Evidence map›Paper›PMID 40486220›Full record

ArticleData in brief2025

An open-source and spatially diverse synthetic population dataset for agent-based modelling and microsimulation in Ireland.

Seán Caulfield Curley, Karl Mason, Patrick Mannion

Abstract read
In one paragraph

Article in Data in brief, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Seán Caulfield CurleySchool of Computer Science, University of Galway, Galway, Ireland.
Karl MasonSchool of Computer Science, University of Galway, Galway, Ireland.
Patrick MannionSchool of Computer Science, University of Galway, Galway, Ireland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Spatial microsimulations, where simulation units represent people or households in a small area, are extremely useful for modelling a wide range of socio-economic scenarios at a fine scale. The characteristics of individuals in these simulations' populations need to accurately represent the real characteristics of the target area to model realistic scenarios. However, individual-level data is not available for the vast majority of populations, Ireland included, due to privacy concerns. Thus, a representative synthetic population for the Republic of Ireland is needed. The data from four methods of generating synthetic populations at the Electoral Division level are given in this paper. Realistic individuals are created by sampling from the Central Statistics Office (CSO) Labour Force Survey. Spatial heterogeneity is achieved by matching the aggregate counts of individuals' characteristics to those from the CSO Census Small Area Population Statistics. Individuals are assigned six characteristics: age group, sex, marital status, house size, primary economic status, and highest level of education achieved.

Indexed as

Agent-based modellingIrelandMicrosimulationSynthetic population

Identifiers

PMID40486220
PMCPMC12145541

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.