Transcript Time line for Bristol

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
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”.
Modelled prevalent IDUs in Scotland
? doubled from 1980-84 and again from 1985-89
Living IDUs (thousands)
120
Current & former IDUs
Current IDUs
100
80
60
40
20
0
1960
1970
1980
Year
1990
2000
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.
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:
2000+01+02; 2003+04+05;
2006+2007
Era
2000+01+02
2003+04+05
2006+07
Drugs-related Classically-analysed CR
deaths
of current injectors
1006
1009
421 + 455
~ 25,000
(reference year 2000/01)
~ 20,000
(reference year 2003/04)
Oops . . . !!!
Scotland’s drug-related deaths by:
age-group, gender, region
Era
Scotland
(male, female)
Greater Elsewhere
Glasgow in Scotland
(29%)
15 – 34 years of age (83% male)
public health success?
2000+01+02
2003+04+05
672 (558, 114)
572 (482, 90)
210
161
462
411
130
336
Since 2005
2006+07
466 (402,
64)
Scotland’s drug-related deaths by:
age-group, gender, region
Era
Scotland
(male, female)
Greater
Glasgow
(35%)
Elsewhere
in Scotland
35+ years of age (76% male)
Ageing epidemic increase!
2000+01+02
2003+04+05
334 (269, 65)
437 (322,115)
116
151
218
286
Since 2005
2006+07
410
(325, 85)
145
265
Scotland’s drugs-related deaths &
Bayesian CR estimates for current
injectors (minor & major modes, King et al.,
SMMR in press)
3-year Era DrugsRelated
Deaths
Bayesian Capture-Recapture
estimated for current IDUs:
annual DRDs per 100 IDUs
2000 – 02
1 006 26 500
2003 - 05
1 009 27 400 (re 2003/04): 1.2
(re 2000/01):
1.3
(HPDI: 20 700 to 32 100)
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
(15% to 35%).
45+ years
Bayesian Capture-Recapture, 2003-05
80,20 estimate iDRD rate per 100 IDUs
Greater
Glasgow
Age-group BCR
Rate
IDUs (HPDI)
M, 15-34yrs 3 300 1.1
Gender
&
(0.9, 1.4)
M, 35+
2 320 1.1
(0.9, 1.5)
F, 15-34yrs
1 600 0.4
(0.3, 0.6)
F, 35+
700 1.0
(0.7, 1.4)
Elsewhere in
Scotland
BCR
Rate:
IDUs (HPDI)
10 060 0.9
(0.8, 1.2)
3 450 1.3
(1.0, 1.7)
4 890 0.4
(0.3, 0.5)
1 040 1.3
(1.0, 1.7)
21st 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 1st 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.
Gamut of surveys, databases, cohorts,
biological sample collections.
Representative surveillance? Health sites
Self-report + biological sample? Schools
New questions? Incidence & recovery (Ro)
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
East England
LONDON
North West
South West
York+Humber
ENGLAND
Bayesian estimate
(95% credible interval)
Localised, classical
estimate (95% CI)
11.1K ( 9.6K; 12.9K)
45.8K (34.8K; 60.6K)
35.4K (31.5K; 39.7K)
19.3K (16.8K; 22.0K)
31.8K (28.4K; 35.8K)
204K
9.4K ( 6.3K; 13.1K)
17.9K (16.2K; 24.0K)
22.1K (18.8K; 25.2K)
17.4K (15.9K; 19.5K)
21.0K (19.9K; 22.8K)
137K
(189K; 223K)
(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 21st C?
Injector careers: snapshot samples.
Referral to Edinburgh’s liver clinic in late 20th C:
non-uniformKAPLAN, 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
Off
Off
Off
Off
Off
1
2
3
4
5
6
DTTO
DTTO
alternative =
DTTO
alternative =
alternative =
Count offenders’ deaths,
re-incarcerations etc . . .
UK courts’ DTTO-eligible
offenders: ? guess
•
•
•
•
•
•
•
•
Off 7
Off 8
Off 9
Off10
Off11
Off12
Off13
Off14
DTTO
DTTO
DTTO
DTTO
DTTO
DTTO
DTTO
DTTO
[
[
[
[
[
[
[
[
?
?
?
?
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?
?
?
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(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
400
200
0
Frequency
600
C ommon assault
Frequency
0
500
1500
Theft from shop
1000
0
Frequency
2500
D riving w hilst disqualified
20
10
0
Frequency
30
S upply and possession of class A drug
30
60
90
Days
120
150
180
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
2004/05
to
2006/07
Tests 110 204P=419
87 300P=
12
O 4 298 (48, 51)
C 6 906 (77, 81)
O 4 739 (42, 44)
C 7 503 (66, 70)
Prisons which elected against 5% rMDT
2000/01
to
2002/03
Tests
2004/05
to
2006/07
Tests
70 997P=
4
O 2 449 (33, 36)
C 4 670 (64, 68)
66 113P=332
O 2 040 (30, 32)
C 3 277 (48, 51)
O=opiates, C=cannabis (95% CI: rate per 1,000)
3-years
Mon+Tues+Wed
Thurs+Friday
Sat+Sunday
Prisons which elected for 5% rMDT
2000/01
to
2002/03
Tests 48 996
O= (46, 50)
2004/05
to
2006/07
Tests 58 614
O= (41, 45)
2000/01
to
2002/03
Tests 38 044
O= (32, 36)
2004/05
to
2006/07
Tests 35 137
O= (29, 33)
C = (78, 83)
Tests 26 169
(51, 56)
(76, 85)
Tests 32 108
(42, 46)
Tests 12 135
(40, 48)
(69, 78)
Tests 19 482
(38, 44)
C = (70, 73)
(64, 70)
(56, 63)
Prisons which elected against 5% rMDT
C= (67, 72)
C= (51, 56)
Tests 21 301
(32, 37)
Tests 11 652
(33, 40)
(59, 65)
(56, 66)
Tests 18 352
(30, 35)
Tests 12 624
(26, 32)
(45, 52)
(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. 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. . . ”
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
Privates in British Army: cocaine
Year:
Monday Tuesday Wednesday
% of all tests
Tests to nearest 100;
on Mondays
cocaine positive rate per 1,000
2007:
54%
2005:
44%
2003:
36%
2003-07
Cocaine+ve
Rate per 1,000
24,500
9.8
23,000
7.8
19,200
3.4
12,000
7.3
13,400
8.2
14,300
3.0
5,800
5.5
10,500
5.1
9,600
1.1
Mon-Wed.
Positives in
3*15,000 tests
338
315
113
3-fold increase
7.0
6.2
3.4
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 1/3rd 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 2006+2007
Greater
Glasgow
Age-group 06+07 Rate
Rate (HPDI)
Gender
&
M,15-34yrs 1.3
1.1
Elsewhere in
Scotland
06+07 Rate
Rate (HPDI)
1.2
(0.9, 1.4)
M,35+
1.4
1.1
(0.8, 1.2)
1.9
(0.9, 1.5)
F, 15-34yrs 0.9
0.4
1.4
1.0
(0.7, 1.4)
1.3
(1.0, 1.7)
0.5
(0.3, 0.6)
F, 35+
0.9
0.4
(0.3, 0.5)
1.4
1.3
(1.0, 1.7)