ArticleScientific reports2019
Reconstructing foot-and-mouth disease outbreaks: a methods comparison of transmission network models.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
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Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A systematic review of epidemiological modelling in response to lumpy skin disease outbreaks.Frontiers in veterinary science · 2024Pooled it
- ScITree: Scalable Bayesian inference of transmission tree from epidemiological and genomic data.PLoS computational biology · 2025Article
- Spatiotemporal analysis of the re-emerging foot and mouth disease outbreak in Central Java, Indonesia.Open veterinary journal · 2025Article
- Spatial and temporal patterns of foot and mouth disease outbreaks (2011-2022) in cattle export-sourcing areas of southeastern Ethiopia.BMC veterinary research · 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
- Inferring Viral Transmission Pathways from Within-Host Variation.medRxiv : the preprint server for health sciences · 2023Article
- Unveiling invisible farm-to-farm PRRSV-2 transmission links and routes through transmission tree and network analysis.Evolutionary applications · 2023Article
- ComparingEpidemiology and infection · 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
- Development of a transboundary model of livestock disease in Europe.Transboundary and emerging diseases · 2022Article
- Increased transmission of SARS-CoV-2 in Denmark during UEFA European championships.Epidemiology and infection · 2022Article
- Methods Combining Genomic and Epidemiological Data in the Reconstruction of Transmission Trees: A Systematic Review.Pathogens (Basel, Switzerland) · 2022Review
- Inferring environmental transmission using phylodynamics: a case-study using simulated evolution of an enteric pathogen.Journal of the Royal Society, Interface · 2021Article
- VERSO: A comprehensive framework for the inference of robust phylogenies and the quantification of intra-host genomic diversity of viral samples.Patterns (New York, N.Y.) · 2021Article
- Integrating epidemiological and genetic data with different sampling intensities into a dynamic model of respiratory syncytial virus transmission.Scientific reports · 2021Article
- Identifying likely transmissions in Mycobacterium bovis infected populations of cattle and badgers using the Kolmogorov Forward Equations.Scientific reports · 2020Article
- Article
- Transmission network reconstruction for foot-and-mouth disease outbreaks incorporating farm-level covariates.PloS one · 2020Article
- Review
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A number of transmission network models are available that combine genomic and epidemiological data to reconstruct networks of who infected whom during infectious disease outbreaks. For such models to reliably inform decision-making they must be transparently validated, robust, and capable of producing accurate predictions within the short data collection and inference timeframes typical of outbreak responses. A lack of transparent multi-model comparisons reduces confidence in the accuracy of transmission network model outputs, negatively impacting on their more widespread use as decision-support tools. We undertook a formal comparison of the performance of nine published transmission network models based on a set of foot-and-mouth disease outbreaks simulated in a previously free country, with corresponding simulated phylogenies and genomic samples from animals on infected premises. Of the transmission network models tested, Lau's systematic Bayesian integration framework was found to be the most accurate for inferring the transmission network and timing of exposures, correctly identifying the source of 73% of the infected premises (with 91% accuracy for sources with model support >0.80). The Structured COalescent Transmission Tree Inference provided the most accurate inference of molecular clock rates. This validation study points to which models might be reliably used to reconstruct similar future outbreaks and how to interpret the outputs to inform control. Further research could involve extending the best-performing models to explicitly represent within-host diversity so they can handle next-generation sequencing data, incorporating additional animal and farm-level covariates and combining predictions using Ensemble methods and other approaches.
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