Tools to study trends in community structure: application to fish and livestock trading networks.

Partitioning of contact networks into communities allows groupings of epidemiologically related nodes to be derived, that could inform the design of disease surveillance and control strategies, e.g. contact tracing or design of 'firebreaks' for disease spread. However, these are only of merit if they persist longer than the timescale of interventions. Here, we apply different methods to identify concordance between network partitions across time for two animal trading networks, those of salmon in Scotland (2002-2004) and livestock in Great Britain (2003-2004). Both trading networks are similar in that they moderately agree over time in terms of their community structures, but this concordance is higher--and therefore community structure is more consistent--when only the 'core' network of nodes involved in trading over the whole time series is considered. In neither case was higher agreement found between partitions close together in time. These measures differ in their absolute values unless appropriate standardisation is applied. Once standardised, the measures gave similar values for both network types.

Small- and large-scale network structure of live fish movements in Scotland.

Networks are increasingly being used as an epidemiological tool for studying the potential for disease transmission through animal movements in farming industries. We analysed the network of live fish movements for commercial salmonids in Scotland in 2003. This network was found to have a mixture of features both aiding and hindering disease transmission, hindered by being fragmented, with comparatively low mean number of connections (2.83), and low correlation between inward and outward connections (0.12), with moderate variance in these numbers (coefficients of dispersion of 0.99 and 3.12 for in and out, respectively); but aided by low levels of clustering (0.060) and some non-random mixing (coefficient of assortativity of 0.16). Estimated inter-site basic reproduction number R(0) did not exceed 2.4 at high transmission rate. The network was strongly organised into communities, resulting in a high modularity index (0.82). Arc (directed connection) removal indicated that effective surveillance of a small number of connections may facilitate a large reduction in the potential for disease spread within the industry. Useful criteria for identification of these important arcs included degree- and betweenness-based measures that could in future prove useful for prioritising surveillance.