BadTrIP

BadTrIP infers host-to-host transmission pathways during infectious disease outbreaks by integrating within-host pathogen genetic variation and epidemiological data within a Bayesian evolutionary framework.

Key Features:

• Bayesian Framework: Models evolution of pathogen populations and transmission dynamics, including transmission bottlenecks, while accounting for sequencing errors.
• Genomic Variant Utilization: Uses within-host genomic variants identified via heterozygous nucleotide base calls as markers to link cases without reconstructing haplotypes.
• No Haplotype Reconstruction Required: Assumes genomic variants are unlinked, avoiding reconstruction of individual haplotypes.
• Integration with Epidemiological Data: Combines genetic variation with epidemiological metadata to reconstruct the direction, timing, and sequence of host-to-host transmissions.
• Robustness and Accuracy: Demonstrated robustness across simulation scenarios and shown in applications to accurately infer transmission events and to outperform existing methods in simulations.

Scientific Applications:

• Outbreak investigations: Reconstructs transmission histories in outbreak settings to elucidate spread within and between hosts using genomic and epidemiological data.
• Ebola 2014 analysis: Applied to reconstruct the transmission history of the early stages of the 2014 Ebola outbreak.

Methodology:

Inputs pathogen genomic sequences from multiple hosts and epidemiological data; employs a Bayesian model of pathogen evolution and transmission that includes bottlenecks and accounts for sequencing errors; infers host-to-host transmission by combining within-host variant (heterozygous nucleotide base call) data with epidemiological context while assuming variants are unlinked so haplotype reconstruction is not required.