Author:
Kahn Rebecca,Hitchings Matt,Wang Rui,Bellan Steven,Lipsitch Marc
Abstract
ABSTRACTVaccine efficacy against susceptibility to infection (VES), regardless of symptoms, is an important endpoint of vaccine trials for pathogens with a high proportion of asymptomatic infection, as such infections may contribute to onward transmission and outcomes such as Congenital Zika Syndrome. However, estimating VESis resource-intensive. We aim to identify methods to accurately estimate VEswhen limited information is available and resources are constrained. We model an individually randomized vaccine trial by generating a network of individuals and simulating an epidemic. The disease natural history follows a Susceptible, Exposed, Infectious and Symptomatic or Infectious and Asymptomatic, Recovered model. We then use seven approaches to estimate VES, and we also estimate vaccine efficacy against progression to symptoms (VEP). A corrected relative risk and an interval censored Cox model accurately estimate VESand only require serologic testing of participants once, while a Cox model using only symptomatic infections returns biased estimates. Only acquiring serological endpoints in a 10% sample and imputing the remaining infection statuses yields unbiased VESestimates across values of R0and accurate estimates of VEPfor higher values. Identifying resource-preserving methods for accurately estimating VESis important in designing trials for diseases with a high proportion of asymptomatic infection.
Publisher
Cold Spring Harbor Laboratory