ArticlePLoS computational biology2018
Bayesian reconstruction of transmission within outbreaks using genomic variants.
Article in PLoS computational biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers.
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Who cites it
51 citing papers in PubMed.
- Strain-level transmission inference across multi-kingdom metagenomic data using TRACS.Nature microbiology · 2026Article
- Clinical utility and limitations of whole-genome sequencing via nanopore technology and Bayesian modeling for outbreak transmission inference.Antimicrobial resistance and infection control · 2026Article
- A graph homomorphism approach for unraveling histories of metastatic cancers and viral outbreaks under evolutionary constraints.Nature communications · 2025Article
- Apollo: a comprehensive GPU-powered within-host simulator for viral evolution and infection dynamics across population, tissue, and cell.Nature communications · 2025Article
- Population sequencing for phylogenetic diversity and transmission analyses.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- JUNIPER: Reconstructing Transmission Events from Next-Generation Sequencing Data at Scale.Research square · 2025Article
- JUNIPER: Reconstructing Transmission Events from Next-Generation Sequencing Data at Scale.medRxiv : the preprint server for health sciences · 2025Article
- Bayesian estimation of transmission networks for infectious diseases.Journal of mathematical biology · 2025Article
- Signatures of transmission in within-host Mycobacterium tuberculosis complex variation: a retrospective genomic epidemiology study.The Lancet. Microbe · 2025Article
- Apollo: A comprehensive GPU-powered within-host simulator for viral evolution and infection dynamics across population, tissue, and cell.bioRxiv : the preprint server for biology · 2024Article
- Genomic analysis of inter-hospital transmission of vancomycin-resistantAntimicrobial agents and chemotherapy · 2024Article
- Inference of Infectious Disease Transmission through a Relaxed Bottleneck Using Multiple Genomes Per Host.Molecular biology and evolution · 2024Article
- Inferring Viral Transmission Pathways from Within-Host Variation.medRxiv : the preprint server for health sciences · 2023Article
- Within-host diversity improves phylogenetic and transmission reconstruction of SARS-CoV-2 outbreaks.eLife · 2023Article
- ComparingEpidemiology and infection · 2023Article
- A Noncoding A-to-U Kozak Site Change Related to the High Transmissibility of Alpha, Delta, and Omicron VOCs.Molecular biology and evolution · 2023Article
- Challenges in Harnessing Shared Within-Host Severe Acute Respiratory Syndrome Coronavirus 2 Variation for Transmission Inference.Open forum infectious diseases · 2023Article
- Evaluating the potential of whole-genome sequencing for tracing transmission routes in experimental infections and natural outbreaks of bovine respiratory syncytial virus.Veterinary research · 2022Article
- Pneumococcal within-host diversity during colonization, transmission and treatment.Nature microbiology · 2022Article
- Molecular source attribution.PLoS computational biology · 2022Article
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Authors and funding
4 authors.
Funding
Abstract
Pathogen genome sequencing can reveal details of transmission histories and is a powerful tool in the fight against infectious disease. In particular, within-host pathogen genomic variants identified through heterozygous nucleotide base calls are a potential source of information to identify linked cases and infer direction and time of transmission. However, using such data effectively to model disease transmission presents a number of challenges, including differentiating genuine variants from those observed due to sequencing error, as well as the specification of a realistic model for within-host pathogen population dynamics. Here we propose a new Bayesian approach to transmission inference, BadTrIP (BAyesian epiDemiological TRansmission Inference from Polymorphisms), that explicitly models evolution of pathogen populations in an outbreak, transmission (including transmission bottlenecks), and sequencing error. BadTrIP enables the inference of host-to-host transmission from pathogen sequencing data and epidemiological data. By assuming that genomic variants are unlinked, our method does not require the computationally intensive and unreliable reconstruction of individual haplotypes. Using simulations we show that BadTrIP is robust in most scenarios and can accurately infer transmission events by efficiently combining information from genetic and epidemiological sources; thanks to its realistic model of pathogen evolution and the inclusion of epidemiological data, BadTrIP is also more accurate than existing approaches. BadTrIP is distributed as an open source package (https://bitbucket.org/nicofmay/badtrip) for the phylogenetic software BEAST2. We apply our method to reconstruct transmission history at the early stages of the 2014 Ebola outbreak, showcasing the power of within-host genomic variants to reconstruct transmission events.
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