  The NSF-funded Robust Epidemic Surveillance and Modeling (RESUME) project
successfully convened a workshop entitled "High-performance computing and
large-scale data management in service of epidemiological modeling" at the
University of Chicago on May 1-2, 2023. This was part of a series of workshops
designed to foster sustainable and interdisciplinary co-design for predictive
intelligence and pandemic prevention. The event brought together 31 experts in
epidemiological modeling, high-performance computing (HPC), HPC workflows, and
large-scale data management to develop a shared vision for capabilities needed
for computational epidemiology to better support pandemic prevention. Through
the workshop, participants identified key areas in which HPC capabilities could
be used to improve epidemiological modeling, particularly in supporting public
health decision-making, with an emphasis on HPC workflows, data integration,
and HPC access. The workshop explored nascent HPC workflow and large-scale data
management approaches currently in use for epidemiological modeling and sought
to draw from approaches used in other domains to determine which practices
could be best adapted for use in epidemiological modeling. This report
documents the key findings and takeaways from the workshop.
