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Network analysis of Danish cattle industry trade patterns as an evaluation of risk potential for disease spread

Elsevier BV
Publication Date
  • Networks
  • Cattle Movements
  • Risk Potential
  • Epidemiology
  • Graphs
  • Mathematics
  • Medicine


Trade patterns of animal movements in a specific industry are complex and difficult to study because there are many stakeholders, premises that are heterogeneously spread over the country, and a highly dynamic flow of animals exists among them. The Danish cattle industry was defined as a network of animal movements and graph theory was used to analyse the movements of cattle within this network. A premise was defined as a farm, an abattoir or a market. These premises constituted the network nodes in the graph and the animal movements between them were the links. In this framework, each premise had a sub-network of other premises to which it was linked by these animal movements. If no movement of animals were registered for a specific farm, then the sub-network for that premise consisted of only that premise. Otherwise, the sub-network linked the premise of interest to all premises from which and to which animals were moved, as long as there was a path linking animal movements to that specific premise. This approach allowed visualization and analyses of four levels of organization that existed in Denmark animal registers: (1) the animal that was moved, (2) the movements of all animals between two premises, (3) the specific premise network, and (4) the overall industry network. When contagious animals are moved from one premise to another, then to a third and so forth, these movements create a path for potential transfer of pathogens. The paths within which pathogens are present identify the transmission risks. A network of animal movements should provide information about pathogen transmission and disease spread. The network of the Danish cattle industry network was a directed scale-free graph (the direction of a movement was known), with an in-degree power of 2 an out-degree power of 1.46, consisted of 29,999 nodes, and 130,265 movements during a 6-month period. The in clustering coefficient was calculated to be 0.52 for the inward direction (movement to), while it was 0.02 for the outward direction (movement from). In Denmark, the cattle movements between premises demonstrated a large degree of heterogeneity. This heterogeneity in movements between farms should be used to evaluate the risk potential of disease transmission for each premise and must be considered when modelling disease spread between premises. The objective of this research was to describe the network of animal movements and not just the animal movements per se.

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