• HOME
  • NEWS
  • EXPLORE
    • CAREER
      • Companies
      • Jobs
    • EVENTS
    • iGEM
      • News
      • Team
    • PHOTOS
    • VIDEO
    • WIKI
  • BLOG
  • COMMUNITY
    • FACEBOOK
    • INSTAGRAM
    • TWITTER
Tuesday, August 5, 2025
BIOENGINEER.ORG
No Result
View All Result
  • Login
  • HOME
  • NEWS
  • EXPLORE
    • CAREER
      • Companies
      • Jobs
        • Lecturer
        • PhD Studentship
        • Postdoc
        • Research Assistant
    • EVENTS
    • iGEM
      • News
      • Team
    • PHOTOS
    • VIDEO
    • WIKI
  • BLOG
  • COMMUNITY
    • FACEBOOK
    • INSTAGRAM
    • TWITTER
  • HOME
  • NEWS
  • EXPLORE
    • CAREER
      • Companies
      • Jobs
        • Lecturer
        • PhD Studentship
        • Postdoc
        • Research Assistant
    • EVENTS
    • iGEM
      • News
      • Team
    • PHOTOS
    • VIDEO
    • WIKI
  • BLOG
  • COMMUNITY
    • FACEBOOK
    • INSTAGRAM
    • TWITTER
No Result
View All Result
Bioengineer.org
No Result
View All Result
Home NEWS Science News Immunology

New testing strategy can speed up COVID-19 test results for healthcare workers

Bioengineer by Bioengineer
April 26, 2021
in Immunology
Reading Time: 3 mins read
0
Share on FacebookShare on TwitterShare on LinkedinShare on RedditShare on Telegram

In The Journal of Molecular Diagnostics investigators share a new methodology for testing pooled samples that maximizes the proportion of samples resolved after a single round of testing

IMAGE

Credit: The Journal of Molecular Diagnostics

Philadelphia, April 26, 2021 – Fast turnaround of COVID-19 test results for healthcare workers is critical. Investigators have now developed a COVID-19 testing strategy that maximizes the proportion of negative results after a single round of testing, allowing prompt notification of results. The method also reduces the need for increasingly limited test reagents, as fewer additional tests are required. Their strategy is described in the Journal of Molecular Diagnostics, published by Elsevier.

There is an urgent need to reduce the spread of COVID-19 transmission in hospitals and care facilities and to maintain adequate levels of staffing. Group testing strategies with pooled samples have been proposed to increase capacity; however, the currently used strategies are slow.

“One of the main hurdles to initiating a comprehensive hospital staff testing program is the large number of staff requiring testing and the rapid turnaround times that would be required to make any screening strategy successful,” explained lead investigators Graeme Black, DPhil, and John Henry McDermott, MD, both from the Division of Evolution and Genomic Sciences, School of Biological Sciences, University of Manchester, Manchester, UK. “Using the method we have developed, any laboratory could adapt their testing scheme based on the current throughput and the current prevalence of infection in the population, facilitating a data-driven testing strategy.”

Traditional Dorfman sequential (DS) pooling combines multiple samples and, if a pool test returns positive, all of the constituent samples undergo further testing. In a healthcare setting, this means that even individuals who ultimately test negative for COVID-19 will have to isolate. The investigators developed a nonadaptive combinatorial (NAC) pooling approach that tests the same sample in several simultaneously assayed pools. The algorithm assumes initially that each sample is positive. It then attempts to disprove this assumption by finding a well in which the sample has been placed that has tested as negative. Then another algorithm is used to find positive wells that contain a single sample on the list of the remaining potentially positive samples. Indeterminate samples are retested.

