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

Abstract

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 (2002-4) and livestock in Great Britain (2003-4). 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.