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Development of a Framework for Establishing 'Gold Standard' Outbreak Data from Submitted SARS-CoV-2 Genome Samples.

Yannan Shen1, Russell Steele2, David Buckeridge1

  • 1School of Population and Global Health, McGill University, Canada.

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|August 23, 2024
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Summary

Genomic data reveal new viral variants, but submission delays hinder real-time tracking. A Bayesian change point detection method establishes reliable outbreak onset dates using genomic data, aiding variant surveillance.

Keywords:
Bayesian change point detectionGenomic surveillanceoutbreak detection

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Area of Science:

  • Epidemiology
  • Genomic Surveillance
  • Computational Biology

Background:

  • Genomic data are crucial for tracking respiratory virus variants and their spread.
  • Delays in genomic data submission limit prospective surveillance capabilities.
  • Limited research exists on utilizing genomic data for evaluating aberration detection in surveillance systems.

Purpose of the Study:

  • To establish 'gold standard' outbreak onset dates using genomic submission data.
  • To evaluate the utility of genomic data for aberration detection in surveillance.
  • To present a framework for using global genomic data for variant outbreak analysis.

Main Methods:

  • Employed a Bayesian online change point detection algorithm (BOCP).
  • Utilized submitted genome samples for respiratory viruses across multiple countries.
  • Compared models with different data transformations and parameter values.

Main Results:

  • BOCP effectively detected change points indicative of outbreak onset.
  • Change point detection was robust to variations in parameter settings.
  • Data transformations were identified as essential for accurate change point detection.

Conclusions:

  • A framework using global genomic submission data can establish 'gold standard' outbreak onset dates.
  • Genomic data, despite submission delays, can be valuable for evaluating surveillance systems.
  • This approach enhances the understanding of new viral variant emergence and spread.