ArticleScientific data2022
A synthetic population dataset for estimating small area health and socio-economic outcomes in Great Britain.
Article in Scientific data, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Synthetic data Using Population Profiles for cardiOvascular Risk facTors (SUPPORT) in mainland China.Scientific data · 2026Article
- Article
- A reproducible pipeline for activity-based travel demand generation in England.Environment and planning. B, urban analytics and city science · 2025Article
- An inclusive economy dataset for wards in Great Britain using administrative and synthetic data sources.Scientific data · 2025Article
- An open-source and spatially diverse synthetic population dataset for agent-based modelling and microsimulation in Ireland.Data in brief · 2025Article
- A National Synthetic Populations Dataset for the United States.Scientific data · 2025Article
- The PHEM-B toolbox of methods for incorporating the influences on Behaviour into Public Health Economic Models.BMC public health · 2024Article
- Article
- A synthetic population dataset for estimating small area health and socio-economic outcomes in Great Britain.Scientific data · 2022Article
- An overview of synthetic administrative data for research.International journal of population data science · 2022Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
In order to understand the health outcomes for distinct sub-groups of the population or across different geographies, it is advantageous to be able to build bespoke groupings from individual level data. Individuals possess distinct characteristics, exhibit distinct behaviours and accumulate their own unique history of exposure or experiences. However, in most disciplines, not least public health, there is a lack of individual level data available outside of secure settings, especially covering large portions of the population. This paper provides detail on the creation of a synthetic micro dataset for individuals in Great Britain who have detailed attributes which can be used to model a wide range of health and other outcomes. These attributes are constructed from a range of sources including the United Kingdom Census, survey and administrative datasets. It provides a rationale for the need for this synthetic population, discusses methods for creating this dataset and provides some example results of different attribute distributions for distinct sub-population groups and over different geographical areas.
Identifiers
What OpenQuestion holds
Registered trials
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.