Projecting the age-distribution of men who have sex with men receiving HIV treatment in the United States
Bibliographic record
Abstract
BACKGROUND: The age-distribution of men who have sex with men (MSM) continues to change in the 'Treat-All' era as effective test-and-treat programs target key-populations. However, the nature of these changes and potential racial heterogeneities remain uncertain. METHODS: The PEARL model is an agent-based simulation of MSM in HIV care in the US, calibrated to data from the North American AIDS Cohort Collaboration on Research and Design (NA-ACCORD). RESULTS: PEARL projects a gradual decrease in median age of MSM at ART initiation from 36 to 31 years during 2010-2030, accompanied by changes in mortality among Black, White, and Hispanic MSM on ART by -8.4%, 42.4% and -19.6%. The median age of all MSM on ART is projected to increase from 45 to 47 years from 2010-2030, with the proportion of ART-users age ≥60y increasing from 6.7% to 28.0%. Almost half (49.7%) of White MSM ART-users are projected to age ≥60y by 2030, compared to 19.5% of Black and 17.2% of Hispanic MSM. CONCLUSIONS: The overall age of US MSM in HIV care is expected to increase over the next decade, and differentially by race/ethnicity. As this population age, HIV programs should expand care for age-related causes of morbidity and mortality.
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 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 | 0.004 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".