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Public Health & Policy Issues: Illegal Drugs Sheila M. Bird MRC Biostatistics Unit, Cambridge Collaborations: Sharon Hutchinson & David Goldberg, HPS Brian.

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Presentation on theme: "Public Health & Policy Issues: Illegal Drugs Sheila M. Bird MRC Biostatistics Unit, Cambridge Collaborations: Sharon Hutchinson & David Goldberg, HPS Brian."— Presentation transcript:

1 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 Hay @ St Andrews & Glasgow

2 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

3 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”.

4 Year Living IDUs (thousands) 19601970198019902000 0 20 40 60 80 100 120 Modelled prevalent IDUs in Scotland ? doubled from 1980-84 and again from 1985-89 Current & former IDUs Current IDUs

5 Scotland’s HCV Action Plan (Hutchinson, Bird & Goldberg. Hepatology 2005; 42: 711-723) Despite harm reduction policies, high HCV incidence ~ 20-30 per 100 susceptible IDU-years. Past IDU epidemic’s current consequences: epidemic wave of DRDs in older current-IDUs ex-IDUs aged 30-49 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.

6 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.

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

8 Drugs-related deaths & Capture-Recapture (CR) in Scotland: 2000+01+02; 2003+04+05; 2006+2007 Era Drugs-related deaths Classically-analysed CR of current injectors 2000+01+02 1006 ~ 25,000 (reference year 2000/01) 2003+04+05 1009 ~ 20,000 (reference year 2003/04) 2006+07 421 + 455Oops... !!!

9 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? 2000+01+02 672 (558, 114) 210 462 2003+04+05 572 (482, 90) 161 411 Since 2005 2006+07 466 (402, 64) 130 336

10 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! 2000+01+02 334 (269, 65) 116 218 2003+04+05 437 (322,115) 151 286 Since 2005 2006+07 410 (325, 85) 145 265

11 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 – 02 1 00626 500 (re 2000/01): 1.3 2003 - 05 1 00927 400 (re 2003/04): 1.2 (HPDI: 20 700 to 32 100)

12 Bayesian Capture-Recapture Not all DRDs occur in IDUs... Prior beliefs: % DRDs who are injectors? 80% for DRDs aged 15-44 years (75% to 85%) 20% for DRDs aged 45+ years (15% to 35%).

13 Bayesian Capture-Recapture, 2003-05 80,20 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 3 3001.1 (0.9, 1.4) 10 0600.9 (0.8, 1.2) M, 35+ 2 3201.1 (0.9, 1.5) 3 4501.3 (1.0, 1.7) F, 15-34yrs 1 6000.4 (0.3, 0.6) 4 8900.4 (0.3, 0.5) F, 35+ 7001.0 (0.7, 1.4) 1 0401.3 (1.0, 1.7)

14 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

15 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 180552), or personal number (PNC, NI, etc); DNA. Deductive disclosure about individuals: safe havens for linkage & analysis of linked, longitudinal data.

16 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.

17 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.

18 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)

19 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.

20 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

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

22 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

23 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...

24 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... [ ? ]

25 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...

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

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

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

29 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.

30 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 87 300 P= 12 O 4 298 (48, 51) C 6 906 (77, 81) 2004/05 to 2006/07 Tests 110 204 P=419 O 4 739 (42, 44) C 7 503 (66, 70) Prisons which elected against 5% rMDT 2000/01 to 2002/03 Tests 70 997 P= 4 O 2 449 (33, 36) C 4 670 (64, 68) 2004/05 to 2006/07 Tests 66 113 P=332 O 2 040 (30, 32) C 3 277 (48, 51)

31 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 48 996 O= (46, 50) C = (78, 83) Tests 26 169 (51, 56) (76, 85) Tests 12 135 (40, 48) (69, 78) 2004/05 to 2006/07 Tests 58 614 O= (41, 45) C = (70, 73) Tests 32 108 (42, 46) (64, 70) Tests 19 482 (38, 44) (56, 63) Prisons which elected against 5% rMDT 2000/01 to 2002/03 Tests 38 044 O= (32, 36) C= (67, 72) Tests 21 301 (32, 37) (59, 65) Tests 11 652 (33, 40) (56, 66) 2004/05 to 2006/07 Tests 35 137 O= (29, 33) C= (51, 56) Tests 18 352 (30, 35) (45, 52) Tests 12 624 (26, 32) (40, 47)

32 Formal experiments: drugs courts “Hugs, not Drugs”

33 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).

34 Guardian Society: 17 Nov. 2004 “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... ”

35 Increased Efficiency at Detection masked trend in soldiers’ cocaine use British Army, 2003 - 2007 1.Accentuated Monday testing 2.Differential testing by rank: privates! 3. Lowered threshold for cocaine

36 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 1,000 2007: 54% 24,500 9.8 12,000 7.3 5,800 5.5 338 2005: 44% 23,000 7.8 13,400 8.2 10,500 5.1 315 2003: 36% 19,200 3.4 14,300 3.0 9,600 1.1 113 2003-07 Cocaine +ve Rate per 1,000 7.06.23.4 3-fold increase in 5 years; Wed. rate = half Mon. rate

37 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}

38 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}

39 Bayesian Capture-Recapture 80,20 point-estimate iDRD rate per 100 IDUs applied to 2006+2007 Gender & Age-group Greater Glasgow Elsewhere in Scotland 06+07 Rate Rate (HPDI) 06+07 Rate Rate (HPDI) M,15-34 yrs 1.31.1 (0.9, 1.4) 1.20.9 (0.8, 1.2) M,35+1.41.1 (0.9, 1.5) 1.91.3 (1.0, 1.7) F, 15-34 yrs 0.90.4 (0.3, 0.6) 0.50.4 (0.3, 0.5) F, 35+1.41.0 (0.7, 1.4) 1.41.3 (1.0, 1.7)


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