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

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