Treatment as prevention effect of direct-acting antivirals on primary hepatitis C virus incidence: findings from a multinational cohort between 2010 and 2019
Bibliographic record
Abstract
Background: Broad direct-acting antiviral (DAA) access may reduce hepatitis C virus (HCV) incidence through a "treatment as prevention" (TasP) effect. We assessed changes in primary HCV incidence following DAA access among people living with HIV (PLHIV). Methods: We used pooled individual-level data from six cohorts from the International Collaboration on Hepatitis C Elimination in HIV Cohorts (InCHEHC). Follow-up started from the first recorded negative HCV antibody test date and ended at last negative antibody test or estimated infection date. Follow-up was restricted to 2010-2019. We used segmented Poisson regression to model trends across pre-, limited- (i.e., restrictions on access) and broad-DAA access periods. Findings: Overall, 45,942 participants had at least one HCV antibody negative result and follow-up between 2010 and 2019. We observed 2042 incident HCV infections over 248,189 person-years (PY). Pooled incidence decreased from 0.91 per 100 PY in 2015 to 0.41 per 100 PY in 2019. Compared to the average pre-DAA period incidence (0.90 per 100 PY), average incidence was similar during the limited-DAA access period (Incidence rate ratio [IRR] = 0.98; 95%CI = 0.87, 1.11), and 52% lower during the broad-DAA access period (IRR = 0.48; 95%CI = 0.42, 0.52). The average annual decline in HCV incidence was 2% in the pre-DAA period; an additional 9% annual decline in incidence was observed during the limited-DAA access period (IRR = 0.91; 95%CI = 0.82, 1.00) and a further 20% decline in the broad-DAA access period (IRR = 0.80, 95%CI = 0.73, 0.89). Interpretation: Our findings suggest that broad DAA access has a TasP effect on primary HCV incidence among PLHIV. Based on the initial years of DAA availability, the countries in the InCHEHC collaboration are on track to meet the World Health Organization's 80% HCV incidence reduction target for PLHIV by 2030. Funding: This study was funded by the Australian Government National Health and Medical Research Council (Grant number GNT1132902).
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 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".