Influenza vaccination for healthcare workers who care for people aged 60 or older living in long‐term care institutions
Bibliographic record
Abstract
Healthcare workers (HCW) may have high rates of clinical and subclinical influenza during influenza seasons. It is not uncommon for HCW to continue attending work while infected with influenza, increasing the likelihood of transmitting the infection to those in their care. Laboratory proven influenza in the general population accounts for a small proportion of “influenza‐like illnesses.” One study found that 3% of vaccinated working adults had laboratory proven influenza symptoms compared with 4.8% of vaccinated HCW, compared with 5.12% of unvaccinated working adults and 7.54% of HCW having laboratory proven influenza symptoms (Kuster et al., 2011). Elderly individuals have a lower response to vaccination because of less responsive immune systems. One way to reduce the spread of influenza to those aged 60 years and older residing in long‐term care institutions (LTCI) may be to vaccinate HCW. In 2003 in the United States, only 36% of all HCW were vaccinated, and 35% of staff in LTCI in Canada were vaccinated in 1999 (Carman et al., 2000; Stevenson, McArthur, Naus, Abraham, & McGeer, 2001). This review (Thomas, Jefferson, & Lasserson, 2016) is important to provide accurate information for informed decision‐making by policy makers and to highlight the need for high quality research to test combinations of interventions including vaccination of HCWs.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".