A Digital One Health framework to integrate data for public health decision-making

Redman-White, C. J., Loosli, K., Qarkaxhija, V., Lee, T. N., Mboowa, G., Wee, B. A. and Muwonge, A. (2023) A Digital One Health framework to integrate data for public health decision-making. IJID One Health, 1, 100012. (doi: 10.1016/j.ijidoh.2023.100012)

Abstract

The current implementation of One Health (OH) primarily focuses on multi-sectoral collaboration but often overlooks opportunities to integrate contextual and pathogen-related data into a unified data resource. This lack of integration hampers effective, data-driven decision-making in OH activities. In this perspective, we examine the existing strategies for data sharing and identify gaps and barriers to integration. To overcome these challenges, we propose the Digital OH (DOH) framework for data integration, which consolidates data-sharing principles within five pillars for the OH community of practice: (a) Harmonization of standards to establish trust, (b) Automation of data capture to enhance quality and efficiency, (c) Integration of data at point of capture to limit bureaucracy, (d) Onboard data analysis to articulate utility, and (e) Archiving and governance to safeguard the OH data resource. We discuss an upcoming pilot program as a use case focusing on antimicrobial resistance surveillance to illustrate the application of this framework. Our ambition is to leverage technology to create data as a shared resource using DOH not only to overcome current structural barriers but also to address prevailing ethical and legal concerns. By doing so, we can enhance the efficiency and effectiveness of decision-making processes in the OH community of practice, at a national, regional, and international level.

• Item Type: Articles
• Additional Information: Funding: AM and BW are funded by the BBSRC at Roslin Institute (BB/ T00875X/1) and AM as Chancellor’s fellow at University of Edinburgh, the Digital One Health pilot is funded by the Royal Society (RGS \R1\231137), CRW acknowledges support for a PhD studentship from the UKRI Biotechnology and Biological Sciences Research Council (BBSRC) and Zoetis (BB/T00875X/1). TNL & VQ are funded by a Wellcome One Health Model PhD studentship and KL is jointly funded by a One Health PhD by the University of Edinburgh and the University of Glasgow Jointly Funded PhD studentships.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Loosli, Kathrin

Creator Roles

Loosli, K.: Writing – original draft, Writing – review and editing

• Authors: Redman-White, C. J., Loosli, K., Qarkaxhija, V., Lee, T. N., Mboowa, G., Wee, B. A., and Muwonge, A.
• College/School: College of Medical Veterinary and Life Sciences
• Journal Name: IJID One Health
• Publisher: Elsevier
• ISSN: 2949-9151
• ISSN (Online): 2949-9151
• Copyright Holders: Copyright © 2023 The Authors
• First Published: First published in IJID One Health 1:100012
• Publisher Policy: Reproduced under a Creative Commons licence