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Application of network analysis parameters in risk-based surveillance - Examples based on cattle trade data and bovine infections in Sweden
Department of Disease Control and Epidemiology, National Veterinary Institute, Uppsala, Sweden / Department of Animal Environment and Health, Swedish University of Agricultural Sciences, Skara, Sweden.
Department of Disease Control and Epidemiology, National Veterinary Institute, Uppsala, Sweden / Department of Clinical Sciences, Swedish University of Agricultural Sciences, Uppsala, Sweden.
Department of Clinical Sciences, Swedish University of Agricultural Sciences, Uppsala, Sweden.
University of Skövde, School of Life Sciences. University of Skövde, The Systems Biology Research Centre. Division of Theoretical Biology, IFM Theory and Modelling, Linköping University, Linköping, Sweden.
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2012 (English)In: Preventive Veterinary Medicine, ISSN 0167-5877, E-ISSN 1873-1716, Vol. 105, no 3, 202-208 p.Article in journal (Refereed) Published
Abstract [en]

Financial resources may limit the number of samples that can be collected and analysed in disease surveillance programmes. When the aim of surveillance is disease detection and identification of case herds, a risk-based approach can increase the sensitivity of the surveillance system. In this paper, the association between two network analysis measures, i.e. ‘in-degree’ and ‘ingoing infection chain’, and signs of infection is investigated. It is shown that based on regression analysis of combined data from a recent cross-sectional study for endemic viral infections and network analysis of animal movements, a positive serological result for bovine coronavirus (BCV) and bovine respiratory syncytial virus (BRSV) is significantly associated with the purchase of animals. For BCV, this association was significant also when accounting for herd size and regional cattle density, but not for BRSV. Examples are given for different approaches to include cattle movement data in risk-based surveillance by selecting herds based on network analysis measures. Results show that compared to completely random sampling these approaches increase the number of detected positives, both for BCV and BRSV in our study population. It is concluded that network measures for the relevant time period based on updated databases of animal movements can provide a simple and straight forward tool for risk-based sampling.

Place, publisher, year, edition, pages
Elsevier, 2012. Vol. 105, no 3, 202-208 p.
Keyword [en]
In-degree, Ingoing infection chain, Bovine coronavirus, Bovine respiratory syncytial virus
National Category
Natural Sciences
Research subject
Natural sciences
Identifiers
URN: urn:nbn:se:his:diva-5921DOI: 10.1016/j.prevetmed.2011.12.011ISI: 000305860700006PubMedID: 22265643Scopus ID: 2-s2.0-84861950750OAI: oai:DiVA.org:his-5921DiVA: diva2:530757
Conference
First International Conference on Animal Health Surveillance (ICAHS), Lyon, France, May 17-20, 2011
Available from: 2012-06-04 Created: 2012-06-04 Last updated: 2015-12-29Bibliographically approved

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CiteExportLink to record
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Citation style
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