Improved scalability, sensitivity, and interpretability of pathogen detection, including SARS-CoV-2, in wastewater using high-throughput, highly multiplexed digital array PCR technology

  • Funded by National Institutes of Health (NIH)
  • Total publications:0 publications

Grant number: 4U01DA053899-02

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Key facts

  • Disease

    Disease X
  • Start & end year

    2021
    2024
  • Known Financial Commitments (USD)

    $673,305
  • Funder

    National Institutes of Health (NIH)
  • Principal Investigator

    PROFESSOR Rachel Noble
  • Research Location

    United States of America
  • Lead Research Institution

    UNIV OF NORTH CAROLINA CHAPEL HILL
  • Research Priority Alignment

    N/A
  • Research Category

    Pathogen: natural history, transmission and diagnostics

  • Research Subcategory

    Diagnostics

  • Special Interest Tags

    N/A

  • Study Type

    Unspecified

  • Clinical Trial Details

    N/A

  • Broad Policy Alignment

    Pending

  • Age Group

    Not Applicable

  • Vulnerable Population

    Not applicable

  • Occupations of Interest

    Not applicable

Abstract

PROJECT ABSTRACT Presently, the application of molecular technology such as RT-qPCR and digital PCR (dPCR) to quantify SARS-CoV-2 and related targets in wastewater is cumbersome, time consuming, and costly. While progress has been made on the development of methods and the interpretation of data, much remains to be improved for the technology to be used as a public health management tool. A major drawback in the current approaches are 1) the lack of streamlined and consistent pre-analytical processing steps, 2) coverage across the relevant targets requires a high number of reactions (>20) from any single sample to provide quantitative information, and 3) a lack of vision on the development of a pathogen/marker panel, much like those used in clinical arenas, for interpretation of the data across different states, regions and nations. The goal of this project will be to successfully navigate these three limitations toward development of a public health warning system that is not dependent on clinical testing and has the ability to rapidly address novel pathogen threats in the future.