Abstract

abstract: “Glanders is a highly infectious zoonotic disease caused by Burkholderia mallei. The transmission occurs mainly by direct contact, and horses are the natural reservoir. Identification of infection sources within horse populations and animal movements is critical to enhance disease control. Here, we analysed the dynamics of horse movements from 2014 to 2016 using network analysis in order to understand the flow of animals in two hierarchical levels: municipalities and farms. Our approach captured and established a direct relationship between movement of infected equines and predicted B. mallei outbreaks. The model revealed that parameters in-degree and closeness centrality out were positively associated with B. mallei. We also detected 10 communities with high commerce among municipalities. The role of each municipality within the network was detailed, showing significant changes over the course of 3 years. The results suggested the necessity to focus on structural changes of the networks over time to better control glanders disease.”