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Volume 14
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10.3390/microorganisms14061267
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Article

Expanding the PHES-ODM: A Comprehensive, Open-Source Data Model for the Future of Wastewater-Based Epidemiology

by
Mathew Thomson
1,
Jean-David Therrien
2,3,
Nikho Hizon
4,
Janet Ting-mei Lin
4,
Martin Wellman
1,
Eugen-Sorin Sion
5,
Carol Bennett
1,
Peter A. Vanrolleghem
2 and
Douglas Manuel
1,*
1
Ottawa Hospital Research Institute, University of Ottawa, Ottawa, ON K1Y 4E9, Canada
2
modelEAU, Université Laval, Québec City, QC G1V 0A6, Canada
3
Faculty of Bioscience Engineering, Ghent University, 9000 Ghent, Belgium
4
Public Health Agency of Canada National Microbiology Laboratory, Winnipeg, MB R3E 3R2, Canada
5
Joint Research Centre, European Commission, 21027 Ispra, Italy
*
Author to whom correspondence should be addressed.
Microorganisms 2026, 14(6), 1267; https://doi.org/10.3390/microorganisms14061267
Submission received: 31 March 2026 / Revised: 22 May 2026 / Accepted: 2 June 2026 / Published: 4 June 2026
(This article belongs to the Special Issue Surveillance of Health-Relevant Pathogens Employing Wastewater)
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Abstract

Wastewater surveillance (WWS) has quickly emerged as an invaluable tool for public health surveillance, particularly in the wake of the COVID-19 pandemic. Its long-term utility is constrained, however, by fragmented data systems, inconsistent metadata practices, and poor interoperability. The Public Health and Environmental Surveillance Open Data Model (PHES-ODM) was developed as an open, collaborative framework to standardize WWS data and support transparent, ethical data use aligned with FAIR principles in response to these challenges. Building on the success and global adoption of earlier versions, this paper introduces version 3 of the model, expanding to address persistent barriers to interoperability and data utility. Key enhancements include improved metadata capture, support for complex relational linkages across sites, samples, measures, and populations, and new tables for public health actions, external data linkages, and analytical workflows. Tools for mapping across existing standards and supporting long and wide data formats are also introduced. Balancing robustness with usability, PHES-ODM v3 provides a scalable, modular infrastructure adaptable to diverse WWS programmes. The model offers comprehensive solutions for improving data quality, accessibility, and integration, supporting more effective public health decision-making in an increasingly complex global surveillance landscape.
Keywords: wastewater surveillance; wastewater epidemiology; environmental surveillance; data standardization; relational data modeling; database schema; public health data; public health wastewater surveillance; wastewater epidemiology; environmental surveillance; data standardization; relational data modeling; database schema; public health data; public health
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MDPI and ACS Style

Thomson, M.; Therrien, J.-D.; Hizon, N.; Lin, J.T.-m.; Wellman, M.; Sion, E.-S.; Bennett, C.; Vanrolleghem, P.A.; Manuel, D. Expanding the PHES-ODM: A Comprehensive, Open-Source Data Model for the Future of Wastewater-Based Epidemiology. Microorganisms 2026, 14, 1267. https://doi.org/10.3390/microorganisms14061267

AMA Style

Thomson M, Therrien J-D, Hizon N, Lin JT-m, Wellman M, Sion E-S, Bennett C, Vanrolleghem PA, Manuel D. Expanding the PHES-ODM: A Comprehensive, Open-Source Data Model for the Future of Wastewater-Based Epidemiology. Microorganisms. 2026; 14(6):1267. https://doi.org/10.3390/microorganisms14061267

Chicago/Turabian Style

Thomson, Mathew, Jean-David Therrien, Nikho Hizon, Janet Ting-mei Lin, Martin Wellman, Eugen-Sorin Sion, Carol Bennett, Peter A. Vanrolleghem, and Douglas Manuel. 2026. "Expanding the PHES-ODM: A Comprehensive, Open-Source Data Model for the Future of Wastewater-Based Epidemiology" Microorganisms 14, no. 6: 1267. https://doi.org/10.3390/microorganisms14061267

APA Style

Thomson, M., Therrien, J.-D., Hizon, N., Lin, J. T.-m., Wellman, M., Sion, E.-S., Bennett, C., Vanrolleghem, P. A., & Manuel, D. (2026). Expanding the PHES-ODM: A Comprehensive, Open-Source Data Model for the Future of Wastewater-Based Epidemiology. Microorganisms, 14(6), 1267. https://doi.org/10.3390/microorganisms14061267

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