Vaccination is one of the most effective ways to protect people from being infected by infectious disease. However, it is often impractical to vaccinate all people in a community due to various resource constraints. Therefore, targeted vaccination, which vaccinates a small group of people, is an alternative approach to contain infectious disease spread. To achieve better performance in targeted vaccination, we collect student contact traces in a high school based on wireless sensors carried by students. With our wireless sensor system, we can record student contacts within the disease propagation distance, and then construct a disease propagation graph to model the infectious disease propagation. Based on this graph, we propose a metric called connectivity centrality to measure a node's importance during disease propagation and design centrality based algorithms for targeted vaccination. The proposed algorithms are evaluated and compared with other schemes based on our collected traces. Trace driven simulation results show that our algorithms can help to effectively contain infectious disease