Racial and Ethnic Disparities in Meningococcal Vaccination Coverage and Disease Burden Among U.S. Adolescents
Bibliographic record
Abstract
PURPOSE: Examining racial disparities in meningococcal vaccination (MenACWY) uptake and disease burden is essential for understanding the potential implications of a revised MenACWY schedule and guiding targeted efforts to reduce health inequities. We assessed associations of socioeconomic factors with MenACWY coverage (≥1 dose), drop-out from the second (booster) dose, and disparities in vaccination coverage and invasive meningococcal disease (IMD) burden among adolescents aged 13-17 years living in noninstitutionalized households in the United States. METHODS: We conducted a retrospective cross-sectional study (2016-2022) using National Immunization Survey-Teen data for vaccine uptake, and Centers for Disease Control and Prevention data for IMD incidence. Segmented logistic regression analyzed MenACWY uptake and drop-out trends. Multivariable models assessed associations with poverty-income ratio, maternal education, and access barriers. Adjusted odds ratios (aORs) compared uptake and drop-out across racial groups, and Poisson regression estimated adjusted relative risks for IMD incidence. RESULTS: Compared to non-Hispanic (NH) White adolescents, NH African American (aOR: 1.33; 95% confidence interval [CI]: 1.23-1.44) and Hispanic (aOR: 1.20; 95% CI: 1.13-1.29) adolescents had higher odds of receiving ≥1 MenACWY dose. Hispanic adolescents had lower odds of drop-out (aOR: 0.79; 95% CI: 0.70-0.89), while NH African American (p = .148) and Other/Multiple races adolescents (p = .098) showed no significant difference. Drop-out was higher among low-income adolescents (p < .001) and those whose mothers did not have college education (aOR: 1.26; 95% CI: 1.14-1.39). Among 16-23-year-olds, IMD incidence was significantly higher in African Americans compared to Whites (adjusted relative risk: 2.66; 95% CI: 1.39-5.07). DISCUSSION: Persistent disparities in MenACWY coverage and disease burden among US adolescents by race and socioeconomic status highlight the need for targeted efforts within the two-dose program.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".