Speaker
Description
Understanding transmission clusters is essential to uncovering the dynamics of viral
epidemics, identifying outbreak drivers, and guiding effective public health responses. Cluster
analysis combines genomic and epidemiological data to trace transmission pathways and
generate actionable insights to curb disease spread.
ClusterFinder, developed within the EU-funded SEQ4EPI project, is a robust tool
designed to identify and analyze transmission clusters across viral pathogens. This workflow
incorporates sequence alignment, mutation analysis, phylogenetic tree construction, and
cluster identification using pathogen-specific thresholds. Initially tailored to SARS-CoV-2, it
has been expanded to include Respiratory Syncytial Virus (RSV) and Influenza viruses,
ensuring versatility across respiratory pathogens.
ClusterFinder has demonstrated significant results in multiple applications. For SARS-
CoV-2, the tool identified clusters across six epidemic waves at the Hospices Civils de Lyon,
spanning variants from Alpha to Omicron, including nosocomial clusters validated by
epidemiological data. For RSV-A, cluster detection within the A.D.1.5 and A.D.1.6 clades
revealed potential transmission events, while RSV-B and Influenza B analyses were limited
by lower sequence counts. Influenza A(H1N1) and A(H3N2) studies leveraged hemagglutinin
and neuraminidase gene data, identifying clusters that advanced understanding of
transmission dynamics.
With its ability to process diverse datasets and pathogens, ClusterFinder provides a
powerful framework for real-time genomic surveillance, delivering critical insights for
managing viral epidemics.
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