HIV and STI positivity rates among transgender people attending two large STI clinics in the Netherlands
Bibliographic record
Abstract
BACKGROUND: Global data show that transgender people (TGP) are disproportionally affected by HIV and sexually transmitted infections (STIs); however, data are scarce for Western European countries. We assessed gender identities, sexual behaviour, HIV prevalence and STI positivity rates, and compared these outcomes between TGP who reported sex work and those who did not. METHODS: We retrospectively retrieved data from all TGP who were tested at the STI clinics of Amsterdam and The Hague, the Netherlands in 2017-2018. To identify one's gender identity, a 'two-step' methodology was used assessing, first, the assigned gender at birth (assigned male at birth (AMAB)) or assigned female at birth), and second, clients were asked to select one gender identity that currently applies: (1) transgender man/transgender woman, (2) man and woman, (3) neither man nor woman, (4) other and (5) not known yet. HIV prevalence, bacterial STI (chlamydia, gonorrhoea and/or infectious syphilis) positivity rates and sexual behaviour were studied using descriptive statistics. RESULTS: TGP reported all five categories of gender identities. In total 273 transgender people assigned male at birth (TGP-AMAB) (83.0%) and 56 transgender people assigned female at birth (TGP-AFAB) (17.0%) attended the STI clinics. Of TGP-AMAB, 14,6% (39/267, 95% CI 10.6% to 19.4%) were HIV-positive, including two new diagnoses and bacterial STI positivity was 15.0% (40/267, 95% CI 10.9% to 19.8%). Among TGP-AFAB, bacterial STI positivity was 5.6% (3/54, 95% CI 1.2% to 15.4%) and none were HIV-positive. Sex work in the past 6 months was reported by 53.3% (137/257, 95% CI 47.0% to 59.5%) of TGP-AMAB and 6.1% (3/49, 95% CI 1.3% to 16.9%) of TGP-AFAB. HIV prevalence did not differ between sex workers and non-sex workers. CONCLUSION: Of all TGP, the majority were TGP-AMAB of whom more than half engaged in sex work. HIV prevalence and STI positivity rates were substantial among TGP-AMAB and much lower among TGP-AFAB. Studies should be performed to provide insight into whether the larger population of TGP-AMAB and TGP-AFAB are at risk of HIV and STI.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".