High burden of previously undiagnosed HIV infections and gaps in HIV care cascade for conflict-affected female sex workers in northern Uganda
Bibliographic record
Abstract
Given the disproportionate HIV burden faced by female sex workers FSWs and limited data regarding their engagement in the HIV cascade of care in conflict-affected settings, we characterized the cascade of care and examined associations with new HIV diagnoses and antiretroviral therapy (ART) use in a community-based cohort of FSWs in conflict-affected Northern Uganda. Data were collected via FSW/peer-led time-location sampling and outreach, interview-administered questionnaires, and voluntary HIV testing. Of 400 FSWs, 33.5% were living with HIV, of whom 33.6% were new/previously undiagnosed infections and 32.8% were on ART. Unstable housing and heavy alcohol/drug use were independently associated with increased odds of new HIV diagnoses, whereas exposure to condom demonstrations and number of lifetime pregnancies were negatively associated. In subanalysis among known HIV-positive women, age and time since diagnosis were associated with ART use, whereas sexually transmitted infections were negatively associated. Findings suggest the need for FSW-tailored, peer-based, and integrated HIV and sexual and reproductive health programs to address gaps in HIV testing and treatment for FSWs in conflict-affected communities.
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How this classification was reachedexpand
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".