ArticleScientific reports2017
Vulnerability of the British swine industry to classical swine fever.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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
9 citing papers in PubMed, 15 citations in OpenAlex.
- Active Participatory Surveillance for Early Detection of Notifiable Pathogens: A Case Study of the U.S. Swine Industry.Viruses · 2026Article
- iPAR: A framework for modelling and inferring information about disease spread when the populations at risk are unknown.PLoS computational biology · 2025Article
- Label-Free Detection of African Swine Fever and Classical Swine Fever in the Point-of-Care Setting Using Photonic Integrated Circuits Integrated in a Microfluidic Device.Pathogens (Basel, Switzerland) · 2024Article
- Spatiotemporal analysis of reported classical swine fever outbreaks in China (2005-2018) and the influence of weather.Transboundary and emerging diseases · 2022Article
- Bayesian nonparametric inference for heterogeneously mixing infectious disease models.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- High Prevalence and Factors Associated With the Distribution of the IntegronFrontiers in veterinary science · 2021Article
- Spatial super-spreaders and super-susceptibles in human movement networks.Scientific reports · 2020Article
- Inferring within-herd transmission parameters for African swine fever virus using mortality data from outbreaks in the Russian Federation.Transboundary and emerging diseases · 2018Article
- A geo-computational algorithm for exploring the structure of diffusion progression in time and space.Scientific reports · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 4 institutions in 1 country.
Funding
Abstract
Classical swine fever (CSF) is a notifiable, highly contagious viral disease of swine which results in severe welfare and economic consequences in affected countries. To improve preparedness, it is critical to have some understanding of how CSF would spread should it be introduced. Based on the data recorded during the 2000 epidemic of CSF in Great Britain (GB), a spatially explicit, premises-based model was developed to explore the risk of CSF spread in GB. We found that large outbreaks of CSF would be rare and generated from a limited number of areas in GB. Despite the consistently low vulnerability of the British swine industry to large CSF outbreaks, we identified concerns with respect to the role played by the non-commercial sector of the industry. The model further revealed how various epidemiological features may influence the spread of CSF in GB, highlighting the importance of between-farm biosecurity in preventing widespread dissemination of the virus. Knowledge of factors affecting the risk of spread are key components for surveillance planning and resource allocation, and this work provides a valuable stepping stone in guiding policy on CSF surveillance and control in GB.
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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.