HIV in Canada—Surveillance Report, 2018
Bibliographic record
Abstract
BACKGROUND: Human immunodeficiency virus (HIV) is a global public health issue, with an estimated 36.9 million people living with HIV in 2017. HIV has been reportable in Canada since 1985 and the Public Health Agency of Canada (PHAC) continues to monitor trends in new HIV diagnoses. OBJECTIVE: The objective of this surveillance report is to provide an overview of the epidemiology of all reported diagnoses of HIV in Canada since 1985 with a focus on 2018 overall, and by geographic location, age group, sex, and exposure category. METHODS: PHAC monitors HIV through the national HIV/AIDS Surveillance System, a passive, case-based system that collates nonnominal data that is voluntarily submitted by all Canadian provinces and territories. Descriptive epidemiological analyses were conducted on national data and those relating to specific populations provided by Immigration, Refugees and Citizenship Canada and the Canadian Perinatal HIV Surveillance Program. RESULTS: In 2018, a total of 2,561 HIV diagnoses were reported in Canada, an increase of 8.2% compared with 2017. The national diagnosis rate increased to 6.9 per 100,000 population in 2018 from 6.5 per 100,000 population in 2017. Saskatchewan reported the highest provincial diagnosis rate at 14.9 per 100,000 population. The 30-39 year age group continued to have the highest HIV diagnosis rate at 15.4 per 100,000 population. Overall, the diagnosis rate for males continued to be higher than that of females (9.8 versus 4.0 per 100,000 population, respectively); however, females experienced a larger increase in reported cases and diagnosis rate. The gay, bisexual and other men who have sex with men (gbMSM) exposure category continued to represent the highest proportion of all reported adult cases (41.4%), though the proportion has decreased over time. Five perinatal HIV transmissions were documented, three were related to the mother not receiving perinatal antiretroviral therapy prophylaxis. CONCLUSION: The number and rate of reported HIV cases in Canada increased in 2018, gbMSM continued to account for the largest exposure category and the number and rate of reported HIV cases among women increased. PHAC will continue to work with its national partners to refine the collection, analysis and publication of national data to better understand the burden of HIV in Canada.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.012 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".