The COVID-19 pandemic highlighted the pivotal role of transportation-related controls and vaccination in mitigating widespread infections. However, the substantial costs associated with these interventions necessitate a nuanced equilibrium between control measures and infection risks. This study, driven by the recognition of spatial heterogeneities in mobility networks and epidemic vulnerability, presents an optimal control framework for two control measures—vaccine distribution and transportation restrictions—within a metapopulation structure. The overarching goal is to minimize the total costs derived from the implementation of control measures and health and opportunity loss from infection. Our findings highlight the effectiveness of transportation control and vaccine distribution in reducing both total costs and infection rates. Notably, the efficacy of these control measures exhibits regional variations, and the simultaneous implementation of both measures emerges as the most effective and economically viable strategy. The synergy effect between vaccine distribution and transportation restrictions is also a key observation in our simulations, showcasing their complementary roles in pandemic control. By considering the spatial nuances of mobility networks and infection vulnerability, this framework provides a flexible and region-specific strategy to optimize the allocation of resources for pandemic control, ultimately striking a balance between efficacy and economic feasibility.