Factors Influencing Childhood Influenza Vaccination: A Systematic Review

Han, Kaiyi; Hou, Zhiyuan; Tu, Shiyi; Liu, Mengyun; Chantler, Tracey; Larson, Heidi

doi:10.3390/vaccines12030233

Cited by 1 publication

(2 citation statements)

References 61 publications

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“…The factors associated with influenza vaccination included the child’s age, child’s previous influenza vaccine uptake, parental age, educational level, annual household income, parental vaccine hesitancy, and influenza vaccination willingness. Among these factors, previous vaccine uptake emerged as a strong positive factor, as supported by previous studies [ 12 , 22 , 23 ]. Individuals who personally witnessed the positive impact due to vaccination, such as a decreased likelihood of infection, were more likely to continue receiving vaccinations.…”

Section: Discussionsupporting

confidence: 75%

“…Additionally, children from households with higher levels of parental education or income were more prone to receiving the influenza vaccine in our study. However, evidence regarding the relationship between parental education, income, and children’s influenza vaccination is inconsistent [ 22 , 23 ]. We also analyzed the factors influencing parents who expressed a willingness to vaccinate their children but ultimately did not do so.…”

Section: Discussionmentioning

confidence: 99%

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A Prediction Model for Identifying Seasonal Influenza Vaccination Uptake Among Children in Wuxi, China: Prospective Observational Study

Wang,

Yang,

Xiu

et al. 2024

JMIR Public Health Surveill

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Background Predicting vaccination behaviors accurately could provide insights for health care professionals to develop targeted interventions. Objective The aim of this study was to develop predictive models for influenza vaccination behavior among children in China. Methods We obtained data from a prospective observational study in Wuxi, eastern China. The predicted outcome was individual-level vaccine uptake and covariates included sociodemographics of the child and parent, parental vaccine hesitancy, perceptions of convenience to the clinic, satisfaction with clinic services, and willingness to vaccinate. Bayesian networks, logistic regression, least absolute shrinkage and selection operator (LASSO) regression, support vector machine (SVM), naive Bayes (NB), random forest (RF), and decision tree classifiers were used to construct prediction models. Various performance metrics, including area under the receiver operating characteristic curve (AUC), were used to evaluate the predictive performance of the different models. Receiver operating characteristic curves and calibration plots were used to assess model performance. Results A total of 2383 participants were included in the study; 83.2% of these children (n=1982) were <5 years old and 6.6% (n=158) had previously received an influenza vaccine. More than half (1356/2383, 56.9%) the parents indicated a willingness to vaccinate their child against influenza. Among the 2383 children, 26.3% (n=627) received influenza vaccination during the 2020-2021 season. Within the training set, the RF model showed the best performance across all metrics. In the validation set, the logistic regression model and NB model had the highest AUC values; the SVM model had the highest precision; the NB model had the highest recall; and the logistic regression model had the highest accuracy, F1 score, and Cohen κ value. The LASSO and logistic regression models were well-calibrated. Conclusions The developed prediction model can be used to quantify the uptake of seasonal influenza vaccination for children in China. The stepwise logistic regression model may be better suited for prediction purposes.

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Section: Discussionsupporting

confidence: 75%

Section: Discussionmentioning

confidence: 99%