Incident HIV infection has fallen rapidly in men who have sex with men in Melbourne, Australia (2013–2017) but not in the newly-arrived Asian-born
Bibliographic record
Abstract
BACKGROUND: We examined differences in incident HIV infection between newly-arrived Asian-born and other men who have sex with men (MSM) after the introduction of universal HIV treatment guidelines in 2015 and pre-exposure prophylaxis in 2016. METHODS: Clinical, demographic, laboratory and behavioural data on MSM presenting for HIV testing at the Melbourne Sexual Health Centre from July 2013 to June 2017 were extracted. We compared the proportion of newly-arrived (four years or less in Australia), Asian-born and other MSM tested each year who were diagnosed with incident HIV infection (negative test within one year or diagnosis with indeterminate or negative Western Blot). RESULTS: We analysed 35,743 testing episodes in 12,180 MSM, including 2781 testing episodes in 1047 newly-arrived Asian-born MSM. The proportion of other MSM tested each year who were diagnosed with incident HIV infection fell from 0.83% in 2014 to 0.38% in 2017 (p = .001), but did not fall in newly-arrived Asian-born MSM (from 1.18% in 2014 to 1.56% in 2017, p = .76). In the multivariate logistic regression, in 2016/2017 but not in 2014/2015, being newly-arrived Asian-born was associated with an increased odds of diagnosis of incident HIV infection (aOR 3.29, 95%CI 1.82-5.94, p < .001). CONCLUSIONS: The epidemiology of HIV in Melbourne Australia has changed dramatically. While there has been an overall reduction amongst MSM, the incidence of HIV in newly-arrived Asian-born MSM remains high. Failing to address these new inequalities leaves individuals at risk and may offset the population benefit of biomedical HIV prevention.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 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".