EpiGeoPop: A Tool for Developing Spatially Accurate Country-level Epidemiological Models
Abstract
Mathematical models play a crucial role in understanding the spread of infectious disease outbreaks and influencing policy decisions. These models aid pandemic preparedness by predicting outcomes under hypothetical scenarios and identifying weaknesses in existing frameworks. However, their accuracy, utility, and comparability are being scrutinized. Agent-based models (ABMs) have emerged as a valuable tool, capturing population heterogeneity and spatial effects, particularly when assessing 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 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 investigation involves the interplay between population density, the implementation of spatial transmission, and realistic interventions implemented in Epiabm.
Cite
@article{arxiv.2310.13468,
title = {EpiGeoPop: A Tool for Developing Spatially Accurate Country-level Epidemiological Models},
author = {Lara Herriott and Henriette L. Capel and Isaac Ellmen and Nathan Schofield and Jiayuan Zhu and Ben Lambert and David Gavaghan and Ioana Bouros and Richard Creswell and Kit Gallagher},
journal= {arXiv preprint arXiv:2310.13468},
year = {2023}
}
Comments
16 pages, 6 figures, 3 supplementary figures