Combined COVID-19 vaccination and hepatitis C virus screening intervention in marginalised populations in Spain
Bibliographic record
Abstract
BACKGROUND: COVID-19 has hindered hepatitis C virus (HCV) and HIV screening, particularly in marginalised groups, who have some of the highest rates of these conditions and lowest rates of COVID-19 vaccination. We assessed the acceptability of combining HCV testing with COVID-19 vaccination in a centre for addiction services (CAS) in Barcelona and a mobile testing unit (MTU) in Madrid, Spain. METHODS: From 28/09/2021 to 30/06/2022, 187 adults from marginalised populations were offered HCV antibody (Ab) testing along with COVID-19 vaccination. If HCV Ab+, they were tested for HCV-RNA. MTU participants were also screened for HIV. HCV-RNA+ and HIV+ participants were offered treatment. Data were analysed descriptively. RESULTS: Findings show how of the 86 CAS participants: 80 (93%) had been previously vaccinated for COVID-19, of whom 72 (90%) had the full first round schedule; none had a COVID-19 vaccine booster and all received a COVID-19 vaccine; 54 (62.8%) were tested for HCV Ab, of whom 17 (31.5%) were positive, of whom all were tested for HCV-RNA and none were positive. Of the 101 MTU participants: none had been vaccinated for COVID-19 and all received a COVID-19 vaccine; all were tested for HCV Ab and HIV and 15 (14.9%) and 9 (8.9%) were positive, respectively; of those HCV Ab+, 9 (60%) were HCV-RNA+, of whom 8 (88.9%) have started treatment; 5 (55.6%) of those HIV+ had abandoned antiretroviral therapy, of whom 3 (60%) have re-started it. CONCLUSIONS: The intervention was accepted by 54 (62.8%) CAS participants and all MTU participants and can be used in marginalised communities.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| 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".