Vaccine Efficacy at a Point in Time

Follmann, D.; Fay, M. P.

Vaccine trials are generally designed to assess efficacy on clinical disease. The vaccine effect on infection, while important both as a proxy for transmission and to describe a vaccine's total effects, requires frequent longitudinal sampling to capture all infections. Such sampling may not always be feasible. A logistically easy approach is to collect a sample to test for infection at a regularly scheduled visit. Such point or cross-sectional sampling does not permit estimation of classic vaccine effciacy on infection, as long duration infections are sampled with higher probability. Building on work by Rinta et al 2009, we evaluate proxies of the vaccine effect on transmission at a point in time; the vaccine efficacy on prevalent infection and on prevalent viral load, VE$_{PI}$ and VE$_{PVL}$, respectively. Longer infections with higher viral loads should have more transmission potential and prevalent vaccine efficacy naturally captures this aspect. We apply a proportional hazards model for infection risk and show how these metrics can be estimated using longitudinal or cross-sectional sampling. We also introduce regression models for designs with multiple cross-sectional sampling. The methods are evaluated by simulation and a phase III vaccine trial with PCR cross-sectional sampling for subclinical infection is analyzed.