Validating and modeling the impact of high-frequency rapid antigen screening on COVID-19 spread and outcomes

  1. Beatrice Nash
  2. Anthony Badea
  3. Ankita Reddy
  4. Miguel Bosch
  5. Nol Salcedo
  6. Adam R. Gomez
  7. Alice Versiani
  8. Gislaine Celestino Dutra Silva
  9. Thayza Maria Izabel Lopes dos Santos
  10. Bruno H. G. A. Milhim
  11. Marilia M Moraes
  12. Guilherme Rodrigues Fernandes Campos
  13. Flávia Quieroz
  14. Andreia Francesli Negri Reis
  15. Mauricio L. Nogueira
  16. Elena N. Naumova
  17. Irene Bosch
  18. Bobby Brooke Herrera

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Abstract

High frequency screening of populations has been proposed as a strategy in facilitating control of the COVID-19 pandemic. We use computational modeling, coupled with clinical data from rapid antigen tests, to predict the impact of frequent viral antigen rapid testing on COVID-19 spread and outcomes. Using patient nasal or nasopharyngeal swab specimens, we demonstrate that the sensitivity/specificity of two rapid antigen tests compared to quantitative real-time polymerase chain reaction (qRT-PCR) are 82.0%/100% and 84.7%/85.7%, respectively; moreover, sensitivity correlates directly with viral load. Based on COVID-19 data from three regions in the United States and São José do Rio Preto, Brazil, we show that high frequency, strategic population-wide rapid testing, even at varied accuracy levels, diminishes COVID-19 infections, hospitalizations, and deaths at a fraction of the cost of nucleic acid detection via qRT-PCR. We propose large-scale antigen-based surveillance as a viable strategy to control SARS-CoV-2 spread and to enable societal re-opening.

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  1. ScreenIT

    SciScore for 10.1101/2020.09.01.20184713: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Antibodies
    SentencesResources
    Each rapid antigen test has a control area adjacent to the paper absorbent pad; the control is an anti-mouse Fc domain antibody (Leinco Technologies, Fenton, MO, USA) that will capture any of the antibody-conjugated gold nanoparticles to generate a control visual signal.
    anti-mouse Fc domain
    suggested: None
    A visual signal at the test area reflects SARS- CoV-2 N or S that is “sandwiched” between an anti-N or anti-S antibody adsorbed to the nitrocellulose membrane and a second anti-N or anti-S antibody covalently coupled to visible gold nanoparticles.
    anti-N
    suggested: None
    anti-S
    suggested: None

    Results from OddPub: Thank you for sharing your code and data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    There are important limitations to be considered in this model. Differences in disease reporting between the geographical regions and the incomplete nature of COVID-19 surveillance data, often due to the lack of testing or delays in reporting, are not considered in the model. It is imperative that the testing results, hospitalization and death statistics, and changes in protocol are reported in real-time to scientists and policy makers so that models can be accurately tuned as the pandemic develops. Infectivity variations between individuals is also not applied to this model, and future clinical studies should gather data on asymptomatic presenting COVID-19 cases. Non- compliant quarantine behaviors and possible infections during testing waiting times are also not included in the calculations. The model also does not take into account infrastructural limitations (eg. hospital capacity) and. Though the rapid antigen test offers several advantages such as affordability, fast turnaround time, and ease of mass production, we are assuming that there are systems in place to implement frequent and safe low-cost screening across different communities and settings. Our model underscores the need for a point-of-care or at-home test for frequent screening, particularly as lockdown restrictions ease. Regulatory agencies can work towards evaluating rapid tests to alternative standards other than comparison to high sensitivity molecular diagnostics, as our model shows that frequency and sc...

    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

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  2. Version published to 10.1101/2020.09.01.20184713 on medRxiv