Article history: Received: 22-05-2017, Accepted: 24-06-2017, Published online: 18-07-2017
Corresponding author: Osvaldo Fonseca
E-mail: firstname.lastname@example.orgCitation: Fonseca O, Santoro KR, Alfonso P, Ayala J, Abeledo MA, Fernandez O, Centelles Y, Montano DN, Percedo MI. Association between the swine production areas and the human population in Pinar del Rio province, Cuba. Int J One Health 2017;3:36-41.
Aim: The aim of this study was to demonstrate the association between high human population density and high pig production in the province of Pinar del Rio, Cuba.
Materials and Methods: Records on pig movements at the district level in Pinar del Rio province from July 2010 to December 2012 were used in the study. A network analysis was carried out considering districts, as nodes, and movements of pigs between them represented the edges. The in-degree parameter was calculated using R 3.1.3 software. Graphical representation of the network was done with Gephi 0.8.2, and ArcGIS 10.2. was used for the spatial analysis to detect clusters by the Getis-Ord Gi* method and visualize maps as well.
Results: Significant spatial clusters of high values (hot spots) and low values (cold spots) of in-degree were identified. A cluster of high values was located in the central area of the province, and a cluster of low values involving municipalities of the Western zone was detected. Logistic regression demonstrated that a higher human population density per district was associated (odds ratio=16.020, 95% confidence interval: 1.692-151.682, p=0.016) with areas of high pork production.
Conclusion: Hot spot of swine production in Pinar del Rio is associated with human densely populated districts, which may suppose a risk of spillover of pathogens able to infect animals and humans. These results can be considered in strategy planning in terms of pork production increases and improvements of sanitary, commercial, and economic policies by decision-makers.
Keywords: cluster, Getis-Ord, logistic regression, network analysis, swine.
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