• Most of UC San Diego's COVID-19 cases de

    From ScienceDaily@1:317/3 to All on Wed Aug 11 21:30:42 2021
    Most of UC San Diego's COVID-19 cases detected early by wastewater
    screening

    Date:
    August 11, 2021
    Source:
    University of California - San Diego
    Summary:
    Part of UC San Diego's Return to Learn program, wastewater screening
    helped prevent outbreaks by detecting 85 percent of cases early,
    allowing for timely testing, contact tracing and isolation.



    FULL STORY ========================================================================== People infected with SARS-CoV-2, the virus that causes COVID-19, are
    known to shed it in their stool, even if they aren't experiencing any
    symptoms. With that in mind, University of California San Diego School of Medicine researchers have been screening wastewater from campus buildings
    for signs of the virus since the summer of 2020, thinking the information
    could help prevent outbreaks.


    ==========================================================================
    Now they have data to back it up: Screening for SARS-CoV-2 in wastewater,
    the team showed they can detect even a single infected, asymptomatic
    person living or working in a large building. Notification to occupants
    of each building with positive wastewater increased COVID-19 testing
    rates by as much as 13-fold.

    Once an occupant tested positive, isolation and contact tracing helped
    prevent further spread of the virus.

    The approach enabled early detection of 85 percent of COVID-19 cases
    on the campus, researchers reported in the August 10, 2021 issue of
    mSystems. In other words, wastewater samples tested positive before most individual case diagnoses.

    "University campuses especially benefit from wastewater surveillance
    as a means to avert COVID-19 outbreaks, as they're full of largely
    asymptomatic populations, and are potential hot spots for transmission
    that necessitate frequent diagnostic testing," said first author Smruthi Karthikeyan, PhD, an environmental engineer and postdoctoral researcher
    at UC San Diego School of Medicine.

    Karthikeyan led the study with senior author Rob Knight, PhD, professor
    and director of the Center for Microbiome Innovation at UC San Diego.

    Wastewater screening is an integral part of UC San Diego's Return to Learn program, an evidence-based approach that has allowed the university to
    offer on-campus housing and in-person classes and research opportunities throughout most of the pandemic.



    ========================================================================== Return to Learn relies on three pillars: risk mitigation, viral detection
    and intervention. With approximately 10,000 students on campus during
    the 2020-2021 academic year, the many components of the program kept
    COVID-19 case rates much lower than the surrounding community and
    compared to most college campuses, maintaining a positivity rate of
    less than 1 percent during that time. The Return to Learn program,
    including wastewater testing, has become a model for other universities,
    K-12 school districts and regions.

    Every morning, seven days a week, a team of students and staff in matching
    t- shirts deploys across campus on golf carts to collect sewage samples
    from 126 collection robots set up to monitor 350 buildings. By 10 a.m.,
    they return to Knight's lab at the School of Medicine.

    There, Karthikeyan and team process the sewage using a different kind
    of robot, which concentrates the virus using magnetic nanoparticles,
    then extracts RNA - - the genetic material that makes up the genomes of
    viruses like SARS-CoV-2 - - from the samples. Polymerase chain reaction
    (PCR) testing is used to search for the virus' signature genes.

    When the virus is detected, automated but targeted messages are sent
    through a campus-wide system to persons associated with affected
    buildings, such as students, staff and faculty, recommending they be
    tested for the virus as soon as possible. The data is added to a public dashboard (https:// returntolearn.ucsd.edu/dashboard/).

    Since its inception, the team has worked constantly to optimize the
    process, Karthikeyan said. The current automated approach has dramatically reduced the sample-to-result turnaround time 20-fold; now five hours for
    96 samples. By miniaturizing the samples, the researchers have reduced processing costs to $13 per sample. Knight estimates the approach exceeds
    the scale of similar surveillance programs by 10- to 100-fold. The next
    step, he said, will be to deploy rapid methods to test for SARS-CoV-2
    variants, including delta, in real time.

    "This system demonstrates how the many different parts of UC San Diego
    can work together as a system to keep campus safe," Knight said. "This
    work required not just advances in viral sample processing, but teams
    including Logistics, Environmental Health and Safety, campus and health
    system IT, Facilities Management, and many others, as well as leadership
    from the Return to Learn program to make it happen. We are now helping
    other campuses and organizations replicate this success, which has
    potential not just for COVID-19, but for many other stool-borne pathogens, including influenza, in future." Co-authors include: Andrew Nguyen,
    Daniel McDonald, Yijian Zong, Nancy Ronquillo, Junting Ren, Jingjing Zou, Sawyer Farmer, Greg Humphrey, Diana Henderson, Tara Javidi, Karen Messer, Cheryl Anderson, Robert Schooley, Natasha K. Martin, all at UC San Diego.

    ========================================================================== Story Source: Materials provided by
    University_of_California_-_San_Diego. Original written by Heather
    Buschman, Ph.D.. Note: Content may be edited for style and length.


    ========================================================================== Journal Reference:
    1. Smruthi Karthikeyan, Andrew Nguyen, Daniel McDonald, Yijian Zong,
    Nancy
    Ronquillo, Junting Ren, Jingjing Zou, Sawyer Farmer, Greg Humphrey,
    Diana Henderson, Tara Javidi, Karen Messer, Cheryl Anderson,
    Robert Schooley, Natasha K. Martin, Rob Knight. Rapid, Large-Scale
    Wastewater Surveillance and Automated Reporting System Enable
    Early Detection of Nearly 85% of COVID-19 Cases on a University
    Campus. mSystems, 2021; DOI: 10.1128/ mSystems.00793-21 ==========================================================================

    Link to news story: https://www.sciencedaily.com/releases/2021/08/210811131552.htm

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