Self-reported lifetime Hepatitis B virus testing, and vaccination uptake among people who inject drugs in Iran: a nationwide study in 2020
Bibliographic record
Abstract
BACKGROUND: Hepatitis B virus (HBV) infection is a silent epidemic among people who inject drugs (PWID). HBV testing and vaccination are important for PWID to reduce the risk of infection, prevent chronic complications and contribute to public health efforts in addressing HBV transmission. Our objective was to assess the self-reported lifetime uptake of HBV testing and vaccination among PWID in Iran and their associated factors. METHOD: This cross-sectional study was conducted among 2,684 PWID in 11 large cities from July 2019 to March 2020 using a respondent-driven sampling method. Participants were interviewed face-to-face and asked about their lifetime experience of HBV testing and vaccination uptake as the outcome. Logistic regression models were built to identify related factors for reporting HBV testing and vaccination uptake. RESULTS: The prevalence of HBV testing and vaccination uptake among PWID was 14.2% (95% confidence intervals [CI]: 12.8-15.6) and 16.4% (95% CI: 14.9-18.1), respectively. Shared needles, syringes, or equipment in the past 12 months decreased the odds of reporting lifetime HBV testing uptake (Adjusted odds ratio [AOR]:0.46, 95% CI: 0.29-0.72). However, having an academic education (AOR: 1.89, 95% CI: 1.09-3.30) and lifetime experience of homelessness (AOR: 1.58, 95% CI: 1.21-2.06) increased the odds of reporting lifetime HBV vaccination uptake. CONCLUSION: Our study highlighted the low prevalence of HBV testing and vaccination uptake among PWID in Iran. It is essential to understand and address the obstacles preventing PWID from getting tested and vaccinated for HBV. Addressing these barriers could significantly reduce the burden of HBV among this socio-economically marginalized population.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".