Epidemiology of HIV in the United States and Canada: Current Status and Ongoing Challenges
Bibliographic record
Abstract
PURPOSE: To determine the status of the HIV epidemic in the United States and Canada. METHODS: We used data on AIDS and HIV diagnoses for 1996-2005 reported to the United States and Canadian national surveillance systems to determine trends in AIDS and HIV (33 US states only) diagnoses and to identify population groups most affected by HIV. HIV incidence for Canada was determined using back-calculation methods. We also determined the proportion of persons diagnosed late (HIV diagnosis within 12 months before AIDS diagnosis). RESULTS: AIDS diagnosis rates were higher in 2005 among blacks (54.1 per 100,000) and Hispanics (18.0) compared with whites (5.9) in the United States and among blacks (4.7) and aboriginal peoples (4.9) compared with whites (0.7) in Canada. Since 2001, HIV diagnoses increased among men who have sex with men in both countries and in Canada, increased among persons from HIV-endemic countries and where heterosexual contact was the only identified risk of transmission. Overall, HIV incidence remained relatively stable in Canada during that period. A large proportion of persons were diagnosed late in the disease process (United States, 54.3%; Canada, 64.2%). CONCLUSIONS: Rates of HIV transmission remain a challenge in both the United States and Canada as overall diagnosis rates have not decreased in recent years. Renewed prevention efforts are needed to further reduce the high HIV diagnosis rates among racial/ethnic minorities and to decrease HIV transmission among men who have sex with men.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.012 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".