A pandemic poses particular challenges to decision-making with regard to the types of decisions and geographic levels ranging from regional and national to international. As decisions should be underpinned by evidence, several steps are necessary: First, data collection in terms of time dimension as well as representativity with respect to all necessary geographical levels is of particular importance. Aspects such as data quality, data availability and data relevance must be considered. These data can be used to develop statistical, mathematical and decision-analytical models enabling prediction and simulation of the consequences of interventions. We especially discuss the role of data in the different models. With respect to reporting, transparent communication to different stakeholders is crucial. This includes methodological aspects (e.g. the choice of model type and input parameters), the availability, quality and role of the data, the definition of relevant outcomes and tradeoffs and dealing with uncertainty. In order to understand the results, statistical literacy should be