Increasing HIV transmission through male homosexual and heterosexual contact in Australia: results from an extended back‐projection approach
Bibliographic record
Abstract
OBJECTIVES: The aim of the study was to reconstruct the HIV epidemic in Australia for selected populations categorized by exposure route; namely, transmission among men who have sex with men (MSM), transmission among injecting drug users (IDUs), and transmission among heterosexual men and women in Australia. DESIGN: Statistical back-projection techniques were extended to reconstruct the historical HIV infection curve using surveillance data. Methods We developed and used a novel modified back-projection modelling technique that makes maximal use of all available surveillance data sources in Australia, namely, (1) newly diagnosed HIV infections, (2) newly acquired HIV infections and (3) AIDS diagnoses. RESULTS: The analyses suggest a peak HIV incidence in Australian MSM of approximately 2000 new infections per year in the late 1980s, followed by a rapid decline to a low of <500 in the early 1990s. We estimate that, by 2007, cumulatively approximately 20 000 MSM were infected with HIV, of whom 13% were not diagnosed with HIV infection. Similarly, a total of approximately 1050 and approximately 2600 individuals were infected through sharing needles and heterosexual contact, respectively, and in 12% and 23% of these individuals, respectively, the infection remained undetected. DISCUSSION: Male homosexual contact accounts for the majority of new HIV infections in Australia. However, the transmission route distribution of new HIV infections has changed over time. The number of HIV infections is increasing substantially among MSM, increasing moderately in those infected via heterosexual exposure, and decreasing in IDUs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".