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 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 | 0.000 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".