Surveillance-to-Diagnostic Testing Program for Asymptomatic SARS-CoV-2 Infections on a Large, Urban Campus in Fall 2020

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Abstract

Six months into the COVID-19 pandemic, college campuses faced uncertainty regarding the likely prevalence and spread of disease, necessitating large-scale testing to help guide policy following re-entry.

Methods:

A SARS-CoV-2 testing program combining pooled saliva sample surveillance leading to diagnosis and intervention surveyed over 112,000 samples from 18,029 students, staff and faculty, as part of integrative efforts to mitigate transmission at the Georgia Institute of Technology in Fall 2020.

Results:

Cumulatively, we confirmed 1,508 individuals diagnostically, 62% of these through the surveillance program and the remainder through diagnostic tests of symptomatic individuals administered on or off campus. The total strategy, including intensification of testing given case clusters early in the semester, was associated with reduced transmission following rapid case increases upon entry in Fall semester in August 2020, again in early November 2020, and upon re-entry for Spring semester in January 2021. During the Fall semester daily asymptomatic test positivity initially peaked at 4.1% but fell below 0.5% by mid-semester, averaging 0.84% across the Fall semester, with similar levels of control in Spring 2021.

Conclusions:

Owing to broad adoption by the campus community, we estimate that the program protected higher risk staff and faculty while allowing some normalization of education and research activities.

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  1. SciScore for 10.1101/2021.01.28.21250700: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementConsent: For safety and simplicity, a saliva-based test was developed, and used with informed consent of all participants.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Leaving six wells for controls, 15×15 = 225 individuals are surveyed per plate, using Integra robots to generate pools, Kingfisher robots to isolate RNA, and QuantStudio quantitative RT-PCR testing.
    Integra
    suggested: None

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).


    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.


    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


    Results from JetFighter: We did not find any issues relating to colormaps.


    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.