[Estimating the 2006 prevalence of HIV by gender and risk groups in Tijuana, Mexico].
Bibliographic record
Abstract
OBJECTIVE: Estimate the 2006 HIV prevalence among adults aged 15-49 from the general population and at-risk subgroups in Tijuana, Mexico. METHODS: Demographic data was obtained from the 2005 Mexican census and HIV prevalence data was obtained from reports in the literature. We developed a population-based HIV prevalence model for the overall population and stratified it by gender. Sensitivity analysis consisted of estimating standard errors in the weighted-average point prevalence and calculating partial derivatives of each parameter. RESULTS: HIV prevalence among adults was 0.54% (N = 4347) (range 0.22-0.86% [N = 1750-6944]). This suggests that 0.85% (range 0.39-1.31%) of men and 0.22% (0.04-0.40%) of women could have been HIV-infected in 2006. Men who have sex with men (MSM), followed by female sex workers who are injection drug users (FSW-IDU), FSW-non IDU, female IDU, and male IDU were the most at risk groups of infected individuals. CONCLUSIONS: The number of HIV-infected adults among at-risk subgroups in Tijuana is significant, highlighting the need to design tailored prevention interventions that focus on the specific needs of certain groups. According to our model, as many as 1 in 116 adults could potentially be HIV-infected.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".