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Encrypted data-sharing for preserving privacy in wastewater-based epidemiology.

Erin M Driver1, Manazir Ahsan2, Lucas Piske2

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New wastewater surveillance methods protect privacy by enabling secure data sharing between untrusted entities. This encrypted framework supports high-resolution public health monitoring while safeguarding sensitive subpopulations.

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Area of Science:

  • Environmental Science
  • Public Health
  • Computer Science

Background:

  • Wastewater surveillance is expanding to granular levels (building, campus), increasing data sensitivity and privacy risks.
  • Sharing high-resolution wastewater data between entities with differing data governance policies presents privacy and trust challenges.
  • Existing data sharing restrictions can hinder comprehensive public health surveillance efforts.

Purpose of the Study:

  • To develop and demonstrate an encrypted framework for secure data sharing in wastewater-based epidemiology (WBE).
  • To enable collaboration between untrusted entities (e.g., municipalities, labs) for sensitive health data.
  • To balance public health surveillance needs with robust privacy protections for subpopulations.

Main Methods:

  • Developed a novel encrypted framework for secure data sharing among multiple entities.
  • Implemented and tested the framework using two real-world case studies involving municipalities and a laboratory.
  • Validated the framework's ability to perform secure private computations for WBE.

Main Results:

  • Demonstrated the feasibility of securely sharing encrypted wastewater data between two municipalities and a laboratory.
  • Achieved high precision, fast computation speeds, and low data costs for secure private computations in WBE.
  • Showcased the framework's compatibility with essential WBE computations like normalization and quality control.

Conclusions:

  • The encrypted framework effectively facilitates secure data sharing and private computations for wastewater-based epidemiology.
  • This approach enhances public health surveillance capabilities by enabling responsible data sharing at community levels.
  • The framework supports the expansion of wastewater surveillance, addressing privacy concerns and improving data utility.