Public Health & Policy Issues: Illegal Drugs Sheila M. Bird MRC Biostatistics Unit, Cambridge Collaborations: Sharon Hutchinson & David Goldberg, HPS Brian Tom, Bo Fu & Elizabeth Merrall, BSU Ruth King & Gordon St Andrews & Glasgow

Keep Injecting iLLEgal Drugs Murder Suicide Overdose Late sequelae of Hepatitis C Late sequelae of HIV Late sequelae of alcohol as co-factor Public costs. IDU  socially transmissible disease IDU  courts, prison, health & drug services

Keep Injecting iLLEgal Drugs Projecting Scottish IDUs’ late HCV sequelae required Past & recent injector incidence Past & recent off-injecting rates Past & recent drug-related death rates Other causes’ death-rate for ex-IDUs BBV transmission model: HCV infectiousness & prevalence, injecting frequency/partners BBV progression model: age at HCV infection, sex, alcohol co-factor, antiviral treatment BBV late sequelae: database linkage from HCV diagnoses (minimally) Costs overlay; policy changes; “if scenarios”.

Year Living IDUs (thousands) Modelled prevalent IDUs in Scotland ? doubled from and again from Current & former IDUs Current IDUs

Scotland’s HCV Action Plan (Hutchinson, Bird & Goldberg. Hepatology 2005; 42: ) Despite harm reduction policies, high HCV incidence ~ per 100 susceptible IDU-years. Past IDU epidemic’s current consequences: epidemic wave of DRDs in older current-IDUs ex-IDUs aged years: HCV test & treat (to halt HCV progression) Clean needles don’t prevent DRDs: off-injecting does + reducing IDU initiations. Only HCV-contaminated works infect: ? count HCV-contaminated injections since last –ve test.

National Institute for Health & Clinical Excellence: threshold of £20-30K per QALY NICE on Needle Exchange (NE): without comment, high baseline cost-per-QALY for IDUs of £38K to £45K. (UK-unaffordable) Possible NICE decision = HCV test every 6 months. This was not modelled... NICE Appraisal is Evidence + Judgment. Decision follows from 30% to 50% HCV prevalence among IDUs, transmission risk of 2% or 3% per contaminated injection  25% HCV risk after 10 contaminated injections. “What if” added IDU-years/DRDs facilitated by NE: was not modelled.

Missed UK target 20% reduction in Drug-Related Deaths by 2005 Policy implications?

Drugs-related deaths & Capture-Recapture (CR) in Scotland: ; ; Era Drugs-related deaths Classically-analysed CR of current injectors ~ 25,000 (reference year 2000/01) ~ 20,000 (reference year 2003/04) Oops... !!!

Scotland’s drug-related deaths by: age-group, gender, region EraScotland (male, female) Greater Glasgow (29%) Elsewhere in Scotland 15 – 34 years of age (83% male) public health success? (558, 114) (482, 90) Since (402, 64)

Scotland’s drug-related deaths by: age-group, gender, region EraScotland (male, female) Greater Glasgow (35%) Elsewhere in Scotland 35+ years of age (76% male) Ageing epidemic increase! (269, 65) (322,115) Since (325, 85)

Scotland’s drugs-related deaths & Bayesian CR estimates for current injectors (minor & major modes, King et al., SMMR in press) 3-year EraDrugs- Related Deaths Bayesian Capture-Recapture estimated for current IDUs: annual DRDs per 100 IDUs 2000 – (re 2000/01): (re 2003/04): 1.2 (HPDI: to )

Bayesian Capture-Recapture Not all DRDs occur in IDUs... Prior beliefs: % DRDs who are injectors? 80% for DRDs aged years (75% to 85%) 20% for DRDs aged 45+ years (15% to 35%).

