A process evaluation of Ontario, Canada’s 2023–24 older-adult RSV vaccination program
Bibliographic record
Abstract
Respiratory syncytial virus (RSV) is a major cause of respiratory illness in older adults. During the 2023-2024 respiratory season, Ontario was the first and only province in Canada to launch a publicly funded RSV vaccination program for older adults. A process evaluation of the program was completed to better understand the experiences of the local Public Health Units (PHUs) and long-term care homes (LTCHs) implementing the program. Two process evaluation surveys, one each for PHUs and LTCHs, and a separate immunization coverage survey for LTCHs were distributed. The coverage survey found that 58.5% of residents, among all those living in LTCHs responding to the survey, received the RSV vaccine. Process evaluation surveys found that both PHUs and LTCHs perceived the RSV vaccine to be of lower priority than influenza and COVID-19 vaccines. There was also concordance between PHU and LTCH respondents regarding barriers to program implementation, which included temporary guidance against routine co-administration, a detailed informed consent procedure, and the timing of program roll-out. An additional barrier for LTCH respondents was vaccine hesitancy among staff and residents or their substitute decision makers. Facilitators to program implementation were effective communication with program partners, availability of technical resources, and programmatic supports. These evaluation findings are being shared to assist other jurisdictions in their planning of potential older adult or LTCH vaccination programs, including RSV vaccination. An important consideration for future program implementation is how to improve vaccine confidence in LTCH residents and staff in a rapidly changing vaccine landscape.
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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 | 0.043 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 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".