2.3 Network characterisation
We created a contact network where premises (farms, traders,
industrials, and markets) became the nodes and movements as their edges,
excluding movements to abattoirs as they are dead-ends for disease
transmission (Guinat et al., 2016). The network was represented by its
adjacency matrix, where the number of neighbours of a node (degree), and
its value was calculated directly from the adjacency matrix (A), where
Aij = 1 if there was a connection between nodes i
and j; otherwise, Aij = 0 (Newman, 2010). Swine
movements were represented as a directed network (networks in which the
direction of movement was taken into account).
Annual and monthly networks of premises were created and computed the
following metrics: betweenness, closeness, clustering coefficient,
degree, density, diameter, average shortest path, and giant weakly and
strongly connected components (Table 1). Then, we analysed seasonal
activity in network metrics and features such as shortest path length
and small-world characteristics (highly clustered networks) (Strogatz,
2001) (James et al., 2009) that may facilitate rapid disease
transmission.
Table 1. Network terminology used to characterise the Ecuadorian pig
movement network.