Varying Vaccination Rates Among Patients Seeking Care for Acute Respiratory Illness: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
Abstract Background Complications following influenza infection are a major cause of morbidity and mortality, and the Centers for Disease Control Advisory Committee on Immunization Practices recommends universal annual vaccination. However, vaccination rates have remained significantly lower than the Department of Health and Human Services goal. The aim of this work was to assess the vaccination rate among patients who present to health care providers with influenza-like illness and identify groups with lower vaccination rates. Methods We performed a systematic search of the PubMed and EMBASE databases with a time frame of January 1, 2010, to March 1, 2019 and focused on the vaccination rate among patients seeking care for acute respiratory illness in the United States. A random effects meta-analysis was performed to estimate the pooled seasonal influenza vaccination rate, and we used a time trend analysis to identify differences in annual vaccination over time. Results The overall pooled influenza vaccination rate was 48.61% (whites: 50.87%; blacks: 36.05%; Hispanics: 41.45%). There was no significant difference among gender groups (men: 46.43%; women: 50.11%). Interestingly, the vaccination rate varied by age group and was significantly higher among adults aged >65 (78.04%) and significantly lower among children 9–17 years old (36.45%). Finally, we found a significant upward time trend in the overall influenza vaccination rate among whites (coef. = .0107; P = .027). Conclusions In conclusion, because of the significantly lower influenza vaccination rates in black and Hispanic communities, societal initiatives and community outreach programs should focus on these populations and on children and adolescents aged 9–17 years.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.003 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".