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

Quantifying efficiency gains of innovative designs of two-arm vaccine trials for COVID-19 using an epidemic simulation model