Growth in Proportion and Disparities of HIV PrEP Use Among Key Populations Identified in the United States National Goals: Systematic Review and Meta-analysis of Published Surveys
Bibliographic record
Abstract
BACKGROUND: Pre-exposure prophylaxis (PrEP) use among populations most vulnerable to HIV as identified in the national HIV prevention goals is not fully known. This systematic review assessed trends of lifetime self-reported PrEP use and disparities among key populations. METHODS: We used the CDC HIV/AIDS Prevention Research Synthesis cumulative database of electronic and manual searches in MEDLINE, CINAHL, EMBASE, and PsycINFO from 2000 to 2019 to identify English-language primary studies reporting PrEP use. Two reviewers independently screened citations, extracted data, and assessed the risk of bias with the modified Newcastle-Ottawa Scale. We estimated pooled proportions and crude/adjusted odds ratio. RESULTS: We identified 95 eligible studies including 95,854 US-based survey respondents. A few studies (6.3%) focused on persons who inject drugs. In 2015-2017, men who have sex with men (MSM) had highest proportion of individuals who used PrEP over their lifetime [13.9% (95% confidence interval: 8.8 to 21.1), k (number of surveys) = 49] followed by Hispanic/Latinos [11.5 (7.1 to 18.1), 12], transgender women [11.2 (5.8 to 20.6), 5], and blacks [9.9 (8.3 to 11.8), 18]. Odds of PrEP use increased by 34%/year [odds ratio = 1.34/year (95% confidence interval: 1.09 to 1.64)] and significantly increased over time among MSM [1.53/year (1.21-1.93)] and blacks [1.44 (1.13-1.83)]. People in the Southern United States [9.9 (4.7-19.7), 8] and youth [7.3 (4.7-11.2), 8] had lower rates and did not demonstrate growth [0.94 (0.29-3.18); 0.82 (0.43-1.55)]. Odds of reporting lifetime PrEP use was twice [2.07 (1.27-3.38)] as great among MSM than non-MSM. CONCLUSIONS: Proportions of PrEP use in published surveys have been growing, but remain low for people in the Southern United States and youth, and understudied in persons who inject drugs. Limitations include few studies in certain years, whereas strengths include a large number of respondents. Culturally tailored approaches targeting vulnerable populations are essential in increasing PrEP use to reduce disparities in HIV acquisition.
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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 | 0.027 | 0.083 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.031 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".