<p>The COVID-19 crisis has highlighted the urgency of ensuring equitable and efficient vaccine administration to prevent future global health emergencies. In this research, we introduce a new bi-level programming model for the design of vaccine supply chains (VSCs) during pandemics, which accounts for equity and operational efficiency in the presence of uncertainties. At the upper-level, the framework involves equitable distribution of vaccine across regions and immunization stations, minimizing unmet demand and vaccine procurement, transportation, and inventory costs, and it incorporates queuing theory for minimizing congestion at vaccination centers. The lower-level optimizes production and procurement decisions for domestic manufacturers. To handle demand and cost uncertainties, this model employs fuzzy chance-constrained programming (FCCP) and fuzzy goal programming (FGP) within a hierarchical decision-making framework. A case study of Arak City, Iran, confirms the model, and results show lower costs and better equity than deterministic methods. Sensitivity analyses further clarify the trade-offs between equity, cost, and service efficiency, offering valuable insights for policymakers. This research highlights the necessity of strategic VSC planning to ensure fairness and efficiency, offering a robust framework for managing vaccine distribution in future pandemics.</p>