Social network analysis of Equidae movements and its application to risk-based surveillance and to control of spread of potential Equidae diseases.

Movements of animals and animal products are one of the most important ways of disease introduction and spread between regions and countries. Maybe one of the most complex animal species in terms of diversity of uses, nature and extent of movements are equidae, for which animal movement records are usually not available. The study presented here is the first characterization of a complete and reliable network of equidae movements in Castile and Leon, which is one of the most important equidae production regions of Spain. Social network analysis and space-time cluster analysis were used to describe the contact patterns of the equidae network and to identify the most important premises, areas and time periods for potential disease introduction or spread into the region. The studied network was complex, with very heterogeneous types of premises and diverse nature and extent of the movements compared with other livestock species, which have important implications for prevention and control of equidae diseases. Centrality measures revealed that production and reproduction farms and centres of livestock competition were the most important type of premises in the studied network. Cluster analyses allowed to identify seventeen significant spatio-temporal clusters of premises at high risk of dispatching or receiving equidae, which formed four interconnected compartments. These clusters were mainly located in the north-west region and in the second part of the year. The results of this study may be useful to design risk-based surveillance and control programmes of equidae diseases and increase the speed of detection and control of potential secondary outbreaks in future epidemics. Consequently, these results will help to minimize the great economic and sanitary impact of equidae diseases. The analytical approach used here may be easily extended to characterize the equidae movement patterns in other countries and regions of the world.

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