Balancing fairness and efficiency in dynamic vaccine allocation during major infectious disease outbreaks

The outbreak of novel infectious diseases presents major public health challenges, highlighting the urgency of accelerating vaccination efforts to reduce morbidity and mortality. Vaccine allocation has become a crucial societal concern. This paper introduces a dynamic vaccine allocation model that considers demand uncertainty and vaccination willingness, focusing on the trade-off between fairness and efficiency. We develop a multi-period dynamic vaccine allocation model, evaluating optimal strategies over different periods. The model addresses structural differences among vaccination groups, strategy selection, dynamic demand, and vaccination willingness. Our findings suggest that prioritizing efficiency in the initial outbreak stages may lead to inequitable distribution, causing adverse social impacts, while overemphasizing fairness can undermine overall utility. Therefore, we propose a dynamic optimization-based strategy balancing fairness and efficiency at different pandemic stages. Our results indicate that allocation strategies should shift from efficiency to fairness as the pandemic evolves to enhance vaccine utility. Additionally, macro-level interventions like reducing free-rider behavior and increasing vaccination convenience can improve total vaccine utility. This study offers new perspectives and methodologies for dynamic vaccine allocation, highlighting the trade-off between fairness and efficiency, providing crucial insights for policy formulation and pandemic response.