Automation and Collaboration in Complex Epidemiological Workflows with OSPREY

Epidemiological modeling, a powerful tool for supporting decision-making during a pandemic, is a workflow problem that incorporates data management of real-time data streams, large-scale simulation and analysis, and complex software integrations. The Open Science Platform for Robust Epidemic Analysis (OSPREY) was introduced to address critical gaps in this challenging scientific application. This paper explores the capabilities of OSPREY regarding data ingestion, curation, and management, and the development of a Shared Development Environment (SDE) for rapid collaboration. We present two use cases to demonstrate the implementation and impact of each of these goals. The first use case highlights real-time data ingestion and curation for epidemiologic modeling, while the second focuses on developing efficient global sensitivity analyses for epidemic models. These advancements aim to enhance OSPREY's capabilities for supporting public health decision-making and reproducible science.