The precision of behavioral intervention strategies remain one of the key strategies for HIV prevention among MSM in the era of pharmaceutical interventions: an ecological study
Bibliographic record
Abstract
BACKGROUND: A series of intervention strategies have been successively implemented to prevent HIV among men who have sex with men (MSM) in Shenzhen. This study aimed to examine HIV yield and assess the impact of different intervention strategies on HIV prevention in Shenzhen. METHODS: A serial cross-sectional study was conducted in Shenzhen from 2009 to 2021 among MSM. The temporal trends of HIV yield and HIV risk behaviours were assessed using the Joinpoint Regression model. The effectiveness of the various interventions was evaluated using interrupted time series (ITS) analysis. Multilevel logistic regression was employed to evaluate the changes in the HIV epidemic and HIV risk behaviours across different periods of intervention. RESULTS: The overall HIV yield was 9.8% among MSM in Shenzhen from 2009 to 2021. The HIV yield decreased rapidly after the comprehensive implementation of venue-based differentiated behavioural interventions, from 14.74% in 2013 to 10.69% in 2016 (SPC=-3.80%, 95%CI: -7.10 to-0.40). Since the implementation of immediate cART and PEP/PrEP promotion, the HIV yield further decreased from 9.51% in 2017 to 4.08% in 2021 (SPC=-9.50%, 95%CI: -12.80 to -6.20%). The results of the ITS models revealed that, compared with an increase of 0.57% per quarter in HIV yield during the preintervention period, a significant decrease of 0.28% per quarter was observed after the implementation of venue-based differentiated behavioural interventions. During the implementation of immediate combined antiretroviral treatment and pre- and postexposure prophylaxis promotion, the trend of HIV yield did not change significantly. HIV risk behaviours such as unprotected anal intercourse, drug abuse, and having sex with both men and women all showed a downwards trend. CONCLUSIONS: The yield of HIV among MSM in Shenzhen has declined since 2012 and was lower than the national average from 2020. Although this is the era of pharmacological interventions, adherence to precisely tailored behavioural interventions for controlling HIV yield in MSM has continued to yield significant benefits.
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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 | 0.012 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".