For appropriate response to the COVID-19 pandemic, and for obtaining answers to various relevant research questions, empirical data are required. Claims data of health insurances are a valid data source in such a situation. Within the project egePan-Unimed of the Netzwerk Universitätsmedizin (NUM) we investigated five COVID-19-related research questions using German claims data of statutory health insurances. We studied the prevalence and relevance of risk factors for a severe course of COVID-19, the background incidence of cerebral venous sinus thrombosis and myocarditis, the frequency and symptoms of post-COVID as well as the care of people with a psychiatric condition during the COVID-19 pandemic. Based on these cases, context-specific recommendations regarding the use of German claims data for future pandemics or other public health emergencies were derived, namely that the utilization of established and interdisciplinary project teams enables a timely project start and furthermore, meta-analytic methods are a valuable way to pool aggregated results of claims data analyses when data protection regulations do not allow a consolidation of data sets from different statutory health insurances. Under these circumstances, claims data are a readily available and valid data source of empirical evidence base necessary for public health measures during a pandemic.