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Comparative cost-effectiveness of SARS-CoV-2 testing strategies in the USA: a modelling study.

Zhanwei Du | Abhishek Pandey | Yuan Bai | Meagan C Fitzpatrick | Matteo Chinazzi | Ana Pastore Y Piontti | Michael Lachmann | Alessandro Vespignani | Benjamin J Cowling | Alison P Galvani | Lauren Ancel Meyers
The Lancet. Public health | 2021

To mitigate the COVID-19 pandemic, countries worldwide have enacted unprecedented movement restrictions, physical distancing measures, and face mask requirements. Until safe and efficacious vaccines or antiviral drugs become widely available, viral testing remains the primary mitigation measure for rapid identification and isolation of infected individuals. We aimed to assess the economic trade-offs of expanding and accelerating testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) across the USA in different transmission scenarios.

Pubmed ID: 33549196

Research resources used in this publication

None found

Antibodies used in this publication

None found

Associated grants

  • Agency: NIGMS NIH HHS, United States
    Id: U01 GM087719
  • Agency: ACL HHS, United States
    Id: U01IP001137
  • Agency: CDC HHS, United States
    Id: U01P001136-01-01
  • Agency: NIAID NIH HHS, United States
    Id: K01 AI141576
  • Agency: NCIRD CDC HHS, United States
    Id: U01 IP001136
  • Agency: NCIRD CDC HHS, United States
    Id: U01 IP001137
  • Agency: CDC HHS, United States
    Id: CDC-HHS-6U01IP001137-01
  • Agency: NIAID NIH HHS, United States
    Id: R01 AI151176

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MATLAB (tool)

RRID:SCR_001622

Multi paradigm numerical computing environment and fourth generation programming language developed by MathWorks. Allows matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages, including C, C++, Java, Fortran and Python. Used to explore and visualize ideas and collaborate across disciplines including signal and image processing, communications, control systems, and computational finance.

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SARS-CoV-2 mutation effects and 3D structure prediction from sequence covariation (tool)

RRID:SCR_018759

Portal for quantitative models using virus sequence variation to predict mutation effects for SARS-CoV-2 proteins, alignments to homologs in other viruses, 3D structures, evolutionarily coupled residues and structure predictions.

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