Institution:
Public health agencies increasingly rely on computational epidemiological models to support preparedness and response to infectious disease outbreaks. However, calibrating large-scale, data-driven simulations and exploring intervention strategies remain computationally demanding tasks that exceed the capabilities of conventional computing infrastructures.
EpiSim-EMEWS combines the EpiSim.jl epidemiological simulator with the EMEWS extreme-scale workflow framework to automate large-scale model exploration on high-performance computing (HPC) systems. The platform enables thousands of simulations to run in parallel for parameter calibration, uncertainty quantification, sensitivity analysis, and optimization of intervention strategies.
Its modular architecture supports customizable workflows, multiple optimization algorithms (e.g., CMA-ES and Genetic Algorithms), interactive visual analytics, and deployment across modern HPC infrastructures. The technology accelerates evidence-based decision making while enabling the development of city-scale digital twins for public health planning.
