Journal
JOURNAL OF BIOPHARMACEUTICAL STATISTICS
Volume 16, Issue 4, Pages 453-462Publisher
TAYLOR & FRANCIS INC
DOI: 10.1080/10543400600719343
Keywords
community-randomized trial; indirect effects; pneumococcal vaccine
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When a sufficiently high proportion of a population is immunized with a vaccine, reduction in secondary transmission of disease can confer significant protection to unimmunized population members. We propose a straightforward method to estimate the degree of this indirect effect of vaccination in the context of a community-randomized vaccine trial. A conditional logistic regression model that accounts for within-randomization unit correlation over time is described, which models risk of disease as a function of community-level covariates. The approach is applied to an example data set from a pneumococcal conjugate vaccine study, with study arm and immunization levels forming the covariates of interest for the investigation of indirect effects.
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