To rapidly evaluate the safety and efficacy of COVID-19 vaccine candidates, prioritizing vaccine trial sites in areas with high expected disease incidence can speed endpoint accrual and shorten trial duration . Mathematical and statistical forecast models can inform the process of site selection, integrating available data sources and facilitating comparisons across locations . We recommend the use of ensemble forecast modeling – combining projections from independent modeling groups – to guide investigators identifying suitable sites for COVID-19 vaccine efficacy trials . We describe an appropriate structure for this process, including minimum requirements, suggested output, and a user-friendly tool for displaying results . Importantly, we advise that this process be repeated regularly throughout the trial, to inform decisions about enrolling new participants at existing sites with waning incidence versus adding entirely new sites . These types of data-driven models can support the implementation of flexible efficacy trials tailored to the outbreak setting.