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Exploring the impact of reimbursement ratios on willingness to vaccinate: A mixed-effects modeling approach using panel data
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Linbo XieM
Mengsha Yan*P
Peiyao LiJ
Junfang XuX
Xin FangZ
Ziting GuoM
Min Yuan*J
Jiming Zhu* DOI：10.1080/21645515.2025.2609339.png)
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Abstract
En 中文
Vaccination remains one of the most cost-effective methods for disease prevention. However, utilization of self-paid vaccines, including EV71, varicella, influenza, and DTaP-IPV-Hib in this study, remains insufficient among children under six in China. To investigate the determinants of willingness to vaccinate (WTV) for self-paid vaccines and assess cost-WTV heterogeneity, we conducted structured-questionnaire surveys with 2212 randomly selected households in Hangzhou, each with at least one child under six. Multiple regression analysis was used to identify the key determinants of WTV, and a mixed-effect model was employed to analyze the correlation between vaccine cost and WTV, further segmenting the data with unsupervised clustering techniques. Our findings highlighted impact of vaccination cost as a pivotal factor influencing the WTV for self-paid vaccines. We categorized the population into four groups based on their sensitivity to vaccine cost. Families with one child, children aged 1–3 y, highly-educated parents, and higher socioeconomic status consistently exhibited high WTV. Our analysis offers targeted strategies to enhance vaccine uptake and improve immunization coverage.
Keywords:
Childhood immunization
mixed-effect model
self-paid vaccines
machine learning
willingness to vaccinate
vaccine hesitancy
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