Parental decisions regarding the vaccination of children and adolescents against SARS-CoV-2 from 2020 to 2023: A descriptive longitudinal study of parents and children in Montreal, Canada
Bibliographic record
Abstract
BACKGROUND: Given the growing evidence on the benefits of hybrid immunity, continued monitoring of vaccine uptake is warranted, particularly of socio-demographic subgroups with early vaccine hesitancy. Racial/ethnic and lower income groups experienced a high infection incidence, but few studies account for the child's history of SARS-CoV-2 infection on the parent's decision to vaccinate their child. METHODS: EnCORE is a SARS-CoV-2 pediatric cohort study comprising five rounds of data collection from 2020 to 2023, with parental questionnaires at each round. Parent's responses on their intention to vaccinate their child and their reasons were summarized descriptively. Vaccine uptake was estimated through time and in relation to participant characteristics, using multivariable regression to adjust for covariates including a history of PCR/serology-confirmed SARS-CoV-2 infection prior to vaccine eligibility. At study end, we estimated the average time lapsed from last vaccine dose. RESULTS: The samples for vaccine uptake and intention to vaccinate analyses were 631 and 1137 participants, respectively. At study end, uptake was 88 % but approximately 49 % of 2-to-4-year-olds remained unvaccinated (95 % CI 39.0, 58.1) and for vaccinated participants the median time since last vaccination was 353 days. In regression analyses, after adjusting for infection prior to vaccine eligibility and other covariates, we found approximately a two-fold increase in unvaccinated status associated with the parent's identification as a racial/ethnic minority and with household income in the lowest sample tercile (minority: adjusted relative risk [aRR] 2.45, 95 % CI 1.56, 3.86; income: aRR 1.76, 95 % CI 1.17, 2.66). CONCLUSION: By mid-2023, most participants were not protected by vaccine-induced antibodies, because they were unvaccinated or several months had lapsed from their last dose. A COVID-19 infection prior to vaccine eligibility was associated with a greater risk of remaining unvaccinated but did not fully account for low uptake in ethnic/racial minorities and lower income groups.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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".