Bibliographic record
Abstract
BACKGROUND: Human immunodeficiency virus (HIV) is a global public health issue. HIV has been nationally notifiable in Canada since 1985. The Public Health Agency of Canada (PHAC) monitors trends in new HIV diagnoses. OBJECTIVES: The objective of this surveillance report is to provide an overview of the epidemiology of reported HIV cases in 2019 in Canada. The report highlights 10-year trends (2010-2019). Data on HIV diagnosed through Immigration Medical Exams (IME) and trends in perinatal transmission of HIV are also presented. METHODS: PHAC monitors HIV through the HIV/AIDS Surveillance System, a passive, case-based system that collates non-nominal data submitted voluntarily by all Canadian provinces and territories. Descriptive analyses were conducted on national data. IME data were obtained from Immigration, Refugees and Citizenship Canada (IRCC), and data on HIV-exposed pregnancies were obtained through the Canadian Perinatal HIV Surveillance Program. RESULTS: In 2019, a total of 2,122 HIV diagnoses were reported in Canada (5.6 per 100,000 population). Saskatchewan reported the highest provincial diagnosis rate at 16.9 per 100,000 population. The 30 to 39-year age group had the highest HIV diagnosis rate at 12.7 per 100,000 population. While the rates for both males and females fluctuated in the past decade, since 2010 the rates among males decreased overall, while the rate among females increased slightly. As in previous years, the diagnosis rate for males in 2019 was higher than that for females (7.9 versus 3.4 per 100,000 population, respectively). The highest proportion of all reported adult cases with known exposure were gay, bisexual and other men who have sex with men (gbMSM, 39.7%), followed by cases attributed to heterosexual contact (28.3%) and among people who inject drugs (PWID, 21.5%). The number of migrants who tested positive for HIV during an IME conducted in Canada was 626. The one documented perinatal HIV transmission related to a mother who had not received antepartum or intrapartum antiretroviral therapy prophylaxis. CONCLUSION: The number and rate of reported HIV cases in Canada has remained relatively stable over the last decade, with minor year-to-year variations. As in previous years, the gbMSM and PWID populations represent a high proportion of HIV diagnoses, although a sizable number of cases were attributed to heterosexual contact. It is important to routinely monitor trends in HIV in light of pan-Canadian commitments to reduce the health impact of sexually transmitted and blood-borne infections by 2030.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.007 | 0.012 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".