Evaluating Epidemic Scenarios with Agent-Based Simulation: A Case Study from UK Public Health Workshop

Abstract

The growing complexity of public health emergencies requires modeling tools that are both scientifically robust and operationally scalable. As part of the EU Horizon 2020 STAMINA project, we deployed the Flu and Coronavirus Simulator (FACS), a geospatial agent-based model designed to simulate the spread of infectious diseases at local and regional levels. This paper presents a case study from a UK Public Health Workshop, where FACS supported the evaluation of epidemic response scenarios. We describe how FACS integrates demographic, spatial, and epidemiological data, and outline key enhancements, such as locationbased parallelization and FabSim3-enabled automation, which enable large-scale simulation. We detail the scenario designs and outcomes, highlighting the intersection of simulation projections and intervention planning. Finally, we reflect on communicating results to stakeholders and bridging the gap between modeling and policy. This work demonstrates how geospatially grounded, scalable agent-based simulations can provide meaningful insights into regional intervention planning within operational timeframes.