Maximizing statistical power in group-randomized vaccine trials

Abstract

Statistical power in group-randomized vaccine trials is complex: group randomization may increase power by capturing more transmission effects but may decrease power as more individuals are affected by a common source of variance. The former effect dominates when most infections arise from within the group and the latter when most arise outside. This process is complicated further when individuals possess partial natural immunity. Vaccine trials typically compare infection frequency (as measured by agent or antibody detection) in vaccinated vs. unvaccinated groups. To assess the relative contributions to statistical power by direct agent detection vs. serological detection of recent infection, we constructed stochastic compartmental models using differential equations describing all possible discrete states of the group. We contrasted models where natural immunity was absent, altered only the susceptible state, or altered both the susceptible and infected states. We observed the effects of endemic infection levels, the fraction of infection arising from outside the group, infectiousness vs. susceptibility vaccine effects and waning rates. There was significant enhancement of statistical power when serological testing separated infected and susceptible classes into subsets by natural immunity status.