Scholarlink

Motivation: The multinational outbreak of human mpox virus (MPOXV) in the summer of 2022 highlighted the need for improved tools to assist public health officials in tracking and responding to new local outbreak clusters. Phylogenetic characterization of MPOXV can support local case investigations by shedding light on whether the virus may have been acquired locally, belongs to endemically circulating strains, or represents a new introduction. In this work, we adapt clustering tools developed for SARS-CoV-2 surveillance to track local MPOXV outbreaks. Results: We present an adapted version of cov2clusters, originally developed for monitoring SARS-CoV-2 cases in British Columbia. The tool offers stable cluster codes between trees and has been improved with optimizations in execution time and memory management. We also demonstrate the advantages of adapting previously developed tools, validated against the pathogen they were originally designed for, to monitor a new pathogen. This approach can conserve resources that would otherwise be spent on developing new tools and facilitate faster deployment in public health settings.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Adapting the Cov2clusters Tool for Clustering MPOXV Whole Genome Sequences

  • 会议论文

  • 发表日期：

    2026年

查看全文
  • Eric CH Chen,
  • Tara Newman,
  • John Tyson,
  • Anthea Lam,
  • Michael Chan,
  • Agatha Jassem,
  • Natalie Prystajecky,
  • Shannon Russell,
  • James Zlosnik

摘要

Motivation: The multinational outbreak of human mpox virus (MPOXV) in the summer of 2022 highlighted the need for improved tools to assist public health officials in tracking and responding to new local outbreak clusters. Phylogenetic characterization of MPOXV can support local case investigations by shedding light on whether the virus may have been acquired locally, belongs to endemically circulating strains, or represents a new introduction. In this work, we adapt clustering tools developed for SARS-CoV-2 surveillance to track local MPOXV outbreaks. Results: We present an adapted version of cov2clusters, originally developed for monitoring SARS-CoV-2 cases in British Columbia. The tool offers stable cluster codes between trees and has been improved with optimizations in execution time and memory management. We also demonstrate the advantages of adapting previously developed tools, validated against the pathogen they were originally designed for, to monitor a new pathogen. This approach can conserve resources that would otherwise be spent on developing new tools and facilitate faster deployment in public health settings.