OBJECTIVES: The aim of the study is to utilize the novel frontier analysis to search for optimal strategy of vaccination policy against infectious diseases with limited vaccine supply. METHODS: An important goal of public health research is to predict clinical impact by nation-wide mass vaccination in preventing infectious diseases. Vaccination is usually given across potential vulnerable populations such as children. However, due to limited resources provided by the government among a growing number of competing vaccine products, some vaccinations are to be given to some targeted high-risk cohorts against infectious diseases, such as pneumonia or influenza. Hence, the optimal strategy of vaccination policy for effective disease control becomes a practical concern. We propose a model using frontier analysis to seek the optimal vaccination policy in controlling infectious disease epidemics with limited resources. The problem is initially formulated to find the maximal life years gained while minimizing the variance. Various vaccination policies were explored in finding the optimal vaccination strategy. The indirect effects on unvaccinated cohorts were also considered in the analysis. The technique is illustrated using pneumococcal conjugate vaccine (PCV) in Taiwan as an example. RESULTS: Using the empirical study of PCV and various scenarios of the policy with limited resource, we provide the best vaccination strategy among various defined cohorts and report the maximal life years gained with the fixed total cost of the vaccine given. Our study can be generalized to the optimization of vaccination strategies for most infectious diseases among different population structures. CONCLUSIONS: When disease burden is high, more emphasis should be laid on the possible health benefits gained with a vaccination program, instead of just considering the economic benefits. Our study can help to guide decision makers in determining optimal uses of limited quantities of vaccine across multiple targeted cohorts to effectively control infectious diseases.