EpiGeoPop: a tool for developing spatially accurate country-level epidemiological models

TL;DR

EpiGeoPop is a tool that helps create accurate spatial models for simulating disease spread at the country level.

Contribution

EpiGeoPop introduces a user-friendly solution for integrating detailed spatial data into agent-based models for epidemiology.

Findings

EpiGeoPop improves the setup of agent-based models by incorporating real-world spatial data.

Accurate spatial detail in ABM simulations is crucial for modeling disease outbreaks effectively.

EpiGeoPop facilitates the use of multiple international data sources to enhance model accuracy.

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.

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