Increased disparity in routine infant vaccination during COVID-19
Bibliographic record
Abstract
Abstract Background COVID-19 restrictions and its impact on healthcare resources have reduced routine infant vaccine uptake, although some report that this effect was short-lived. These prior studies mostly described entire populations, but disparities in uptake may have changed during the pandemic due to differential access to healthcare. Objectives We aimed to examine disparities in the reduction in routine infant vaccine uptake during the COVID-19 pandemic in Manitoba, Canada. Methods We assessed vaccine uptake for routine infant vaccines for a pre-pandemic and pandemic subcohort. We assessed how the reduction in vaccine uptake differed by gender, neighborhood income quintile and region of residence. For each evaluation age, we limited the pandemic subcohort to children reaching this milestone age on/before November 30, 2021. Results Vaccine uptake was about 5-10% lower during the pandemic. The groups most vulnerable to COVID-19 saw the largest reductions in vaccine uptake, with an ongoing downward trend throughout the pandemic. Children in the lowest income neighborhoods saw a 17% reduction in diphtheria, tetanus, and acellular pertussis dose 4 uptake at 24 months, 4.4-fold that of high-income neighborhoods, and an 11% reduction in measles, mumps, rubella (MMR) vaccine uptake at 24 months, 5.6-fold that of high-income neighborhoods. The largest reductions were for low-income Northern residents and smallest for high-income Winnipeg residents, e.g. 16-fold larger for MMR at 24 months (79:94 pre-pandemic to 65:93 during the pandemic). Conclusions While privileged children have similar high vaccine uptake as before the pandemic, children in populations hardest hit by COVID-19 continue seeing concerning reductions in routine infant vaccination. It is imperative that infant vaccination rates are increased, especially in communities with lower socioeconomic status, as a failure to do so could lead to persistent rebound epidemics in the most vulnerable populations. Synopsis Study question How did COVID-19 and its restrictions affect routine infant vaccine uptake? What’s already known We know that vaccine uptake in infants decreased during the pandemic. We do not know whether this affected everyone equally or whether the pandemic worsened existing disparities in vaccine uptake. What this study adds Although vaccine uptake was not affected in wealthy urban neighborhoods, the reduction in uptake was largest, and continued on a downward trend, for groups with the lowest baseline vaccine uptake. Only two-thirds of children, instead of the 4/5th before the pandemic, in the remote, predominantly Indigenous Northern region received a measles vaccine by their second birthday.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".