Using validation sets for outcomes and exposure to infection in vaccine field studies

Methods of adjusting for bias in estimates due to mismeasured or missing co variates and outcomes through the use of validation sets have been develope d in many types of health studies. These methods can be employed for the ef ficient design and analysis of vaccine studies as well. On the one hand, no nspecific case definitions can lead to attenuated efficacy and effectivenes s estimates, but confirmation by culture or a quick test of the infectious agent is also expensive and difficult. On the other hand, data on exposure to infection can influence estimates of vaccine efficacy, but good data on exposure are difficult to obtain. In this paper, the authors show how use o f small validation sets can correct the bias of the estimates obtained from a large main study while maintaining efficiency. They illustrate the appro ach for outcomes using the example of influenza vaccine efficacy and effect iveness trials and illustrate the approach for exposure to infection using the example of a human immunodeficiency virus vaccine trial. The authors di scuss challenges posed by infectious diseases in the use of currently avail able methods. Development of these efficient designs and methods of analysi s for vaccine field studies will improve estimation of vaccine efficacy for both susceptibility and infectiousness, as well as estimation of indirect and overall effects of vaccination in community trials.