Optimizing vaccine allocation: a review of epidemiological models with behavioral adaptation

Accurate vaccine distribution remains central to epidemic management, particularly when resources are limited and public response varies. This revised review evaluates three epidemiological modeling approaches that guide vaccine allocation decisions: DELPHI-V-OPT (an integrated epidemiological-optimization framework), a hybrid Agent-Based plus Differential Equation model, and Probabilistic (stochastic) Control models. Building on the original manuscript, this revision adds a transparent literature-search methodology, a strengthened, chronological literature review, clearer technical descriptions (especially the bidirectional coupling between agent-based simulations and compartmental equations), and a comprehensive limitations and future-work section for each model. We justify the selection of DELPHI-V-OPT as the primary practical framework for policy use, then introduce and analytically integrate a behavioral variable representing vaccine hesitancy into the allocation optimization. The extension recalibrates effective demand, reduces dose wastage, and provides operational recommendations for estimating hesitancy and adapting allocations in resource-limited and resource-rich settings. The revised manuscript includes a summary comparison table of model features, explicit search strategy, and targeted references that support methodological choices and model adaptations.