Harm production : correctional environments, injection drug users and risk of infection with blood-borne pathogens
Bibliographic record
Abstract
Background: Analyses of the individual-, social- and structural-level factors promoting the transmission of HIV and other blood-borne pathogens have consistently identified exposure to correctional environments, especially for individuals who use injection drugs (IDU), as a risk factor for infection. The objectives of this project were: to review the epidemiologic literature on incarceration and HIV infection among IDU, critically examining evidence presented supporting a causal linkage between imprisonment and infection; to investigate incarceration experiences in a cohort of active IDU; and to assess the possible effects of incarceration on the post-release risk environment of active IDU. Methods: Longitudinal datasets for quantitative analyses were derived from the Vancouver Injection Drug User Study (VIDUS) and the Scientific Evaluation of Supervised Injection (SEOSI), both prospective cohorts of IDU in Vancouver’s Downtown Eastside neighbourhood. In the first analysis, the prevalence and correlates of reporting incarceration in the the previous six months were identified in SEOSI using generalized estimating equations (GEE). In the second analysis, the possible effect of imprisonment on the prevalence of risk factors for HIV infection was estimated in VIDUS using linear growth curve analysis. Results: In the first analysis, 902 individuals interviewed at least once between 1 July 2004 and 30 June 2006 were included. Overall, 423 (46.9%) reported an incarceration event at some point during the study period. In a multivariate GEE model, recent incarceration was independently associated with a number of high-risk factors, including syringe sharing. In the second analysis, 1603 individuals were interviewed at least once between 1 May 1996 and 31 December 2005 and in cluded. Of these, 147 (9.2%) matched the study criteria and were included as cases; 742 (46.3%) were included as matched controls. In linear growth curve analyses adjusted for age, gender and ethnicity, syringe sharing was significantly more common in the incarcerated group (p = 0.03) after incarceration than in the control group. Conclusions: Our findings support the existence of a role for incarceration in continued viral transmission. In response, appropriate harm reduction measures should be expanded within correctional environments and social, political and legal reforms enacted to reduce the incidence of imprisonment for individuals who use illicit drugs.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".