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A comprehensive, open-source data model for wastewater-based epidemiology.

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Wastewater-based epidemiology (WBE) monitors population health. The Public Health Environmental Surveillance Open Data Model (PHES-ODM) standardizes environmental surveillance data for better public health insights.

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Area of Science:

  • Environmental science
  • Public health
  • Data science

Background:

  • The SARS-COV-2 pandemic accelerated the use of wastewater-based epidemiology (WBE) for population health monitoring.
  • Environmental surveillance data requires context for meaningful interpretation across different locations.
  • Open data sharing is crucial for scientific advancement and public service.

Purpose of the Study:

  • To introduce the second iteration of the Public Health Environmental Surveillance Open Data Model (PHES-ODM).
  • To enhance the interoperability and contextualization of environmental surveillance data.
  • To provide open-source tools for data collection, management, and analysis in public health surveillance.

Main Methods:

  • Developed PHES-ODM, an open-source data model and tools.
  • The model standardizes storage for environmental surveillance program data, including specimen metadata and measurement protocols.
  • Software tools support data collection, PCR calculations, validation, and SQL database generation.

Main Results:

  • The PHES-ODM facilitates the storage of contextual metadata alongside environmental surveillance data.
  • It provides tools for data processing, including PCR calculations and validation.
  • The model supports the generation of analysis-ready datasets and database schemas.

Conclusions:

  • The PHES-ODM offers a standardized approach for creating robust, interoperable, and open environmental public health datasets.
  • It is applicable to SARS-CoV-2 surveillance and other public health monitoring initiatives.
  • The open-source model has international adoption, promoting collaborative environmental health surveillance.