0,0,0) parameter estimate s.e. t p-value β0 7.072 0.271 26.

62 0.54 β5 0.028 0.213 0.13 0.89 φ1 0.387 0.083 4.67 0.00 *** φ2 0.111 0.086 1.30 0.19 φ3 0.063 0.087 0.72 0.

21 Public Nuisance on Streets, Footpaths Model 5 (7,0,0)(0,0,0) parameter estimate s.e. t p-value β *** β β * β *** β β φ *** φ φ φ φ ** φ ** φ * R2=0.89

73 β2 0.379 0.899 0.42 0.67 β3 0.627 1.128 0.56 0.58 β4 0.003 0.911 0.003 0.99 β5 0.

23 Drug Offences Inside Licensed Premises Model 3 (0,0,1)(0,0,1) parameter estimate s.e. t p value β *** β β β β β θ s(θ1 ) R2 =.04

25 Conclusions LEAPS is an intervention that holds promise. Observed crime control effects, especially for volume type disorder incidents No evidence of a displacement effect from inside the premises to outdoors Relatively cheap policing intervention Education Campaigns short-lived effect, at best

26 Contact details Lorraine Mazerolle Patricia Ferguson

70 β2-0.026 0.034-0.76 0.45 β3 0.052 0.043 1.22 0.22 β4 0.023 0.035 0.66 0.

27 Public Nuisance inside Licensed Premises Model 6 (0,0,1)(0,0,1) parameter estimate s.e. t p-value β *** β β β β β θ s(θ1 ) R2 = 0.09

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