Trends in HIV prevalence, new HIV diagnoses, and mortality among adults with HIV who entered care in Ontario, 1996/1997 to 2009/2010: a population-based study.
Bibliographic record
Abstract
BACKGROUND: Population-based estimates of HIV prevalence, rates of new HIV diagnoses, and mortality rates among persons with HIV who have entered care are needed to optimize health service delivery and to improve the health outcomes of these individuals. However, these data have been lacking for Ontario. METHODS: Using a validated case-finding algorithm and linked administrative health care databases, we conducted a population-based study to determine the prevalence of HIV and rates of new HIV diagnoses among adults aged 18 years or older in Ontario between fiscal year 1996/1997 and fiscal year 2009/2010, as well as all-cause mortality rates among persons with HIV over the same period. RESULTS: Between 1996/1997 and 2009/2010, the number of adults living with HIV increased by 98.6% (from 7608 to 15,107), and the age- and sex-standardized prevalence of HIV increased by 52.8% (from 92.8 to 141.8 per 100,000 population; p < 0.001). Women and individuals 50 years of age or older accounted for increasing proportions of persons with HIV, rising from 12.8% to 19.7% (p < 0.001) and from 10.4% to 29.9% (p < 0.001), respectively, over the study period. During the study period, age- and sex-standardized rates of new HIV diagnoses decreased by 32.5% (from 12.3 to 8.3 per 100,000 population; p < 0.001) and mortality rates among adults with HIV decreased by 71.9% (from 5.7 to 1.6 per 100 adults with HIV; p < 0.001). INTERPRETATION: The prevalence of HIV infection in Ontario increased considerably between 1996/1997 and 2009/2010, with a greater relative burden falling on women and individuals aged 50 years of age or older. These trends may be due to the decreased rate of new diagnoses among younger men. All-cause mortality rates declined among persons with HIV who entered care.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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, 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".