To establish a suitable limit of detection for pooling, nasopharyngeal samples of known SARS-CoV-2 status were placed in two pools, each containing 14 SARS-CoV-2 negative samples and one SARS-CoV-2 positive sample, with the positive samples at differing viral loads. Pooling matrices were generated for 700, 350, and 250 samples, with each sample assigned to 2, 4, and 5 wells, respectively. The samples were also tested in a DS testing scheme. The efficacy of each matrix was tested under different SARS-CoV-2 prevalence levels of 0.1 percent, 3 percent, 7 percent, and 10 percent of the population.

All NAC matrices performed well at low prevalence levels, with an average of 585 tests saved per assay in the 700 sample matrix. In simulations of low-to-medium prevalence levels (0.1 percent – 3 percent), which is the prevalence expected in an asymptomatic healthcare worker population, all the NAC matrices required fewer retests than the DS testing scheme. However, as the population prevalence increased, the performance of each matrix deteriorated.

“Pooling becomes increasingly useful as the population prevalence of SARS-CoV-2 decreases,” Prof. Black and Dr. McDermott observed. “Initially the most conservative matrix, 250 samples, should be used to determine the prevalence level. As the prevalence falls, the use of less tolerant but higher throughput assays could be used, such as the 700 sample pool.”

The matrices and system to decode the results are freely available (http://www.samplepooling.com) and laboratories can choose the matrix that best suits their current population prevalence and sample size, facilitating a context-specific, relatively low cost data-driven testing approach.

“Many high-throughput testing schemes for SARS-CoV-2 detection have been developed over the past year. We illustrate the potential power that adaptable automated, innovative mathematical approaches have to increase COVID-19 diagnostic capability in a safe manner. Such an approach could reach far greater numbers, save lives, and be delivered in a sustainable way. Undoubtedly, this has considerable relevance to other future population-based screening approaches,” Prof. Black and Dr. McDermott concluded.

###

Media Contact
Eileen Leahy
[email protected]

Original Source

https://www.elsevier.com/about/press-releases/research-and-journals/new-testing-strategy-can-speed-up-covid19-test-results-for-healthcare-workers

Related Journal Article

http://dx.doi.org/10.1016/j.jmoldx.2021.01.010

Tags: DiagnosticsHealth ProfessionalsInfectious/Emerging DiseasesMedicine/HealthPublic Health
Share12Tweet8Share2ShareShareShare2

Related Posts

IMAGE

UMass Amherst grad student awarded fellowship for food allergy research

July 23, 2021
IMAGE

Less-sensitive COVID-19 tests may still achieve optimal results if enough people tested

July 22, 2021

Public trust in CDC, FDA, and Fauci holds steady, survey shows

July 20, 2021

USC study shows male-female differences in immune cell function

July 19, 2021
Please login to join discussion

POPULAR NEWS

  • blank

    Neuropsychiatric Risks Linked to COVID-19 Revealed

    71 shares
    Share 28 Tweet 18
  • Overlooked Dangers: Debunking Common Myths About Skin Cancer Risk in the U.S.

    61 shares
    Share 24 Tweet 15
  • Predicting Colorectal Cancer Using Lifestyle Factors

    46 shares
    Share 18 Tweet 12
  • Dr. Miriam Merad Honored with French Knighthood for Groundbreaking Contributions to Science and Medicine

    46 shares
    Share 18 Tweet 12

About

We bring you the latest biotechnology news from best research centers and universities around the world. Check our website.

Follow us

Recent News

Diastereodivergent Routes to Multi-Substituted Cycloalkanes

Spatial Metabolomics Reveals Lasting Stroke Brain Changes

Rethinking Resilience in Post-Nuclear Food Trade Recovery

  • Contact Us

Bioengineer.org © Copyright 2023 All Rights Reserved.

Welcome Back!

Login to your account below

Forgotten Password?

Retrieve your password

Please enter your username or email address to reset your password.

Log In
No Result
View All Result
  • Homepages
    • Home Page 1
    • Home Page 2
  • News
  • National
  • Business
  • Health
  • Lifestyle
  • Science

Bioengineer.org © Copyright 2023 All Rights Reserved.