CMV primary and non-primary infections among daycare workers, and development of strategies to prevent infection (EDUQ-CMV): a mixed-method study protocol
Bibliographic record
Abstract
BACKGROUND: Cytomegalovirus (CMV) is associated with congenital infections that can lead to severe developmental and neurological complications in affected children. Daycare workers, who frequently interact with infants and young children, may be at higher risk of CMV infection. This study aims to investigate the rates of primary infection and reinfection of CMV among female daycare workers in the province of Québec, Canada to better understand the risk of occupational exposure in this population. METHODS: This mixed-method observational study protocol uses quantitative (prospective cohort) and qualitative (semi-structured interviews with daycare workers) components. Female daycare workers (n = 553) are recruited and enrolled in a prospective cohort study, with a non-daycare workers comparison group comprising hospital employees and plasma donors who do not have direct professional contact with children < 36 months of age (low-risk group, n = 1659, 1:3 ratio). Participants are followed for 12 months, with blood for CMV serology, strain-specific antibody profiling with CMV-specific ELISA, CMV quantitative polymerase chain reaction (qPCR) and CMV-Scan assay collected from all participants at the first (V0) and last (V12) study visits. Among daycare workers and hospital employees, saliva samples are collected at these visits and monthly throughout the study for testing via CMV qPCR. Testing enables the identification of primary infections, reinfections, and reactivations, and estimates the association between demographic and occupational factors and CMV infection. Additionally, qualitative data is collected through interviews with daycare workers and daycare managers, focusing on their perceptions of CMV risks and current infection control practices. DISCUSSION: This study is expected to improve the understanding of CMV epidemiology among a high-risk group (i.e. female daycare workers). By estimating the incidence of CMV infections and patterns of viral shedding, the findings may inform occupational health strategies and public health policies. Based on our findings, guidelines aimed at preventing CMV infections could help protect not only daycare workers but also vulnerable populations, including young children and immunocompromised individuals, with whom they interact.
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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 | 0.030 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 0.003 |
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".