PrEP in Prisons: HIV prevention in incarcerated populations
Bibliographic record
Abstract
PURPOSE: The purpose of this paper is to discuss the possibility of using pre-exposure prophylaxis (PrEP) as an HIV harm reduction intervention in prisons. PrEP is primarily discussed in relation to men who have sex with men (MSM), meaning other high-risk populations, such as prisoners, are often side-lined. The authors wanted to consider how it could prove beneficial beyond the MSM community. DESIGN/METHODOLOGY/APPROACH: First, the authors discuss whether the common objections to existing HIV harm reduction interventions in prisons, such as needle exchanges, are applicable to PrEP. The authors then apply common objections to the provision of PrEP in the general population to the provision of PrEP in a prison context in order to assess their strength. Finally, the authors discuss what the authors anticipate to be a key objection to PrEP in prisons: post-incarceration access. FINDINGS: The authors argue that both sets of common objections considered are easily refuted in the case of PrEP in prisons. The unique setting and nature of the intervention are such that it is without immediately apparent flaws. In addressing post-incarceration access, the authors suggest that a longitudinal consideration of a prisoner's HIV risk undermines the objection. ORIGINALITY/VALUE: This discussion is of importance due to the significantly heightened risk of HIV infection prisoners are subject to. Not only do effective HIV prevention interventions in prisons contribute to fair access to health for incarcerated individuals, but also to the wider fight against HIV. The authors demonstrate that PrEP has potential as a new approach and call for further research in this area.
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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 | 0.008 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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".