  Clinical trials of a vaccine during an epidemic face particular challenges,
such as the pressure to identify an effective vaccine quickly to control the
epidemic, and the effect that time-space-varying infection incidence has on the
power of a trial. We illustrate how the operating characteristics of different
trial design elements may be evaluated using a network epidemic and trial
simulation model, based on COVID-19 and individually randomised two-arm trials
with a binary outcome. We show that "ring" recruitment strategies, prioritising
participants at high risk of infection, can result in substantial improvement
in terms of power, if sufficiently many contacts of observed cases are at high
risk. In addition, we introduce a novel method to make more efficient use of
the data from the earliest cases of infection observed in the trial, whose
infection may have been too early to be vaccine-preventable. Finally, we
compare several methods of response-adaptive randomisation, discussing their
advantages and disadvantages in this two-arm context and identifying particular
adaptation strategies that preserve power and estimation properties, while
slightly reducing the number of infections, given an effective vaccine.
