The Public Health and Environmental Surveillance Open Data Model (PHES-ODM) Version 3: An Open, Relational Data Model and Interoperability Framework for Wastewater Surveillance

📅 2026-04-20
📈 Citations: 0
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🤖 AI Summary
This study addresses longstanding challenges in wastewater surveillance—namely data fragmentation, inconsistent metadata, and insufficient interoperability—by proposing an open, relational, and modular data model and interoperability framework. Designed to align with established standards such as PHA4GE and the U.S. CDC’s National Wastewater Surveillance System, the framework supports transparent and ethical data use under FAIR principles. It introduces novel features including public health action tables, links to external databases (e.g., GISAID, GenBank), and documentation of analytical workflows, while enhancing multidimensional relational modeling and facilitating conversion between wide and long data formats. Deployed across 25 countries, the framework has been adopted by the Public Health Agency of Canada and adapted by the European Union’s Sewage Sentinel System, demonstrating significant advantages over six existing wastewater data standards across 25 key criteria.

Technology Category

Application Domains: Humanities & Computational Social ScienceData Mining & Knowledge Management: Linked Open Data, Knowledge Graphs & KB CompletionNatural Language Processing: Ethics — Bias, Fairness, Transparency & Privacy

Application Category

Systems and Infrastructure for Web, Mobile and WoT: Data management and stream processing for Web, mobile and wireless applicationsSecurity and Privacy: Data transparency and provenanceWeb Mining and Content Analysis: Web data integration and cleaning
📝 Abstract
Wastewater surveillance (WWS) has emerged as a valuable tool for public health surveillance, particularly since 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. Adopted by the Public Health Agency of Canada and adapted by the EU Sewage Sentinel System, the model is now used in over 25 countries. This paper introduces version 3 of the model, which addresses persistent barriers to interoperability and data utility. Key enhancements include new tables for public health actions, external repository linkages (e.g., GISAID, GenBank), and analytical workflow documentation, as well as support for complex relational linkages across sites, samples, measures, and populations. Tools for mapping across other data formats, including PHA4GE and the US CDC National Wastewater Surveillance System, and for supporting long and wide data formats are also introduced. We compare PHES-ODM against six other WWS data standards across 25 features. Balancing robustness with usability, PHES-ODM v3 provides a scalable, modular infrastructure adaptable to diverse WWS and environmental surveillance programs.
Problem

Research questions and friction points this paper is trying to address.

wastewater surveillance
data interoperability
metadata standardization
public health surveillance
fragmented data systems
Innovation

Methods, ideas, or system contributions that make the work stand out.

interoperability
relational data model
wastewater surveillance
FAIR principles
data standardization
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