Using Haplotype-Based Artificial Intelligence to Evaluate SARS-CoV-2 Novel Variants and Mutations.

Journal: JAMA network open
PMID: 36809468

Abstract

IMPORTANCE: Earlier detection of emerging novel SARS-COV-2 variants is important for public health surveillance of potential viral threats and for earlier prevention research. Artificial intelligence may facilitate early detection of SARS-CoV2 emerging novel variants based on variant-specific mutation haplotypes and, in turn, be associated with enhanced implementation of risk-stratified public health prevention strategies.

Authors

  • Lue Ping Zhao
    Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington.
  • Seth Cohen
    Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington.
  • Michael Zhao
    QuantFu Inc, Boston, Massachusetts.
  • Margaret Madeleine
    Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington.
  • Thomas H Payne
    Department of Medicine, University of Washington School of Medicine, Seattle.
  • Terry P Lybrand
    Quintepa Computing LLC, Nashville, Tennessee.
  • Daniel E Geraghty
    Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, Washington.
  • Keith R Jerome
    Vaccine and Infectious Disease, Fred Hutchinson Cancer Research Center, Seattle, Washington; Virology Division, University of Washington, Seattle, Washington; Department of Laboratory Medicine, University of Washington, Seattle, Washington.
  • Lawrence Corey
    Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington.

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