Abstract
Mathematical models play a crucial role in understanding the spread of infectious disease outbreaks and influencing policy decisions. These models have aided pandemic preparedness by predicting outcomes under hypothetical scenarios and identifying weaknesses in existing frameworks; however, their accuracy, utility, and comparability are being scrutinised. Agent-based models (ABMs) have emerged as a valuable tool, capturing population heterogeneity and spatial effects, particularly when assessing potential intervention strategies. Here we present EpiGeoPop, a user-friendly tool for rapidly preparing spatially accurate population configurations of entire countries. EpiGeoPop helps to address the problem of complex and time-consuming model set-up in ABMs, specifically improving the integration of real-world spatial detail. We subsequently demonstrate the importance of accurate spatial detail in ABM simulations of disease outbreaks using Epiabm, an ABM based on Imperial College London's CovidSim with improved modularity, documentation and testing. Our simulations present a number of possible applications of ABMs where including spatially accurate data is crucial, highlighting the potential impact of EpiGeoPop in facilitating this process using multiple international data sources.