Social Network Analysis of Pig Movements and Spatial Characterization of Pig Farms in Mato Grosso, Brazil.

Abstract

Event Abstract Back to Event Social Network Analysis of Pig Movements and Spatial Characterization of Pig Farms in Mato Grosso, Brazil. Daniella D. Schettino1, 2*, Kimberly VanderWaal2 and Andres M. Perez2 1 Instituto de Defesa Agropecuária de Mato Grosso (INDEA MT), Brazil 2 University of Minnesota Twin Cities, United States Social network analysis (SNA) is an important tool for understanding the pattern of animal trade and elucidate how a disease may spread between farms, helping the design and implementation of surveillance actions. Brazil is the 4th largest pig producer in the World, and the State of Mato Grosso (MT) holds the 5th largest national pig herd, with 8.7% of the country’s pig population. However, there is a lack of information about the structure of the pig trade network in MT. The objective of this study was to build the between-farm pig movements network in MT, including within- and between-state movements. Data collected in 2018 were used to characterize the pig farms. The data of pig movements in 2018 was collected from the computerized system of the Official Veterinary Service of MT, all analyses for the network were conducted in R version 3.5.2, using the igraph and EpiContactTrace packages, and the spatio-temporal analysis of results was conducted using Arc Gis version 10.5.1. Here we show that MT pig’s network was clustered, not so dense, but some connections were very well established between specific farms, as well as many existing communities. There was a high heterogeneity regarding herd size between farms. Commercial pig farms were significantly clustered (P-value <0.05) according to Moran’s I statistic test results, with I = 0.049548, Z-score = 7.416751. The cluster was located in the center-north part of MT, which has the 66% of pigs and most of these animals are in commercial farms. Assessing the network of pig movements in MT is important because results would help informing decisions for disease surveillance and for health control measures, where at-risk farms may be targeted, saving financial and human resources, bringing efficiency and objectivity to Official Veterinary Service. Acknowledgements We would like to thank INDEA, the Official Veterinary Service of Mato Grosso, Brazil, for sharing data. Keywords: Social network, Pig movements, spatial distribution, Mato Grosso, Brazil Conference: GeoVet 2019. Novel spatio-temporal approaches in the era of Big Data, Davis, United States, 8 Oct - 10 Oct, 2019. Presentation Type: Student oral presentation Topic: Spatial-explicit or spatio-temporal network analysis Citation: Schettino DD, VanderWaal K and Perez AM (2019). Social Network Analysis of Pig Movements and Spatial Characterization of Pig Farms in Mato Grosso, Brazil.. Front. Vet. Sci. Conference Abstract: GeoVet 2019. Novel spatio-temporal approaches in the era of Big Data. doi: 10.3389/conf.fvets.2019.05.00061 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 31 May 2019; Published Online: 27 Sep 2019. * Correspondence: DVM. Daniella D Schettino, Instituto de Defesa Agropecuária de Mato Grosso (INDEA MT), Cuiaba, Brazil, donas001@umn.edu Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Daniella D Schettino Kimberly VanderWaal Andres M Perez Google Daniella D Schettino Kimberly VanderWaal Andres M Perez Google Scholar Daniella D Schettino Kimberly VanderWaal Andres M Perez PubMed Daniella D Schettino Kimberly VanderWaal Andres M Perez Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.