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85% of Campus COVID-19 Cases Detected Early by UC San Diego’s Wastewater Screening

Smruthi Karthikeyan, PhD (left) and Rob Knight, PhD (proper) decide up wastewater samples from assortment robots on the UC San Diego campus. Credit score: Erik Jepsen/UC San Diego

Half of the college’s Return to Be taught program, wastewater screening helped forestall outbreaks by detecting 85 % of instances early, permitting for well timed testing, contact tracing and isolation.

Folks contaminated with SARS-CoV-2, the virus that causes COVID-19, are recognized to shed it of their stool, even when they aren’t experiencing any signs. With that in thoughts, College of California San Diego College of Drugs researchers have been screening wastewater from campus buildings for indicators of the virus because the summer time of 2020, considering the knowledge may assist forestall outbreaks.

Now they’ve information to again it up: Screening for SARS-CoV-2 in wastewater, the staff confirmed they will detect even a single contaminated, asymptomatic particular person residing or working in a big constructing. Notification to occupants of every constructing with optimistic wastewater elevated COVID-19 testing charges by as a lot as 13-fold. As soon as an occupant examined optimistic, isolation and call tracing helped forestall additional unfold of the virus. 

The method enabled early detection of 85 % of COVID-19 instances on the campus, researchers reported within the August 10, 2021 concern of mSystems. In different phrases, wastewater samples examined optimistic earlier than most particular person case diagnoses.

Roughly 10,000 college students lived on the UC San Diego campus through the 2020-2021 educational 12 months, with low COVID-19 case charges because of the various threat mitigation, viral detection and intervention parts that make up the Return to Be taught program. Credit score: Erik Jepsen/UC San Diego.

“College campuses particularly profit from wastewater surveillance as a way to avert COVID-19 outbreaks, as they’re full of largely asymptomatic populations, and are potential sizzling spots for transmission that necessitate frequent diagnostic testing,” mentioned first writer Smruthi Karthikeyan, PhD, an environmental engineer and postdoctoral researcher at UC San Diego College of Drugs. 

Karthikeyan led the examine with senior writer Rob Knight, PhD, professor and director of the Middle for Microbiome Innovation at UC San Diego.

Wastewater screening is an integral half of UC San Diego’s Return to Be taught program, an evidence-based method that has allowed the college to supply on-campus housing and in-person courses and analysis alternatives all through most of the pandemic. 

Return to Be taught depends on three pillars: threat mitigation, viral detection and intervention. With roughly 10,000 college students on campus through the 2020-2021 educational 12 months, the various elements of this system stored COVID-19 case charges a lot decrease than the encompassing neighborhood and in comparison with most school campuses, sustaining a positivity price of lower than 1 % throughout that point. The Return to Be taught program, together with wastewater testing, has turn out to be a mannequin for different universities, Okay-12 faculty districts and areas.  

Each morning, seven days per week, a staff of college students and employees in matching t-shirts deploys throughout campus on golf carts to gather sewage samples from 126 assortment robots set as much as monitor 350 buildings. By 10 a.m., they return to Knight’s lab on the College of Drugs. 

A web based dashboard tracks COVID-positive wastewater detection on the UC San Diego campus and makes it accessible to the general public. Credit score: UC San Diego

There, Karthikeyan and staff course of the sewage utilizing a different kind of robot, which concentrates the virus utilizing magnetic nanoparticles, then extracts RNA — the genetic materials that makes up the genomes of viruses like SARS-CoV-2 — from the samples. Polymerase chain response (PCR) testing is used to seek for the virus’ signature genes. 

When the virus is detected, automated however focused messages are despatched by a campus-wide system to individuals related to affected buildings, resembling college students, employees and college, recommending they be examined for the virus as quickly as attainable. The info is added to a public dashboard.  

Since its inception, the staff has labored continuously to optimize the method, Karthikeyan mentioned. The present automated method has dramatically decreased the sample-to-result turnaround time 20-fold; now 5 hours for 96 samples. By miniaturizing the samples, the researchers have decreased processing prices to $13 per pattern. Knight estimates the method exceeds the dimensions of related surveillance packages by 10- to 100-fold. The following step, he mentioned, can be to deploy fast strategies to check for SARS-CoV-2 variants, together with delta, in actual time. 

“This method demonstrates how the various totally different elements of UC San Diego can work collectively as a system to maintain campus protected,” Knight mentioned. “This work required not simply advances in viral pattern processing, however groups together with Logistics, Environmental Well being and Security, campus and well being system IT, Services Administration, and plenty of others, in addition to management from the Return to Be taught program to make it occur. We at the moment are serving to different campuses and organizations replicate this success, which has potential not only for COVID-19, however for a lot of different stool-borne pathogens, together with influenza, in future.”

Reference: “Speedy, Giant-Scale Wastewater Surveillance and Automated Reporting System Allow Early Detection of Practically 85% of COVID-19 Cases on a College Campus” by 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 Okay. Martin and Rob Knight, 10 August 2021, mSystems.
DOI: 10.1128/mSystems.00793-21

Co-authors embrace: 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 Okay. Martin, all at UC San Diego.

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