Although vaccine field studies conform in many ways to the paradigm of clinical trials of treatments, they also have their own characteristics. First, the vaccine can be evaluated for both how it reduces susceptibility, VE_S, and how it reduces infectiousness, VE_I, as well as how it slows progression, VE_P. Secondly, the transmission probability or secondary attack rate is a parameter that can be used to estimate both VE_I and VE_S. Thirdly, vaccination can have indirect as well as direct effects in populations, so that even unvaccinated people benefit from widespread vaccination. Studies can be designed to evaluate both individual and population level effects of vaccination. Fourthly, the various VE parameters can be though of as a heirarchy depending on how much information about the contact and transmission process is used for their estimation. This lead to the idea of efficient design of vaccine studies by combining sets of study participants with differing levels of exposure to infection data using missing data and errors-in-variables methods. We present the design and data analysis methods for these different special characteristics of vaccine studies.

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