Incidence of HIV and hepatitis C virus among people who inject drugs, and associations with age and sex or gender: a global systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Measuring the incidence of HIV and hepatitis C virus (HCV) infection among people who inject drugs (PWID) is key to track progress towards elimination. We aimed to summarise global data on HIV and primary HCV incidence among PWID and associations with age and sex or gender. METHODS: In this systematic review and meta-analysis, we updated an existing database of HIV and HCV incidence studies among PWID by searching MEDLINE, Embase, and PsycINFO, capturing studies published between Jan 1, 2000, and Dec 12, 2022, with no language or study design restrictions. We contacted authors of identified studies for unpublished or updated data. We included studies that estimated incidence by longitudinally re-testing people at risk of infection or by using assays for recent infection. We pooled incidence and relative risk (RR; young [generally defined as ≤25 years] vs older PWID; women vs men) estimates using random-effects meta-analysis and assessed risk of bias with a modified Newcastle-Ottawa scale. This study is registered with PROSPERO, CRD42020220884. FINDINGS: =43·3%) acquisition than men. For both HIV and HCV, the median risk-of-bias score was 6 (IQR 6-7), indicating moderate risk. INTERPRETATION: Although sparse, available HIV and HCV incidence estimates offer insights into global levels of HIV and HCV transmission among PWID. Intensified efforts are needed to keep track of the HIV and HCV epidemics among PWID and to expand access to age-appropriate and gender-appropriate prevention services that serve young PWID and women who inject drugs. FUNDING: Canadian Institutes of Health Research, Fonds de recherche du Québec-Santé, Canadian Network on Hepatitis C, UK National Institute for Health and Care Research, and WHO.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.015 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".