The correct management of diseases that are transmitted between wildlife and livestock requires a reliable estimate of the pathogen transmission rate. The calculation of this parameter is a challenge for epidemiologists, since transmission can occur through multiple pathways. The social network analysis is a widely used tool in epidemiology due to its capacity to identify individuals and communities with relevant roles for pathogen transmission. In the present work, we studied the dynamic network of interactions in a complex epidemiological scenario using information from different methodologies. In 2015, nine red deer, seven fallow deer, six wild boar and nine cattle were simultaneously monitored using GPS-GSM-Proximity collars in Doñana National Park. In addition, 16 proximity loggers were set in aggregation points. Using the social network analysis, we studied the dynamic network of interactions, including direct and indirect interactions, between individuals of different species and the potential transmission of pathogens within this network. The results show a high connection between species through indirect interactions, with a marked seasonality in the conformation of new interactions. Within the network, we differentiated four communities that included individuals of all the species. Regarding the transmission of pathogens, we observed the important role that fallow deer could be playing in the maintenance and transmission of pathogens to livestock. The present work shows the need to consider different types of methodologies in order to understand the complete functioning of the network of interactions at the wildlife/livestock interface. It also provides a methodological approach applicable to the management of shared diseases.
This is an open access article distributed under the Creative Commons Attribution License
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited