Vaccine hesitancy in war-torn Ukraine: A machine learning framework for resilient immunization

Background Vaccination prevents millions of deaths, yet conflict magnifies inequities and erodes trust. Ukraine’s war has jeopardized immunization, exposing urgent gaps in vaccine confidence. We conducted a nationwide survey and applied traditional statistics and interpretable machine-learning models to identify drivers of hesitancy. Our approach uncovers complex behavioral determinants and offers actionable, context-specific insights to strengthen vaccination strategies in Ukraine and other crisis settings. Method We conducted a cross-sectional household survey (November–December 2024) across 557 purposively selected hromadas in Ukraine, excluding occupied or frontline areas. Eligible respondents were parents (≥ 18 years) responsible for vaccination decisions for children aged 0–17. Of 4,972 households approached, 2,526 met the inclusion criteria and completed a structured questionnaire administered online. The 135-item instrument integrated validated scales (WHO Vaccine Confidence Scale, Parent Attitudes about Childhood Vaccines) and Ukraine-specific items. Data were analyzed using descriptive statistics, χ² tests, and machine learning models with cross-validation to identify determinants of vaccine confidence and uptake. Results Among 2,526 surveyed Ukrainian parents, 24% perceived vaccines as risky, 44% reported low trust in vaccine information, and only 34.5% of children were fully vaccinated in the past year. Attitudes and uptake were strongly influenced by cultural norms, perceived safety, social media, and healthcare trust. Using machine learning, the BART model identified novel, high-impact predictors of vaccine hesitancy, including perceived risk, lack of safety information, institutional distrust, and urban–rural access gaps. Interaction analyses revealed that these factors synergistically shape parental beliefs, attitudes, and vaccination practices, offering unprecedented insights into determinants of vaccine uptake in conflict-affected settings. Conclusion Our findings reveal that parental vaccine confidence and uptake are shaped by perceived risks, cultural norms, trust in healthcare professionals, and access disparities. Machine learning identified these factors as key predictors, highlighting targets for interventions to address hesitancy and improve equitable childhood immunization in Ukraine.