ArticleScientific reports2014
Highly dynamic animal contact network and implications on disease transmission.
Article in Scientific reports, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
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Who cites it
30 citing papers in PubMed.
- Assessing the impact of mitigation measures on cattle movement patterns in Austria: bluetongue virus outbreaks as a case study.Frontiers in veterinary science · 2026Article
- Revealing the Hidden Social Structure of Pigs with AI-Assisted Automated Monitoring Data and Social Network Analysis.Animals : an open access journal from MDPI · 2025Article
- Dissecting transmission to understand parasite evolution.PLoS pathogens · 2025Review
- The effect of temporal resolution and contact duration on Real-Time location system-based contact networks for confined feedlot cattle.Preventive veterinary medicine · 2025Article
- The contribution of movement to social network structure and spreading dynamics under simple and complex transmission.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024Article
- Analysis of within-pen and between-pen fenceline temporal contact networks in confined feedlot cattle.Preventive veterinary medicine · 2024Article
- Technological Tools for the Early Detection of Bovine Respiratory Disease in Farms.Animals : an open access journal from MDPI · 2022Review
- Social behaviour and transmission of lameness in a flock of ewes and lambs.Frontiers in veterinary science · 2022Article
- Revealing mechanisms of infectious disease spread through empirical contact networks.PLoS computational biology · 2021Article
- An Information-Theoretic Approach to Detect the Associations of GPS-Tracked Heifers in Pasture.Sensors (Basel, Switzerland) · 2021Article
- Analyzing spatial mobility patterns with time-varying graphical lasso: Application to COVID-19 spread.Transactions in GIS : TG · 2021Article
- Combining epidemiological and ecological methods to quantify social effects onRoyal Society open science · 2021Article
- Spatial and temporal variation in proximity networks of commercial dairy cattle in Great Britain.Preventive veterinary medicine · 2021Article
- Analysis of dynamic contact network of patients with COVID-19 in Shaanxi Province of China.Scientific reports · 2021Article
- Social Network Predicts Exposure to Respiratory Infection in a Wild Chimpanzee Group.EcoHealth · 2020Article
- Dynamic Network of Interactions in the Wildlife-Livestock Interface in Mediterranean Spain: An Epidemiological Point of View.Pathogens (Basel, Switzerland) · 2020Article
- Antimicrobial Usage Factors and Resistance Profiles of Shiga Toxin-ProducingFrontiers in veterinary science · 2020Article
- Multilayer and Multiplex Networks: An Introduction to Their Use in Veterinary Epidemiology.Frontiers in veterinary science · 2020Review
- Transmission on empirical dynamic contact networks is influenced by data processing decisions.Epidemics · 2019Article
- Comparing the effects of non-homogenous mixing patterns on epidemiological outcomes in equine populations: A mathematical modelling study.Scientific reports · 2019Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Contact patterns among hosts are considered as one of the most critical factors contributing to unequal pathogen transmission. Consequently, networks have been widely applied in infectious disease modeling. However most studies assume static network structure due to lack of accurate observation and appropriate analytic tools. In this study we used high temporal and spatial resolution animal position data to construct a high-resolution contact network relevant to infectious disease transmission. The animal contact network aggregated at hourly level was highly variable and dynamic within and between days, for both network structure (network degree distribution) and individual rank of degree distribution in the network (degree order). We integrated network degree distribution and degree order heterogeneities with a commonly used contact-based, directly transmitted disease model to quantify the effect of these two sources of heterogeneity on the infectious disease dynamics. Four conditions were simulated based on the combination of these two heterogeneities. Simulation results indicated that disease dynamics and individual contribution to new infections varied substantially among these four conditions under both parameter settings. Changes in the contact network had a greater effect on disease dynamics for pathogens with smaller basic reproduction number (i.e. R0 < 2).
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