Relationship of trade patterns of the Danish swine industry animal movements network to potential disease spread.

作者: Michel Bigras-Poulin , Kristen Barfod , Sten Mortensen , Matthias Greiner

DOI: 10.1016/J.PREVETMED.2007.02.004

关键词:

摘要: The movements of animals were analysed under the conceptual framework graph theory in mathematics. swine production related premises Denmark considered to constitute nodes a network and links animal movements. In this framework, each farm will have other which it be linked. A premise was (breeding, rearing or slaughter pig), an abattoir trade market. overall divided specific subnets that linked from moved. This approach allowed us visualise analyse three levels organization existed Danish registers: movement between two premises, networks, industry network. analyses done using these organisation. studied for period September 30, 2002 May 22, 2003. For daily pig median number pigs moved 130 with maximum 3306. abattoir, 24. largest percentage (82.5%); per 24 2018. whole Euclidean distances observed farm-to-farm 22 km 289 respectively, while farm-to-abattoir movements, they 36.2 285 km. one showed mainly away farms (3) breeder (26) (1535). assumption can randomly generated on basis density surrounding area any is not correct since patterns topology scale-free large degree heterogeneity. supported opinion disease spread software assuming homogeneity relationship should only used large-scale interpretation epidemic preparedness. approach, based theory, efficiently express more precisely, local scale (premise), heterogeneity by providing knowledge veterinarian charge controlling spread, also evaluated as potential tool manage epidemics during crisis. Geographic information systems could produce about transmission disease.

参考文章(28)
L. R. Foulds, Graph theory applications ,(1991)
Claude Berge, Graphes et hypergraphes ,(1970)
Gregory Z. Gutin, Jrgen Bang-Jensen, Digraphs: Theory, Algorithms and Applications ,(2002)
Béla Bollobás, Oliver M. Riordan, Mathematical results on scale‐free random graphs John Wiley & Sons, Ltd. pp. 1- 34 ,(2005) , 10.1002/3527602755.CH1
Handbook of Graphs and Networks: From the Genome to the Internet Handbook of Graphs and Networks: From the Genome to the Internet. pp. 417- ,(2003) , 10.1002/3527602755
Robert M. May, Roy M. Anderson, Infectious Diseases of Humans: Dynamics and Control ,(1991)
Wouter de Nooy, Andrej Mrvar, Vladimir Batagelj, Exploratory Social Network Analysis with Pajek ,(2005)
Cristopher Moore, M. E. J. Newman, Epidemics and percolation in small-world networks. Physical Review E. ,vol. 61, pp. 5678- 5682 ,(2000) , 10.1103/PHYSREVE.61.5678
Michalis Faloutsos, Petros Faloutsos, Christos Faloutsos, On power-law relationships of the Internet topology acm special interest group on data communication. ,vol. 29, pp. 251- 262 ,(1999) , 10.1145/316188.316229
Matt J Keeling, Mark EJ Woolhouse, Darren J Shaw, Louise Matthews, Margo Chase-Topping, Dan T Haydon, Stephen J Cornell, Jens Kappey, John Wilesmith, Bryan T Grenfell, Dynamics of the 2001 UK Foot and Mouth Epidemic: Stochastic Dispersal in a Heterogeneous Landscape Science. ,vol. 294, pp. 813- 817 ,(2001) , 10.1126/SCIENCE.1065973