ArticleJournal of the Royal Society, Interface2016
Market analyses of livestock trade networks to inform the prevention of joint economic and epidemiological risks.
Article in Journal of the Royal Society, Interface, 2016. 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
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
9 citing papers in PubMed.
- Current trends and challenges in the management of foot and mouth disease in Saudi Arabia: A review.Open veterinary journal · 2025Review
- Rewiring cattle movements to limit infection spread.Veterinary research · 2024Article
- Modelling transmission of Mycobacterium avium subspecies paratuberculosis between Irish dairy cattle herds.Veterinary research · 2022Article
- Research perspectives on animal health in the era of artificial intelligence.Veterinary research · 2021Review
- Generative models of network dynamics provide insight into the effects of trade on endemic livestock disease.Royal Society open science · 2021Article
- Use of Network Analysis and Spread Models to Target Control Actions for Bovine Tuberculosis in a State from Brazil.Microorganisms · 2021Article
- A Temporal Network Model for Livestock Trade Systems.Frontiers in veterinary science · 2021Article
- Predictive gravity models of livestock mobility in Mauritania: The effects of supply, demand and cultural factors.PloS one · 2018Article
- Spatial dynamics and control of a crop pathogen with mixed-mode transmission.PLoS computational biology · 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
7 authors.
Funding
Abstract
Conventional epidemiological studies of infections spreading through trade networks, e.g., via livestock movements, generally show that central large-size holdings (hubs) should be preferentially surveyed and controlled in order to reduce epidemic spread. However, epidemiological strategies alone may not be economically optimal when costs of control are factored in together with risks of market disruption from targeting core holdings in a supply chain. Using extensive data on animal movements in supply chains for cattle and swine in France, we introduce a method to identify effective strategies for preventing outbreaks with limited budgets while minimizing the risk of market disruptions. Our method involves the categorization of holdings based on position along the supply chain and degree of market share. Our analyses suggest that trade has a higher risk of propagating epidemics through cattle networks, which are dominated by exchanges involving wholesalers, than for swine. We assess the effectiveness of contrasting interventions from the perspectives of regulators and the market, using percolation analysis. We show that preferentially targeting minor, non-central agents can outperform targeting of hubs when the costs to stakeholders and the risks of market disturbance are considered. Our study highlights the importance of assessing joint economic-epidemiological risks in networks underlying pathogen propagation and trade.
Indexed as
Identifiers
What OpenQuestion holds
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.