Initial SARS-CoV-2 Vaccination Uptake in a Correctional Setting: Cross-sectional Study
Bibliographic record
Abstract
BACKGROUND: The largest outbreaks of COVID-19 in the United States have occurred in correctional facilities, and little is known about the feasibility and acceptability of SARS-CoV-2 vaccine campaigns among incarcerated people. OBJECTIVE: The aim of this study was to describe a statewide vaccination program among incarcerated people and staff working in a prison setting. METHODS: Between December 2020 and February 2021, the Rhode Island Department of Corrections (RIDOC) offered the opportunity for SARS-CoV-2 vaccination to all correctional staff and sentenced individuals. Two RIDOC public health educators provided education on the vaccine, answered questions, and obtained consent before the vaccine clinic day for the incarcerated group. All staff received information on signing up for vaccines and watched an educational video that was created by the medical director. Additional information regarding vaccine education and resources was sent via email to the entire RIDOC department. RESULTS: During this initial campaign, 76.4% (1106/1447) of sentenced individuals and 68.4% (1008/1474) of correctional staff accepted and received the vaccine. Four months after the first vaccine was offered, 77.7% (1124/1447) of the sentenced population and 69.6% (1026/1474) of staff were fully vaccinated. CONCLUSIONS: This study demonstrates the feasibility and efficiency of vaccine implementation in a carceral setting. Education and communication likely played an important role in mitigating vaccine refusals.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".