Characteristics of and Factors Associated With Partner Service Uptake Cascade Among People With Newly Reported HIV/AIDS Diagnoses in Southeastern China in 2022: Cross-Sectional Survey
Bibliographic record
Abstract
BACKGROUND: HIV notification and testing integrated into partner service (PS) practices among HIV-positive individuals have been proven to be an efficient approach for case finding, although it remains a weak link in China. Although nonmarital sexual activities accounted for a large proportion of newly diagnosed HIV-positive cases in China, little is known about PS uptake and associated factors within nonmarital partnerships. OBJECTIVE: This study aimed to describe HIV PS utilization and its associated factors among HIV-positive individuals with nonmarital sexual partners. METHODS: We recruited newly diagnosed HIV-positive individuals who had nonmarital sexual partners in 2022 in Zhejiang Province and offered them PS. We described the PS uptake cascade within sexual partner categories and analyzed the associated factors with 3 primary outcomes from the participants' perspective: nonmarital partner enumeration, HIV testing, and HIV positivity. RESULTS: In this study, 3509 HIV-positive individuals were recruited as participants, and they enumerated 2507 nonmarital sex partners (2507/14,556, 17.2% of all nonmarital sex partners) with contact information. Among these, 43.1% (1090/2507) underwent an HIV test, with an HIV-positive rate of 28.3% (309/1090). Heterosexual commercial partners were the least likely of being enumerated (441/4292, 10.3%) and had the highest HIV-positive rate (40/107, 37.4%). At the participant level, 48.1% (1688/3509) of the participants enumerated at least one nonmarital sex partner with contact information, 52.7% (890/1688) had a sex partner tested for HIV, and 31% (276/890) had at least one nonmarital sex partner who tested positive. Multivariate analysis indicated that gender and transmission route were associated with both nonmarital sex partner enumeration and HIV testing. Age and occupation were associated with nonmarital sex partner enumeration and HIV positivity. Compared with participants who had no regular nonmarital sex partner, those who had a regular nonmarital sex partner were more likely to enumerate nonmarital sex partners (adjusted odds ratio [aOR] 3.017, 95% CI 2.560-3.554), have them get tested for HIV (aOR 1.725, 95% CI 1.403-2.122), and have an HIV-positive nonmarital sex partner (aOR 1.962, 95% CI 1.454-2.647). CONCLUSIONS: The percentage of partner enumeration was low, and HIV testing rate was moderate among nonmarital partnerships of HIV-positive individuals. More efforts should be made to improve PS practices among HIV-positive individuals and address the gap in partner enumeration, especially for heterosexual commercial nonmarital partnerships. Additionally, enhancing PS operational skills among health care personnel could increase the overall efficiency of PS uptake in China.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".