Investigating the HIV epidemic among Black gay and bisexual men in the Southern United States: Results of the HPTN 096 pilot cross-sectional assessment
Bibliographic record
Abstract
BACKGROUND: The HIV Prevention Trials Network (HPTN) 096 study was designed to address the markedly higher rates of HIV incidence among Black men who have sex with men (MSM) in the Southern United States (US). A cross-sectional assessment was conducted during the pilot phase of the study to determine its feasibility and collect key HIV-related metrics for the study population. METHODS AND FINDINGS: Four hundred and twenty-two Black MSM, ≥ 15 years old and living in the four pilot communities (Dallas, TX; Houston, TX; Montgomery, AL; Greenville, SC), were enrolled via starfish sampling into the cross-sectional assessment. Each participant completed two questionnaires and had blood samples collected at a single study visit. Laboratory testing was performed to determine HIV status and use of oral pre-exposure prophylaxis (PrEP). HIV drug resistance and viral suppression were also assessed for two of the four pilot communities (Dallas and Houston). Categorical variables were summarized using frequency and percentage. Continuous variables were summarized using mean, standard deviation, median and interquartile range. Univariable and multivariable logistic regression models were used to assess various associations. HIV status was determined for 403 of the 422 participants (95.5%); 212 (52.6%) men were living with HIV, including one with acute HIV. For these participants, 163 (76.9%) reported that they were in HIV care. In Dallas and Houston, 71 of the 101 living with HIV (70.3%) were virally suppressed. Of the 191 not living with HIV, 57 (29.8%) reported ever taking PrEP, 41 (21.5%) reported being currently on PrEP, and eight (4.2%) reported never having heard of PrEP. PrEP use was documented through laboratory testing in 36 (19.1%) of 188 participants tested; of the 41 participants reporting current PrEP use, five did not have laboratory evidence of PrEP use. CONCLUSION: During the pilot, we successfully recruited Black MSM using starfish sampling and demonstrated the feasibility of collecting primary study outcomes using a cross-sectional assessment. We found a high burden of HIV and those living with HIV had only a moderate rate of viral suppression. In addition, PrEP use was uncommon among the men living without HIV. Reducing HIV incidence in Black MSM remains a key element to addressing the HIV epidemic in the US.
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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 | 0.009 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".