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Updated: Feb 6, 2026

Cross-Modal Multivariate Pattern Analysis
Published on: November 9, 2011
Descriptive and multivariate analysis of the pig sector in Georgia and its implications for disease transmission
Daniel Beltrán-Alcrudo1, Esther A Kukielka2, Nienke de Groot3
1Regional Office for Europe and Central Asia, Food and Agriculture Organization, Budapest, Hungary.
Background:
Georgia is a country in the Caucasus region with a traditional backyard and highly variable pig farming system. The practices of such sectors have seldom been described and analyzed to better understand their implication in the introduction and spread of infectious pig diseases. Moreover, the Georgian pig sector was badly hit by an epidemic of African swine fever in 2007 that quickly spread throughout the region.
Materials And Methods:
We interviewed 487 pig farmers and 116 butchers using closed questionnaires on socioeconomic issues related to pig production, husbandry practices, biosecurity, marketing and movements, and disease awareness. Surveys were conducted in four regions of Georgia and descriptive statistics were computed. Factorial analyses of mixed data and hierarchical clustering on principal components were applied to study the relationship among collected variables for both farmers and butchers.
Results:
Results show that pig farming in Georgia is a non-professional sector, highly heterogeneous by region, characterized by smallholdings of few animals, with low inputs, outdated technologies, and poor biosecurity, which all translates into low outputs and productivity. The hierarchical clustering on principal components confirmed that there are five major production and husbandry strategies, which match the four regions where the study was conducted.
Conclusions:
Our results are the first step to quantify biosecurity gaps and risky behaviours, develop risk profiles, and identify critical control points across the market chain where to implement mitigation measures. This study provides the baseline information needed to design realistic and sustainable prevention, surveillance and control strategies.
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