O11.3 Using HCV Incidence Trends to Disentangle the Likely Impact of HIV Anti-Retroviral Treatment on Decreasing HIV Incidence Amongst Injecting Drug Users: A Modelling Analysis
Bibliographic record
Abstract
Background Two epidemiological studies (Vancouver/Baltimore) have used ecological correlations between community measures of HIV viral load (CVL) and HIV incidence to postulate that scaled-up HIV anti-retroviral treatment (ART) has decreased HIV transmission amongst injecting drug users (IDUs). However, for both studies HCV incidence decreased concurrently with observed decreases in HIV incidence suggesting that reductions in injecting risks may also have played a role. We use modelling to estimate the likely importance of ART in producing the observed reductions in HIV incidence in Vancouver from 1997 to 2007. Methods A joint HIV and HCV transmission model, calibrated to the Vancouver IDU HIV epidemic (60% chronic HCV prevalence and 20% HIV prevalence) explored what combinations of ART recruitment and decreases in injecting risk could produce the observed relative reductions in HIV (> 66%) and HCV (> 50%) incidence for Vancouver. For each, the relative importance of ART was assessed. Sensitivity analyses considered the implications of behavioural uncertainty. Results Model projections suggest modest reductions in injecting risk (∼30%) result in large reductions in HIV (∼70%) and HCV (∼45%) incidence over 10 years, whereas ART scale-up (10% per year) only reduces HIV incidence (∼40%). If we assume that HIV and HCV incidence decreased by 83% and 50% in Vancouver, respectively, then projections suggest 31–45% of the HIV impact was possibly due to ART. However, the combined intervention’s impact is less than the sum of its parts, with the estimated HIV incidence decrease only reducing by < 15% with no ART. For smaller assumed reductions in HIV incidence and/or larger decreases in HCV incidence then projections suggest a smaller contribution due to ART. Conclusions Our analysis suggests ART may not have been too important for producing observed HIV incidence declines in Vancouver, and highlights the importance of considering HCV incidence trends in similar analyses.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".