StrainHub: a phylogenetic tool to construct pathogen transmission networks.

Area of Science:

• Epidemiology
• Computational Biology
• Phylogenetics

Background:

• Network analysis is crucial for understanding infectious disease epidemiology.
• Traditional methods often rely on direct contact tracing.
• Integrating pathogen metadata with phylogenetic trees offers a novel approach.

Purpose of the Study:

• To introduce StrainHub, a web-based application for reconstructing pathogen transmission networks.
• To enable derivation of insights into pathogen lineage dynamics.
• To support the development of targeted infection control strategies.

Main Methods:

• Users input phylogenetic trees and associated metadata (e.g., host species, isolation location).
• StrainHub generates transmission networks based on metadata character state changes mapped onto the phylogenetic tree.
• Calculates centrality metrics (betweenness, closeness, degree, source/hub ratio) on network nodes.

Main Results:

• StrainHub successfully generates transmission networks from diverse phylogenetic and metadata inputs.
• Provides visualized networks with node centrality metrics.
• Outputs include reconstructed trees and exportable network data for further analysis.

Conclusions:

• StrainHub offers a novel computational tool for pathogen transmission network reconstruction.
• Facilitates deeper understanding of pathogen evolution and spread.
• Supports informed public health and infection control decision-making.