Sexually transmitted and blood-borne infections in transgender and non-binary people in Canada: A scoping review
Bibliographic record
Abstract
In the 2021 census, 100,815 people in Canada aged 15 and older identified as transgender or non-binary. Globally, transgender people are disproportionately burdened by several Sexually Transmitted and Blood-Borne Infections (STBBIs) but limited data are available in Canada. Transgender and non-binary people are recognised as key populations in the STBBI Action Plan 2024-2030. We conducted a scoping review of the evidence relating to STBBI prevalence; risk exposures; and use of STBBI testing, treatment and prevention services among transgender and non-binary people in Canada. We searched six databases for articles published between January 1, 2013 and September 1, 2023 and conducted a grey literature search of information published on provincial and territorial public health department websites and websites of eight relevant community organisations. 26 of 934 screened records were included, of which five were provincial surveillance reports from Ontario and Quebec. It is difficult to quantify the prevalence of any STBBI among transgender and non-binary people in Canada. Most provinces and territories, and the federal government, do not publish disaggregated STBBI prevalence data for these populations. Peer-reviewed literature provides HIV prevalence data for several subgroups of the transgender population in some parts of Canada but, in general, these studies were not designed to produce valid prevalence estimates. Transgender people may be less sexually active than other population groups, though this may vary between subgroups of the transgender population. Transgender people face many barriers to accessing healthcare, testing and treatment for STBBIs, while almost no research has been conducted on STBBIs in non-binary people. It is not possible to make specific recommendations for public policy based on the evidence as it currently exists. More public health surveillance and research, conducted in collaboration with transgender and non-binary communities across Canada, would help to better understand the burden of STBBIs in these populations nationally.
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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 | 0.009 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.023 | 0.034 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".