The Practice and Potential Role of HIV Self-testing in China: Systematic Review and Meta-analysis
Bibliographic record
Abstract
Background HIV self-testing (HIVST) is recommended by the World Health Organization as a valid approach to routine HIV testing services. The scale of HIVST use has gradually been expanded in China over the past 5 years. To take a closer look at the role of HIVST in China, we reviewed the promotion and application of HIVST within China. Objective The main objective of this study was to systematically analyze the proportion of past use and actual uptake of HIVST within China. Moreover, we aimed to quantify the effect of HIVST on HIV prevention and treatment. Methods In all, 5 medical databases and 2 registration systems, including PubMed, Web of Science, MEDLINE, WanFang, China National Knowledge Internet, ClinicalTrials.gov, and the Chinese Clinical Trial Registry were systematically searched for studies reporting the prevalence of HIVST use from January 1, 2010, to December 25, 2021. Meta-analyses of the pooled proportion estimates were carried out by the meta-package in R software (version 4.1.2). Statistical heterogeneity among the studies was estimated using Cochran Q test and the inconsistency index (I2). Results A total of 50 studies were included in our systematic review. The estimated pooled prevalence of HIVST use in China was 29.9% (95% CI 22.5%-37.9%). Among individuals who have ever used HIVST, 47.5% (95% CI 37.2%-57.8%) were tested for HIV for the first time. The pooled reactive rate of HIVST was 4.2% (95% CI 3.1%-5.8%). When HIVST revealed a reactive result, 81.3% (95% CI 70.9%-91.6%) of individuals sought medical care. Conclusions In recent times, HIVST has become a valuable tool for HIV prevention in China. The widespread use of HIVST in non–men who have sex with men populations needs to be endorsed and promoted. The long-term applications of HIVST and the potential consequences of self-financing of HIVST in China have yet to be explored. Trial Registration PROSPERO CRD42022304846; https://tinyurl.com/54d9pxy8
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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 | 0.030 | 0.060 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.030 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".