Accepted for/Published in: JMIR Public Health and Surveillance
Date Submitted: Jan 4, 2024
Date Accepted: May 15, 2024
Identify Seasonal Influenza Vaccination among Children in Wuxi, China using the Prediction Model: A Prospective Observational Study
ABSTRACT
Background:
Predicting vaccination behaviors accurately could provide insights for healthcare professionals to develop targeted interventions.
Objective:
The study aimed 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 socio-demographics, parental vaccine hesitancy, perceptions of convenience to the clinic, satisfaction with the clinic services, and willingness to vaccinate. Bayesian networks, logistic regression, lasso regression, support vector machines (SVM), naive Bayes (NB), random forest (RF), and decision tree classifiers were employed to construct prediction models. Various performance metrics, such as area under the receiver operating characteristic curve (AUC), were used to evaluate the predictive performance of various models. Receiver operating characteristic curves and calibration plots were plotted to assess model performance.
Results:
A total of 2,383 study participants were included. 83.2% of children (1,982/2,383) were < 5 years and 6.6% (158/2,383) received influenza vaccine before. More than half (56.9%, 1,356/2,383) of parents showed willingness to vaccinate their child against influenza. 26.3% (627/2,383) of children 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 value. The SVM model had the highest precision and the NB model had the highest recall. The Logistic regression model had the highest accuracy, F1 score, and Cohen’s kappa. The Lasso regression model and Logistic regression model were well-calibrated.
Conclusions:
The prediction model can be used to quantify seasonal influenza vaccination for children in China. The stepwise logistic regression model may be better suited for prediction purposes.
Citation
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