Bayesian Capture-Recapture, ,20 estimate iDRD rate per 100 IDUs Gender & Age-group Greater Glasgow Elsewhere in Scotland BCR IDUs Rate (HPDI) BCR IDUs Rate: (HPDI) M, 15-34yrs (0.9, 1.4) (0.8, 1.2) M, (0.9, 1.5) (1.0, 1.7) F, 15-34yrs (0.3, 0.6) (0.3, 0.5) F, (0.7, 1.4) (1.0, 1.7)

21 st Century Drugs and Statistical Science in UK Surveys, Design & Statistics Subcommittee of HOSAC 1.Landscape: Now surveys with/without biological samples; databases; cohorts; biological sample collections; tangle of technologies 2. Methodology Matters Database linkage & ‘virtual’ cohorts; Capture-recapture methods to estimate #injectors; Epidemics – initiations & removals; Evidence-synthesis, and biases; Formal experiments: randomization & cost-effectiveness; Genetics 3. Essential New Questions 4. New Prospects

Landscape: Now National databases ~ give event-dates (physical, mental health & CJ morbidity + mortality)  access to biological samples. Cohorts ~ conventionally comprise individuals who meet eligibility criteria (born in week W; diagnosed with condition X in region R) & give informed consent for clinical or other re-contact. Identifiers ~ NIL, classificatory, linkable (such as master-index: initial of 1 st name, soundex surname, sex, date of birth  S B630 f ), or personal number (PNC, NI, etc); DNA. Deductive disclosure about individuals: safe havens for linkage & analysis of linked, longitudinal data.

Gamut of surveys, databases, cohorts, biological sample collections. Representative surveillance? Health sites Self-report + biological sample? Schools New questions? Incidence & recovery (R o ) New tests? HCV-RNA for injectors Longitudinal linkage of “health”, drug referral, criminal databases? Coherent reports of IDU debut; powerful re trajectories. Birth & at-risk cohorts? Costly, losses, lack power ‘Virtual’ cohorts? Event-dates without context. Formal experiments in criminal justice? Efficacy, safety & cost-effectiveness.

Methodology Matters Capture-recapture methods to estimate # current injectors POLICY PRIORITY for local estimates, v. capture propensities: 22 models v. all 2-way interactions... Assumptions matter: new CR results for England.

New estimates for current injectors: England REGION Bayesian estimate (95% credible interval) Localised, classical estimate (95% CI) East England 11.1K ( 9.6K; 12.9K) 9.4K ( 6.3K; 13.1K) LONDON 45.8K (34.8K; 60.6K) 17.9K (16.2K; 24.0K) North West 35.4K (31.5K; 39.7K) 22.1K (18.8K; 25.2K) South West 19.3K (16.8K; 22.0K) 17.4K (15.9K; 19.5K) York+Humber 31.8K (28.4K; 35.8K) 21.0K (19.9K; 22.8K) ENGLAND 204K (189K; 223K) 137K (133K; 149K)

Epidemics: initiations into, & removals from injecting Back-calculation from overdose deaths to heroin/IDU incidence: needs duration of injecting Assumptions matter: surely, removal rate increased in 21 st C? Injector careers: snapshot samples.

Referral to Edinburgh’s liver clinic in late 20 th C: non-uniform KAPLAN, typically in last half/quarter of incubation period to cirrhosis (Fu et al., 2007) Clinic patients (if only 5% of community patients routinely referred, rest near to cirrhosis): over-estimate % fast progressors e.g. 55% v. 33% re community Covariate effect size in clinic patients (such as heavy drinking): under-estimated re true effect in community

Judges prescribe sentence on lesser evidence than doctors prescribe medicines Is public aware?

Drug Treatment &Testing Orders (DTTOs) England & Wales: 210 clients Scotland: 96 clients Targets for DTTO clients in E&W: 6,000+ per annum DTTO clients: 21,000+ by end 2003

RSS Court DTTO-eligible offenders: do DTTOs work ? Off 1 DTTO Off 2 DTTO Off 3 alternative = Off 4 DTTO Off 5 alternative = Off 6 alternative = Count offenders’ deaths, re-incarcerations etc...

UK courts’ DTTO-eligible offenders: ? guess Off 7 DTTO [ ? ] Off 8 DTTO [ ? ] Off 9 DTTO [ ? ] Off10 DTTO [ ? ] Off11 DTTO [ ? ] Off12 DTTO [ ? ] Off13 DTTO [ ? ] Off14 DTTO [ ? ] (before/after) Interviews versus... [ ? ]

Evaluations-charade Failure to randomise Failure to find out about major harms Failure even to elicit alternative sentence  funded guesswork on relative cost-effectiveness Volunteer-bias in follow-up interviews Inadequate study size re major outcomes...

The ‘business’ of judging & Judicial counting...

