The Cascade of Care for Hepatitis C Treatment in Rwanda: A Retrospective Cohort Study of the 2017–2019 Mass Screening and Treatment Campaign
Bibliographic record
Abstract
Access to hepatitis C (HCV) testing and treatment is still limited globally. To address this, the Government of Rwanda launched a voluntary mass screening and treatment campaign in 2017. We studied the progression of patients through the cascade of HCV care during this campaign. We conducted a retrospective cohort study and included all patients screened at 46 hospitals between April 2017 and October 2019. We used hierarchical logistic regression to assess factors associated with HCV positivity, gaps in care, and treatment failure. A total of 860,801 people attended the mass screening during the study period. Some 5.7% tested positive for anti-HCV, and 2.9% were confirmed positive. Of those who were confirmed positive, 52% initiated treatment, and 72% of those initiated treatment, completed treatment and returned for assessment 12 weeks afterward. The cure rate was 88%. HCV positivity was associated with age, socio-economic status, sex, marital status, and HIV coinfection. Treatment failure was associated with cirrhosis, baseline viral load, and a family history of HCV. Our results suggest that future HCV screening and testing interventions in Rwanda and other similar settings should target high-risk groups. High dropout rates suggest that more effort should be put into patient follow-up to increase adherence to care.
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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) | 0.000 | 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 | 0.000 |
| 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".