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Enhanced Extraction of Low-Molecular Weight DNA from Wastewater for Comprehensive Assessment of Antimicrobial Resistance
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Expanding the PHES-ODM: A Comprehensive, Open-Source Data Model for the Future of Wastewater-Based Epidemiology
Mathew Thomson1, Jean-David Therrien2,3, Nikho Hizon4
1Ottawa Hospital Research Institute, University of Ottawa, Ottawa, ON K1Y 4E9, Canada.
Microorganisms
|June 26, 2026
Summary
Wastewater surveillance (WWS) data challenges are addressed by the Public Health and Environmental Surveillance Open Data Model (PHES-ODM) v3. This standardized framework enhances data interoperability and utility for public health decision-making.
Area of Science:
- Public Health
- Environmental Science
- Data Science
Background:
- Wastewater surveillance (WWS) is crucial for public health, especially post-COVID-19.
- Data fragmentation and poor interoperability hinder WWS long-term utility.
- Existing systems lack standardized metadata and FAIR data principles alignment.
Purpose of the Study:
- Introduce version 3 of the Public Health and Environmental Surveillance Open Data Model (PHES-ODM).
- Address persistent barriers in WWS data interoperability and utility.
- Promote transparent, ethical, and FAIR-aligned data use in WWS.
Main Methods:
- Developed PHES-ODM v3 as an open, collaborative framework.
- Enhanced metadata capture and relational data linkages.
- Introduced new tables for public health actions, external data, and analytical workflows.
- Provided tools for mapping existing standards and supporting data formats.
Main Results:
- PHES-ODM v3 offers a scalable, modular infrastructure for diverse WWS programs.
- Improved data quality, accessibility, and integration capabilities.
- Facilitates complex relational data linking across various surveillance components.
Conclusions:
- PHES-ODM v3 provides a robust solution for WWS data standardization.
- Enhances public health decision-making through improved data integration.
- Supports a more effective and complex global surveillance landscape.
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