ArticleHeredity2011
Reconstructing disease outbreaks from genetic data: a graph approach.
Article in Heredity, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 95 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
95 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Interpreting whole genome sequencing for investigating tuberculosis transmission: a systematic review.BMC medicine · 2016Pooled it
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- The clinical impact and dissemination of carbapenemase-producingMicrobiology spectrum · 2025Article
- A graph homomorphism approach for unraveling histories of metastatic cancers and viral outbreaks under evolutionary constraints.Nature communications · 2025Article
- Global Circulation Dynamics and Its Determinants of Dengue Virus: A Network Evolution and Model Study from 1990 to 2019.Viruses · 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
- Population structure and history ofMicrobiology spectrum · 2024Article
- AUTO-TUNE: SELECTING THE DISTANCE THRESHOLD FOR INFERRING HIV TRANSMISSION CLUSTERS.bioRxiv : the preprint server for biology · 2024Article
- HAIviz: an interactive dashboard for visualising and integrating healthcare-associated genomic epidemiological data.Microbial genomics · 2024Article
- Inference of Infectious Disease Transmission through a Relaxed Bottleneck Using Multiple Genomes Per Host.Molecular biology and evolution · 2024Article
- AUTO-TUNE: selecting the distance threshold for inferring HIV transmission clusters.Frontiers in bioinformatics · 2024Article
- Association between negative psychology and sleep quality in dialysis patients during the COVID-19 pandemic.Nursing open · 2023Article
- ComparingEpidemiology and infection · 2023Article
- GraphSNP: an interactive distance viewer for investigating outbreaks and transmission networks using a graph approach.BMC bioinformatics · 2023Article
- TransFlow: a Snakemake workflow for transmission analysis of Mycobacterium tuberculosis whole-genome sequencing data.Bioinformatics (Oxford, England) · 2023Article
- SARS-CoV-2 evolution among patients with immunosuppression in a nosocomial cluster of a Japanese medical center during the Delta (AY.29 sublineage) surge.Frontiers in microbiology · 2023Article
- Molecular source attribution.PLoS computational biology · 2022Article
- SOPHIE: Viral outbreak investigation and transmission history reconstruction in a joint phylogenetic and network theory framework.Cell systems · 2022Article
35 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Epidemiology and public health planning will increasingly rely on the analysis of genetic sequence data. In particular, genetic data coupled with dates and locations of sampled isolates can be used to reconstruct the spatiotemporal dynamics of pathogens during outbreaks. Thus far, phylogenetic methods have been used to tackle this issue. Although these approaches have proved useful for informing on the spread of pathogens, they do not aim at directly reconstructing the underlying transmission tree. Instead, phylogenetic models infer most recent common ancestors between pairs of isolates, which can be inadequate for densely sampled recent outbreaks, where the sample includes ancestral and descendent isolates. In this paper, we introduce a novel method based on a graph approach to reconstruct transmission trees directly from genetic data. Using simulated data, we show that our approach can efficiently reconstruct genealogies of isolates in situations where classical phylogenetic approaches fail to do so. We then illustrate our method by analyzing data from the early stages of the swine-origin A/H1N1 influenza pandemic. Using 433 isolates sequenced at both the hemagglutinin and neuraminidase genes, we reconstruct the likely history of the worldwide spread of this new influenza strain. The presented methodology opens new perspectives for the analysis of genetic data in the context of disease outbreaks.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.