Occult HIV infection in a large sample of health-care users in Lombardy, Italy in 2014–2015: implications for control strategies
Bibliographic record
Abstract
We estimated the number of people unaware of their human immunodeficiency virus (HIV) infection in our province, Pavia (population 540 000) in Lombardy, Italy, by means of anonymous unlinked testing of 10 044 serum/plasma samples residual from clinical analyses at the outpatient clinic of Policlinico San Matteo in 2014 and 2015. Ethical and legal approval was obtained prior to study start. Samples were irreversibly anonymised, only retaining gender and 5-year age class. Five sample pools were tested for HIV using LIAISON® XL MUREX HIV Ab/Ag (DiaSorin, Saluggia, Italy). If the pool tested positive, individual samples underwent confirmatory tests, Innotest HIV Antigen mAb (Fujirebio Europe, Gent, Belgium) and HIV BLOT 2·2 (MP Diagnostics, Singapore). Among the 10 044 samples processed, eight were confirmed positive (0·08%, 95% confidence interval 0·03-0·16%), all were males and age was >50 in 3 (37·5%). If projected to the entire population of the Pavia province, this would result in approximately 1000 people unaware of their HIV infection, with age older than expected. In Italy, HIV testing is voluntary, universally free-of-charge and (upon request) anonymous. Nevertheless, this study demonstrates that it is suboptimally employed, and that new strategies and population-level actions will be needed to achieve better implementation of HIV testing and HIV control in our province.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".