RESUMO
Amid the surge in data volume generated across various fields of knowledge, there is an increasing necessity for advanced analytical methodologies to effectively process and utilize this information. Particularly in the field of animal health, this approach is pivotal for enhancing disease understanding, surveillance, and management. The main objective of the study was to conduct a comprehensive livestock and environmental characterization of Colombian municipalities and examine their relationship with the distribution of vesicular stomatitis (VS). Utilizing satellite imagery to delineate climatic and land use profiles, along with data from the Colombian Agricultural Institute (ICA) concerning animal populations and their movements, the research employed Principal Component Analysis (PCA) to explore the correlation between environmental and livestock-related variables. Additionally, municipalities were grouped through a Hierarchical Clustering process. The assessment of risk associated with VS was carried out using a Generalized Linear Model. This process resulted in the formation of four distinct clusters: three primarily characterized by climatic attributes and one predominantly defined by livestock characteristics. Cluster 1, identified as "Andino" due to its climatic and environmental features, exhibited the highest odds ratio for VS occurrence. The adopted methodology not only provides a deeper understanding of the local population and its context, but also offers valuable insights for enhancing disease surveillance and control programs.
