Evidence map›Paper›PMID 40696036›Full record

ArticleScientific reports2025

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

Lara Herriott, Henriette L Capel, Isaac Ellmen, Nathan Schofield, Jiayuan Zhu, Ben Lambert, David Gavaghan, Ioana Bouros, Richard Creswell, Kit Gallagher

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Lara Herriott *SABS R3 CDT, University of Oxford, Oxford, UK.
Henriette L Capel *SABS R3 CDT, University of Oxford, Oxford, UK.
Isaac Ellmen *SABS R3 CDT, University of Oxford, Oxford, UK.
Nathan Schofield *SABS R3 CDT, University of Oxford, Oxford, UK.
Jiayuan Zhu *SABS R3 CDT, University of Oxford, Oxford, UK.
Ben LambertDepartment of Statistics, University of Oxford, Oxford, UK.
David GavaghanSABS R3 CDT, University of Oxford, Oxford, UK.
Ioana BourosSABS R3 CDT, University of Oxford, Oxford, UK.
Richard CreswellDepartment of Computer Science, University of Oxford, Oxford, UK.
Kit GallagherSABS R3 CDT, University of Oxford, Oxford, UK. kit.gallagher@maths.ox.ac.uk.

Funding

RCUK | Engineering and Physical Sciences Research Council (EPSRC) EP/S024093/1
6 · The paper itself

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.

Indexed as

COVID-19Epidemiological ModelsSoftwareComputer SimulationDisease OutbreaksHumansPandemicsSARS-CoV-2

Identifiers

PMID40696036
PMCPMC12284068

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.