ArticleScientific reports2016
Disease-emergence dynamics and control in a socially-structured wildlife species.
Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed.
- The influence of social and spatial processes on the epidemiology of environmentally transmitted pathogens in wildlife: implications for management.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024Article
- African swine fever at the wildlife-livestock interface: challenges for management and outbreak response within invasive wild pigs in the United States.Frontiers in veterinary science · 2024Review
- Social structure defines spatial transmission of African swine fever in wild boar.Journal of the Royal Society, Interface · 2021Article
- Ecological drivers of African swine fever virus persistence in wild boar populations: Insight for control.Ecology and evolution · 2020Article
- Individual-Level Antibody Dynamics Reveal Potential Drivers of Influenza A Seasonality in Wild Pig Populations.Integrative and comparative biology · 2019Article
- BOARD INVITED REVIEW: Prospects for improving management of animal disease introductions using disease-dynamic models.Journal of animal science · 2019Review
- Demographic stochasticity drives epidemiological patterns in wildlife with implications for diseases and population management.Scientific reports · 2018Article
- A Review of Classical Swine Fever Virus and Routes of Introduction into the United States and the Potential for Virus Establishment.Frontiers in veterinary science · 2018Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Once a pathogen is introduced in a population, key factors governing rate of spread include contact structure, supply of susceptible individuals and pathogen life-history. We examined the interplay of these factors on emergence dynamics and efficacy of disease prevention and response. We contrasted transmission dynamics of livestock viruses with different life-histories in hypothetical populations of feral swine with different contact structures (homogenous, metapopulation, spatial and network). Persistence probability was near 0 for the FMDV-like case under a wide range of parameter values and contact structures, while persistence was probable for the CSFV-like case. There were no sets of conditions where the FMDV-like pathogen persisted in every stochastic simulation. Even when population growth rates were up to 300% annually, the FMDV-like pathogen persisted in <25% of simulations regardless of transmission probabilities and contact structure. For networks and spatial contact structure, persistence probability of the FMDV-like pathogen was always <10%. Because of its low persistence probability, even very early response to the FMDV-like pathogen in feral swine was unwarranted while response to the CSFV-like pathogen was generally effective. When pre-emergence culling of feral swine caused population declines, it was effective at decreasing outbreak size of both diseases by ≥80%.
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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.