Local Data Spaces: Leveraging trusted research environments for secure location-based policy research in the age of coronavirus disease-2019
Jacob L. Macdonald; Mark A. Green; Maurizio Gibin; Simon Leech; Alex Singleton; Paul Longley (2023). Data & Policy, 5. DOI: 10.1017/dap.2023.14
Abstract
This work explores the use of Trusted Research Environments for the secure analysis of sensitive, record-level data on local coronavirus disease-2019 (COVID-19) inequalities and economic vulnerabilities. The Local Data Spaces (LDS) project was a targeted rapid response and cross-disciplinary collaborative initiative using the Office for National Statistics’ Secure Research Service for localized comparison and analysis of health and economic outcomes over the course of the COVID-19 pandemic. Embedded researchers worked on co-producing a range of locally focused insights and reports built on secure secondary data and made appropriately open and available to the public and all local stakeholders for wider use. With secure infrastructure and overall data governance practices in place, accredited researchers were able to access a wealth of detailed data and resources to facilitate more targeted local policy analysis. Working with data within such infrastructure as part of a larger research project involved advanced planning and coordination to be efficient. As new and novel granular data resources become securely available (e.g., record-level administrative digital health records or consumer data), a range of local policy insights can be gained across issues of public health or local economic vitality. Many of these new forms of data however often come with a large degree of sensitivity around issues of personal identifiability and how the data is used for public-facing research and require secure and responsible use. Learning to work appropriately with secure data and research environments can open up many avenues for collaboration and analysis.
Extended Summary
This research demonstrates how Trusted Research Environments (TREs) can enable secure analysis of sensitive location-based data for local policy research during public health emergencies. The study presents the Local Data Spaces (LDS) project, a rapid response collaborative initiative that ran from November 2020 to April 2021, involving the Joint Biosecurity Centre, Office for National Statistics, and academic researchers. The project utilised the ONS Secure Research Service to analyse record-level national surveys and administrative registries related to COVID-19 health outcomes and economic vulnerabilities at the local authority level. The methodology combined secure datasets including the COVID-19 Infection Survey, Test and Trace data, Labour Force Survey, and Business Registry Database with openly available mobility and demographic indicators. Through co-production processes involving 25 Local Authority teams, the research identified priority concerns around COVID-19 inequalities and economic vulnerabilities that required granular data analysis beyond what local teams could access independently. The study developed a systematic workflow for generating local area profiles, producing 10 individualised reports for each of 323 Local Authority Districts across England. These reports covered domains including occupational and ethnic inequalities in COVID-19, demographic patterns, geospatial disparities, excess mortality, industry workforce densities, economic vulnerabilities, and mobility patterns. The research demonstrates significant policy impact, with 813 report packages downloaded in the initial seven months, primarily by academic and local government users. The secure infrastructure enabled rapid response to urgent policy needs, including support for Liverpool’s mass testing pilot and evidence provision to the UK Government’s Scientific Advisory Group for Emergencies on gender inequalities in COVID-19. However, the study identifies key limitations including the intensive time commitment required for researcher accreditation, challenges in scaling direct local authority access to TREs, and the need for advance planning when working within secure environments. The research concludes that TREs provide valuable infrastructure for combining sensitive granular data with open datasets to generate locally relevant policy insights whilst maintaining appropriate data protection safeguards. This approach offers significant potential for future local policy research as new forms of administrative and commercial data become available, particularly for addressing public health challenges and economic development at the neighbourhood level.
Key Findings
- Trusted Research Environments enable secure analysis of sensitive health and economic data for local policy development during emergencies.
- The Local Data Spaces project successfully generated 323 individualised local authority reports using record-level COVID-19 and economic datasets.
- Co-production with 25 Local Authority teams identified priority research questions that required granular data analysis beyond local capacity.
- Significant policy impact achieved with 813 report downloads and direct support for mass testing pilots and government advisory groups.
- Key barriers include intensive researcher accreditation requirements and challenges scaling direct local authority access to secure environments.
Citation
@article{macdonald2023local,
author = {Jacob L. Macdonald; Mark A. Green; Maurizio Gibin; Simon Leech; Alex Singleton; Paul Longley},
title = {Local Data Spaces: Leveraging trusted research environments for secure location-based policy research in the age of coronavirus disease-2019},
journal = {Data \& Policy},
year = {2023},
volume = {5},
doi = {10.1017/dap.2023.14}
}