Effect of early measles vaccination on long-term protection: A systematic review
Bibliographic record
Abstract
BACKGROUND: In North America, the first dose of a measles-containing vaccine (MCV1) is administered at ≥12 months of age. However, MCV1 may be given to infants <12 months living in highly endemic areas or traveling to these areas. Although an early dose of MCV1 leads to immediate protection, it remains unclear how this impacts long-term immunity. METHODS: This systematic review and meta-analysis evaluates the impact of MCV1 given at <12 months vs. ≥12 months of age on long-term immunogenicity and vaccine effectiveness, with long-term defined as at least one-year post-vaccination. PubMed, EMBASE, Global Health, Web of Science and Scopus were searched on October 31st, 2019. Studies were included if they included a cohort of infants vaccinated <12 months of age and evaluated long-term immunogenicity, vaccine efficacy, or effectiveness. RESULTS: A total of 51 texts were identified: 23 reported outcomes related to vaccine effectiveness and 30 to immunogenicity. Infants vaccinated with MCV1 < 12 months of age showed an overall higher risk of measles compared to ≥12 months of age (RR = 3.16, 95% CI: 2.00, 5.01; OR = 2.46, 95% CI: 1.40, 4.32). Risk of measles decreased with increasing age at first vaccination, with those vaccinated with one dose ≥15 months at a lesser risk compared to 12-14 months or <12 months. Measles seroconversion and seropositivity was not affected by age at first vaccination, but antibody levels were significantly lower in the MCV1 < 12-month group (MD = -0.40, 95% CI: -0.71, -0.09). CONCLUSION: Long-term measles seroconversion and seropositivity did not appear to be affected by age at MCV1, while vaccine effectiveness decreased with younger age. There was not enough evidence to look at the effect of age at MCV1 on immune blunting.
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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 | 0.006 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.014 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".