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Improving Influenza Vaccination in Children With Comorbidities: A Systematic Review
Daniel A Norman1,2, Rosanne Barnes3, Rebecca Pavlos3
1Wesfarmers Centre of Vaccines and Infectious Diseases, Telethon Kids Institute, Western Australia, Australia; daniel.norman@telethonkids.org.au.
Insights
Influenza vaccination coverage in children with medical conditions improved with reminders and education, but effectiveness varied. More research is needed to identify optimal strategies for these high-risk children.
Area of Science:
- Pediatrics
- Public Health
- Vaccinology
Background:
- Children with medical comorbidities face higher risks of severe influenza and adverse outcomes.
- Despite existing recommendations and funding, influenza vaccine uptake remains insufficient in this vulnerable pediatric population.
Purpose of the Study:
- To systematically review interventions aimed at improving influenza vaccine coverage in children with comorbidities.
- To assess the impact of these interventions on influenza vaccination rates.
Main Methods:
- A comprehensive literature search was conducted across multiple major databases (PubMed, Scopus, Embase, CINAHL, Cochrane, AMED, Web of Science).
- Studies focusing on interventions for influenza vaccination in children with medical comorbidities were selected.
- Data extraction and risk of bias assessment were performed independently by multiple reviewers.
Main Results:
- Out of 961 screened articles, 35 met the inclusion criteria.
- Interventions including vaccination reminders, parent/provider education, and clinic process changes significantly improved influenza vaccine coverage by an average of 60%.
- No significant differences in coverage were found between different intervention types, with notable study bias and heterogeneity.
Conclusions:
- Interventions consistently enhance influenza vaccine coverage in children with comorbidities.
- The study identified a high risk of bias and low evidence quality, limiting definitive conclusions on intervention effectiveness.
- Further well-designed research is necessary to determine the most effective interventions for optimizing influenza vaccination in this population.
Context:
Children with medical comorbidities are at greater risk for severe influenza and poorer clinical outcomes. Despite recommendations and funding, influenza vaccine coverage remains inadequate in these children.
Objective:
We aimed to systematically review literature assessing interventions targeting influenza vaccine coverage in children with comorbidities and assess the impact on influenza vaccine coverage.
Data Sources:
PubMed, Scopus, Embase, Cumulative Index to Nursing and Allied Health Literature, Cochrane Central Register of Controlled Trials, Allied and Complementary Medicine Database, and Web of Science databases were searched.
Study Selection:
Interventions targeting influenza vaccine coverage in children with medical comorbidities.
Data Extraction:
Two reviewers independently screened articles, extracting studies' methods, interventions, settings, populations, and results. Four reviewers independently assessed risk of bias.
Results:
From 961 screened articles, 35 met inclusion criteria. Published studies revealed that influenza vaccine coverage was significantly improved through vaccination reminders and education directed at either patients' parents or providers, as well as by vaccination-related clinic process changes. Interventions improved influenza vaccine coverage by an average 60%, but no significant differences between intervention types were detected. Significant bias and study heterogeneity were also identified, limiting confidence in this effect estimate.
Limitations:
A high risk of bias and overall low quality of evidence limited our capacity to assess intervention types and methods.
Conclusions:
Interventions were shown to consistently improve influenza vaccine coverage; however, no significant differences in coverage between different intervention types were observed. Future well-designed studies evaluating the effectiveness of different intervention are required to inform future optimal interventions.
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