In the COVID-19 pandemic, models were often at the forefront of decision making and public discussion. Models helped with case projections, estimating the impacts of non-pharmaceutical interventions, estimating real-time measures of transmission (like Rt, the effective reproduction number). Models helped us think about the vaccine rollout, to project healthcare burden in the context of evolution of new variants, and to reason about what might happen next. Our network of infectious disease modellers collected the questions that decision-makers asked. I will describe a selection of these chronologically, describing new models that were developed to help support decision-making, the data needs that this raised, and challenges related to communicating uncertainty to decision-makers and the public.