Comprehensive needle and syringe program and opioid agonist therapy reduce HIV and hepatitis c virus acquisition among people who inject drugs in different settings: A pooled analysis of emulated trials
Bibliographic record
Abstract
Abstract Background and Aims Although the Netherlands, Canada and Australia were early adopters of harm reduction for people who inject drugs (PWID), their respective HIV and hepatitis C (HCV) epidemics differ. We measured the pooled effect of needle and syringe program (NSP) and opioid agonist therapy (OAT) participation on HIV and HCV incidence in these settings. Design For each cohort, we emulated the design and statistical analysis of a target trial using observational data. Setting and Participants We included PWID at risk of HIV or HCV infection from the Amsterdam Cohort Studies (1985–2013), Vancouver Injection Drug Users Study (1997–2009) and Melbourne Injecting Drug User Cohort Study (SuperMIX) (2010–2021). Measurements Separately for each infection and cohort (only HCV in SuperMIX), marginal structural models were used to compare the effect of comprehensive (on OAT and 100% NSP coverage or on OAT only if no recent injection drug use) versus no/partial NSP/OAT (no OAT and/or <100% NSP coverage) participation. Pooled hazard ratios (HR) and 95% CI were calculated using random‐effects meta‐analysis. Findings We observed 94 HIV seroconversions and 81 HCV seroconversions among 2023 and 430 participants, respectively. Comprehensive NSP/OAT led to a 41% lower risk of HIV acquisition (pooled HR = 0.59, 95% CI = 0.36–0.96) and a 76% lower risk of HCV acquisition (pooled HR = 0.24, 95% CI = 0.11–0.51), compared with no/partial NSP/OAT, with little heterogeneity between studies for both infections ( I 2 = 0%). Conclusions In the Netherlands, Canada and Australia, comprehensive needle and syringe program and opioid agonist therapy participation appears to substantially reduce HIV and hepatitis C acquisition compared with no or partial needle and syringe program/opioid agonist therapy participation. These findings from an emulated trial design reinforce the critical role of comprehensive access to harm reduction in optimizing infection prevention for people who inject drugs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.038 | 0.050 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.051 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".