Prevalence and factors associated with severe acute respiratory syndrome coronavirus 2, sexually transmitted, and blood-borne infections in British Columbia Corrections
Bibliographic record
Abstract
People who are incarcerated (PWAI) and correctional staff face a higher risk of communicable diseases. This study assessed the seroprevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and sexually transmitted bloodborne infections (STBBIs) in British Columbia (BC) Provincial Correctional Centres (PCCs). A multicentre cross-sectional serosurvey was conducted from January 4 to February 14, 2021, among PWAI and staff. Antibody and molecular screening assessed pathogen prevalence, with Pearson’s chi-squared tests for group comparisons. Mixed-effects logistic regression explored clinical and sociodemographic factors associated with SARS-CoV-2 or STBBIs. Among PWAI (n=299), seroprevalence was 5.5% for SARS-CoV-2, 14.6% for hepatitis C virus, and 1.3% for syphilis. Among staff (n=505), seroprevalence was 2.9% for SARS-CoV-2, 1.7% for hepatitis B virus, and 0.6% for syphilis. Among PWAI, lower education (adjusted odds ratio [aOR]=2.38, 95% confidence interval [CI]: 1.02-5.56), unstable employment (aOR=2.86, 95% CI: 1.16-6.67), and opioid use (aOR=3.56, 95% CI: 1.15-12.65) were associated with STBBI acquisition. Among staff, working in a PCC with a SARS-CoV-2 outbreak was associated with infection acquisition (aOR=7.97, 95% CI: 2.28-27.97). The ongoing presence of SARS-CoV-2 and STBBIs in correctional facilities highlights the need for balanced public health interventions addressing both transmissions, ensuring timely prevention, testing, and treatment for all individuals.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".