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2 results

  • Chapter 12 - Testing Strategies to Mitigate COVID-19 Disease Spread

  • Edited by Steven C. Schachter, Harvard Medical School, Wade E. Bolton, VentureWell/Rapid Acceleration of Diagnostics (RADx)
  • Book:
    Accelerating Diagnostics in a Time of Crisis
    Published online:
    06 January 2024
    Print publication:
    07 March 2024, pp 236-249

  • Summary

    The expansion of COVID-19 diagnostic testing across the USA was – and continues to be – essential to slowing and preventing the spread of COVID-19. This chapter summarizes the efforts of the Rapid Acceleration of Diagnostics (RADx®) Tech team to (1) provide science-based outputs to assess and guide specific mitigation and testing strategies, (2) demonstrate how COVID-19 prevention and containment efforts can most effectively be combined with the latest testing strategies to minimize the spread of the virus in a semi-contained population, and (3) deliver personal recommendations based on how likely an individual is to get COVID-19 and spread it to other people. Details are provided on a data-driven model to mitigate disease spread that is based on a simple counting exercise known in different disciplines as a control volume approach or queueing theory. The effects of social distancing, mask wearing, vaccination, and contact tracing on disease spread and testing requirements are explored. The US government public policy effect on testing is also discussed.

  • Real World Performance of SARS-CoV-2 Antigen Rapid Diagnostic Tests in Various Clinical Settings

  • Part of
  • Gili Regev-Yochay, Or Kriger, Michael J. Mina, Sharon Beni, Carmit Rubin, Bella Mechnik, Sabrina Hason, Elad Biber, Bian Nadaf, Yitshak Kreiss, Sharon Amit
  • Journal:
    Infection Control & Hospital Epidemiology / Accepted manuscript
    Published online by Cambridge University Press:
    02 March 2022, pp. 1-20
  • Objective:

    To assess the validity of Antigen rapid diagnostic tests (Ag-RDT) for SARS-CoV-2 as decision support tool in various hospital-based clinical settings.

    Design:

    Retrospective cohort study among symptomatic and asymptomatic patients and Healthcare workers (HCW).

    Setting:

    A large tertiary teaching medical center serving as a major COVID-19 hospitalizing facility.

    Participants and Methods:

    Ag-RDTs’ performance was assessed in three clinical settings: 1. Symptomatic patients and HCW presenting at the Emergency Departments 2. Asymptomatic patients screened upon hospitalization 3. HCW of all sectors tested at the HCW clinic following exposure.

    Results:

    We obtained 5172 samples from 4595 individuals, who had both Ag-RDT and quantitative real-time PCR (qRT-PCR) results available. Of these, 485 samples were positive by qRT-PCR. The positive percent agreement (PPA) of Ag-RDT was greater for lower cycle threshold (Ct) values, reaching 93% in cases where Ct-value was <25 and 85% where Ct-value was <30. PPA was similar between symptomatic and asymptomatic individuals. We observed a significant correlation between Ct-value and time from infection onset (p<0.001).

    Conclusions:

    Ag-RDT are highly sensitive to the infectious stage of COVID-19 manifested by either high viral load (lower Ct) or proximity to infection, whether patient is symptomatic or asymptomatic. Thus, this simple-to-use and inexpensive detection method can be used as a decision support tool in various in-hospital clinical settings, assisting patient flow and maintaining sufficient hospital staffing.