Characterization of Acute HCV Infection and Transmission Networks in People Who Currently Inject Drugs in Catalonia: Usefulness of Dried Blood Spots
Bibliographic record
Abstract
BACKGROUND AND AIMS: Accurate identification of recent HCV infections is critical for tracing the extent and mechanisms of ongoing transmission. We aimed to validate dried blood spot (DBS) samples for the assessment of Hepatitis C virus (HCV) genetic diversity and to determine epidemiological parameters including incidence, determinants of acute infection, and phylogenetic clustering in people who inject drugs (PWID). APPROACH AND RESULTS: HCV nonstructural protein 5B next-generation sequencing was performed from plasma and/or DBS in 220 viremic PWID from the HepCdetect II study. No significant differences were found in consensus sequences or Shannon entropy (SE) intrahost diversity estimate between paired plasma/DBS specimens. SE values were used to identify acute infections with 93.3% sensitivity (95% CI, 0.81-1.06) and 95.0% specificity (95% CI, 0.88-1.02) in a set of well-defined controls. An acute HCV infection (either primary infection or reinfection) was detected in 13.5% of viremic participants and was associated with age ≤30 years (OR, 8.09), injecting less than daily (OR, 4.35), ≤5 years of injected drug use (OR, 3.43), sharing cocaine snorting straws (OR, 2.89), and being unaware of their HCV status (OR, 3.62). Annualized HCV incidence was estimated between 31 and 59/100 person-years. On phylogenetic analysis, 46.8% of viremic cases were part of a transmission pair or cluster; age ≤30 years (OR, 6.16), acute infection (OR, 5.73), and infection with subtype 1a (OR, 4.78) were independently associated with this condition. CONCLUSIONS: The results obtained from plasma and DBS characterize PWID with acute infection and those involved in ongoing HCV transmission and allow estimating incidence from cross-sectional data. This information is critical for the design and assessment of targeted harm reduction programs and test-and-treat interventions and to facilitate monitoring of HCV elimination in this key population.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".