The release of the Corona-Warn-App (CWA), a governmental pandemic tracing app to track infection chains related to COVID-19 in Germany, marks an unprecedented situation that offers a unique opportunity for investigating population-wide adoption of novel technology. We develop a conceptual model to investigate the effects and path relationships of multiple constructs related to technology adoption, data security, morality, social influence, trust, and COVID-19 to predict behavioral intentions and actual usage behavior. We use structural equation modelling with the partial least squares method and identify effort expectancy, social influence, prevailing opinions on COVID-19 and the CWA, as well as moral and ethical considerations as the most influential predictors. We are able to explain moderate to high amounts of variance with our model. Our results offer valuable insights for the technology ac- ceptance literature and enable practical recommendations for improving the public communication and elevating user numbers of pandemic tracing apps in Germany.