ArticleAmerican journal of epidemiology2017
Shared Genomic Variants: Identification of Transmission Routes Using Pathogen Deep-Sequence Data.
Article in American journal of epidemiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers, 2 of them syntheses that pooled it.
What it found
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
61 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Equitable data sharing in epidemics and pandemics.BMC medical ethics · 2021Pooled it
- Interpreting whole genome sequencing for investigating tuberculosis transmission: a systematic review.BMC medicine · 2016Pooled it
- Global status, bias risks, and ecological integration of wild bat and rodent virome research.One health (Amsterdam, Netherlands) · 2026Review
- Identification and masking of artifactual and misleading within-host variants in deep-sequencing SARS-CoV-2 data.Molecular biology and evolution · 2026Article
- Mapping the resistance landscape: A large-scale study of polymyxin-resistant pathogens circulating in low-and middle-income countries.Research square · 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
- Prediction of genetic relatedness ofAntimicrobial agents and chemotherapy · 2026Article
- Transmission Dynamics of Torque Teno Sus Virus 1 (TTSuV1) Between Wild and Farmed Pigs: A Molecular Tool for Monitoring Cross-Population Spillover in Swine.Microorganisms · 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
- ViralBottleneck: an R package for estimating viral transmission bottlenecks from deep sequencing data using multiple methods.Virus evolution · 2025Article
- Inferring bacterial transmission dynamics using deep sequencing genomic surveillance data.Nature communications · 2023Article
- Inferring Viral Transmission Pathways from Within-Host Variation.medRxiv : the preprint server for health sciences · 2023Article
- P-DOR, an easy-to-use pipeline to reconstruct bacterial outbreaks using genomics.Bioinformatics (Oxford, England) · 2023Article
- Novel Network Method Major Minor Variation Clustering Enables Identification of Poliovirus Clusters with High-Resolution Linkages.Journal of computational biology : a journal of computational molecular cell biology · 2023Article
- Challenges in Harnessing Shared Within-Host Severe Acute Respiratory Syndrome Coronavirus 2 Variation for Transmission Inference.Open forum infectious diseases · 2023Article
- Patterns of within-host spread ofbioRxiv : the preprint server for biology · 2023Article
- Diagnosis of helminths depends on worm fecundity and the distribution of parasites within hosts.Proceedings. Biological sciences · 2023Article
- Patterns of within-host spread ofFrontiers in microbiology · 2023Article
- SARS-CoV-2 Genomic Diversity in Households Highlights the Challenges of Sequence-Based Transmission Inference.mSphere · 2022Article
1 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
3 authors.
Funding
Abstract
Sequencing pathogen samples during a communicable disease outbreak is becoming an increasingly common procedure in epidemiologic investigations. Identifying who infected whom sheds considerable light on transmission patterns, high-risk settings and subpopulations, and the effectiveness of infection control. Genomic data shed new light on transmission dynamics and can be used to identify clusters of individuals likely to be linked by direct transmission. However, identification of individual routes of infection via single genome samples typically remains uncertain. We investigated the potential of deep sequence data to provide greater resolution on transmission routes, via the identification of shared genomic variants. We assessed several easily implemented methods to identify transmission routes using both shared variants and genetic distance, demonstrating that shared variants can provide considerable additional information in most scenarios. While shared-variant approaches identify relatively few links in the presence of a small transmission bottleneck, these links are highly accurate. Furthermore, we propose a hybrid approach that also incorporates phylogenetic distance to provide greater resolution. We applied our methods to data collected during the 2014 Ebola outbreak, identifying several likely routes of transmission. Our study highlights the power of data from deep sequencing of pathogens as a component of outbreak investigation and epidemiologic analyses.
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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.