Abstract
Due to the dependent happenings in infectious diseases (Ross 1916), widespread vaccination in a population can reduce transmission and produce indirect protective effects, even in unvaccinated individuals. The public health importance of a vaccine is related to the direct protection of the vaccinated individuals as well as the indirect protection conferred by increased herd immunity at the population level. In recent years, interest in estimating the indirect, total, and overall effects of vaccination programs has increased. Most often, the effects have been evaluated using surveillance data by comparing the incidence before and after implementation of a vaccination strategy in a population. In some cases, dramatic effects have been observed such as with pneumococcal vaccines (Musher 2006). Up until now, planned, prospective community-randomized studies to evaluate indirect, total, and overall effects of vaccination strategies are rare. However, interest in implementing such studies, either pre- or post-licensure is increasing. Although mathematical models offer useful guidance on examining potential population effects of vaccination strategies (Chapters 4 and 5), they cannot replace data from an actual study when such a study is feasible.
Struchiner et al (1990) and Halloran and Struchiner (1991) developed a conceptual framework for four classes of study designs to evaluate the direct, indirect, total, and overall effects of interventions called the study designs for dependent happenings. In Chapter 2 we introduced the general concepts of direct, indirect, total, and overall effects of vaccination and the four basic study designs to evaluate them (Figure 2.3). In this chapter, we present the concepts of direct, indirect, total, and overall effects using an informal potential outcomes approach to causal inference. Throughout this chapter we distinguish two levels of intervention, vaccination strategies, allocations or programs at the population level, and vaccination of individuals within populations.We present some of the observational approaches to assessing indirect, total, and overall effects, and their advantages and disadvantages. We then present community-randomized studies as an approach to estimation and inference of indirect, total, and overall effects. We consider basic designs, approaches to randomization, sample size determination, and general considerations of analysis. Finally we formally define causal estimands of direct, indirect, total, and overall effects and their estimators for group-randomized studies.
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© 2010 Springer Science+Business Media, LLC
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Halloran, M.E., Longini, I.M., Struchiner, C.J. (2010). Assessing Indirect, Total, and Overall Effects. In: Design and Analysis of Vaccine Studies. Statistics for Biology and Health. Springer, New York, NY. https://doi.org/10.1007/978-0-387-68636-3_13
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DOI: https://doi.org/10.1007/978-0-387-68636-3_13
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