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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.
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.
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