Using Validation Sets in Vaccine Studies with Rapid Temporal Changes in Transmission
(Elizabeth Halloran, Emory University)

Methods for adjusting for bias in estimates due to mismeasured or missing covariates and outcomes using validation sets  have been developed in many types of health studies. These methods can be used for the efficient design and analysis of vaccine studies as well. Non-specific case definitions can lead to attenuated efficacy and effectiveness estimates, but confirmation by culture or a quick test of the infectious agent is also expensive and difficult. Use of  small validation sets can correct the bias of the estimates obtained from a large main study at some cost in precision of the estimates. Using validation sets in infectious diseases such as influenza poses many challenges because the incidence of disease can change rapidly with time. In particular, the relation of the incidence of nonspecific influenza-like infections  and true influenza changes rapidly. We propose new statistical methods that account for the rapid temporal evolution. We illustrate the approach for outcomes on the example of influenza vaccine efficacy.