Custodial sentence lengths Male, Adults, Magistrates’ court, single offences, 2004 E&W

Awash with data... urines... Compulsory Drugs Testing in the British Army

10% reduction in opiate +ve rate, weekday pattern in cannabis positive rates. National Offender Management Service in 21st C. 1.Weekend v. Mon-Wed v. Thurs/Fri testing. 2.Different test rate by prison: annual election for or against 5% rMDT! 3.Lowered % positive for cannabis & opiates between eras. 4. Prescribed methadone ~ rarely.

T=tests, P=prescribed methadone, O=opiates, C=cannabis (95% CI for rate per 1,000) Prisons which elected for 5% rMDT 2000/01 to 2002/03 Tests P= 12 O (48, 51) C (77, 81) 2004/05 to 2006/07 Tests P=419 O (42, 44) C (66, 70) Prisons which elected against 5% rMDT 2000/01 to 2002/03 Tests P= 4 O (33, 36) C (64, 68) 2004/05 to 2006/07 Tests P=332 O (30, 32) C (48, 51)

O=opiates, C=cannabis (95% CI: rate per 1,000) 3-yearsMon+Tues+WedThurs+FridaySat+Sunday Prisons which elected for 5% rMDT 2000/01 to 2002/03 Tests O= (46, 50) C = (78, 83) Tests (51, 56) (76, 85) Tests (40, 48) (69, 78) 2004/05 to 2006/07 Tests O= (41, 45) C = (70, 73) Tests (42, 46) (64, 70) Tests (38, 44) (56, 63) Prisons which elected against 5% rMDT 2000/01 to 2002/03 Tests O= (32, 36) C= (67, 72) Tests (32, 37) (59, 65) Tests (33, 40) (56, 66) 2004/05 to 2006/07 Tests O= (29, 33) C= (51, 56) Tests (30, 35) (45, 52) Tests (26, 32) (40, 47)

Formal experiments: drugs courts “Hugs, not Drugs”

Harveian Oration: De Testimonio Evidence + Judgment Efficacy (typically in RCTs) v. Safety (rare events) + Effectiveness (promise into practice) Designs that are fit for purpose... (delayed judgments... ) Signal:noise ratio (usual outcome).

Guardian Society: 17 Nov “Some statisticians are so severe that they would stop social policy making in its tracks. For example, Bird would forbid the government to introduce any policy that had not been assessed through controlled trials... ”

Increased Efficiency at Detection masked trend in soldiers’ cocaine use British Army, Accentuated Monday testing 2.Differential testing by rank: privates! 3. Lowered threshold for cocaine

Privates in British Army: cocaine Year: % of all tests on Mondays MondayTuesdayWednesday Mon-Wed. Positives in 3*15,000 tests Tests to nearest 100; cocaine positive rate per 1, : 54% 24, , , : 44% 23, , , : 36% 19, , , Cocaine +ve Rate per 1, fold increase in 5 years; Wed. rate = half Mon. rate

Essential New Questions [1] Age at/year of starting to inject & at off-injecting. {up to 5 snapshots} # Periods “off-injecting for a least 1 year” since injecting debut. # New initiates to injecting, in your presence, in the past year. {3 present: count each 1/3 rd responsible} # Injectors, known to you, who gave up injecting in past 2 years v. # injectors who died in past 2 years. {pause for reflection}

Four PQs for every CJ initiative PQ1: Minister, why no randomised controls? PQ2: Minister, why have judges not even been asked to document offender’s alternative sentence that this CJ initiative supplants? {cf electronic tagging} PQ3: What statistical power does Ministerial pilot have re well-reasoned targets? {or, just kite flying...} PQ4: Minister, cost-effectiveness is driven by longer-term health & CJ harms, how are these ascertained? {  database linkage}

Bayesian Capture-Recapture 80,20 point-estimate iDRD rate per 100 IDUs applied to Gender & Age-group Greater Glasgow Elsewhere in Scotland Rate Rate (HPDI) Rate Rate (HPDI) M,15-34 yrs (0.9, 1.4) (0.8, 1.2) M, (0.9, 1.5) (1.0, 1.7) F, yrs (0.3, 0.6) (0.3, 0.5) F, (0.7, 1.4) (1.0, 1.7)