Trends in Serosorting and the Association With HIV/STI Risk Over Time Among Men Who Have Sex With Men
Bibliographic record
Abstract
BACKGROUND: Serosorting among men who have sex with men (MSM) is common, but recent data to describe trends in serosorting are limited. How serosorting affects population-level trends in HIV and other sexually transmitted infection (STI) risk is largely unknown. METHODS: We collected data as part of routine care from MSM attending a sexually transmitted disease clinic (2002-2013) and a community-based HIV/sexually transmitted disease testing center (2004-2013) in Seattle, WA. MSM were asked about condom use with HIV-positive, HIV-negative, and unknown-status partners in the prior 12 months. We classified behaviors into 4 mutually exclusive categories: no anal intercourse (AI); consistent condom use (always used condoms for AI); serosorting [condom-less anal intercourse (CAI) only with HIV-concordant partners]; and nonconcordant CAI (CAI with HIV-discordant/unknown-status partners; NCCAI). RESULTS: Behavioral data were complete for 49,912 clinic visits. Serosorting increased significantly among both HIV-positive and HIV-negative men over the study period. This increase in serosorting was concurrent with a decrease in NCCAI among HIV-negative MSM, but a decrease in consistent condom use among HIV-positive MSM. Adjusting for time since last negative HIV test, the risk of testing HIV positive during the study period decreased among MSM who reported NCCAI (7.1%-2.8%; P= 0.02), serosorting (2.4%-1.3%; P = 0.17), and no CAI (1.5%-0.7%; P = 0.01). Serosorting was associated with a 47% lower risk of testing HIV positive compared with NCCAI (adjusted prevalence ratio = 0.53; 95% confidence interval: 0.45 to 0.62). CONCLUSIONS: Between 2002 and 2013, serosorting increased and NCCAI decreased among Seattle MSM. These changes paralleled a decline in HIV test positivity among MSM.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".