Burkholderia mallei : The dynamics of networks and disease transmission

Abstract

Glanders is a highly infectious zoonotic disease caused by Burkholderia mallei. The transmission of B. mallei occurs mainly by direct contact, and horses are the natural reservoir. Therefore, the 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. The municipality‐level network was used to investigate both community clustering and the balance between the municipality's trades and the farm‐level network associations between B. mallei outbreaks and the network centrality measurements, analysed by spatio‐temporal generalized additive model (GAM). Causal paths were established for the dispersion of B. mallei outbreaks through the network. Our approach captured and established a direct relationship between movement of infected equines and predicted B. mallei outbreaks. The GAM model revealed that the parameters in degree and closeness centrality out were positively associated with B. mallei. In addition, we also detected 10 communities with high commerce among municipalities. The role of each municipality within the network was detailed, and significant changes in the structures of the network were detected 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. The identification of farms with a putative risk of B. mallei infection using the horse movement network provided a direct opportunity for disease control through active surveillance, thus minimizing economic losses and risks for human cases of B. mallei.

First record of Burkholderia mallei Turkey 10 strain originating from glanderous horses from Brazil

“…The molecular methods have a potential for detecting B. mallei in animals with clinical signs of glanders, differing from Burkholderia pseudomallei infections, which determine similar clinical signs, whereas these Burkholderia species have similarity in their genomes greater than 90% [9,11,12,16,17,19,20]. Polymerase chain reaction (PCR) has been used in the clinical setting and in public health laboratories for the identification of B. mallei [8,14] and when associated with genetic sequencing, it is possible to reduce time and to improve the efficiency of the reagents used [1,3,5].…”

Development of an immunoblotting assay for serodiagnosis of Burkholderia mallei infection: the whole-cell proteome-based paradigm

“…Burkholderia mallei , a Gram-negative bacillus, is the causative agent of the febrile disease known as glanders, a pulmonary disease, and a facultative intracellular pathogen mostly of equidae (1, 2). Glanders is a highly contagious and zoonotic disease primarily affecting solipeds (i.e., horses, mules, and donkeys) (3).…”

Descriptive analysis of horse movement networks during the 2015 equestrian season in Ontario, Canada

“…Previous explorations of horse movements have demonstrated high variability among horse use, the types of facilities in which they live, frequency of their movements, and reasons for travel [13–21]. In some countries, horses are included in traceability requirements and therefore their characteristics, movements, and time-varying spatial locations can be described [15,16,22]. In countries without these requirements, description of horse populations have been gathered through questionnaire-based methods [13,14,17–19].…”

“…Significant outbreaks, such as the 2007 equine influenza outbreak in Australia [25–27] and the 2011 equine herpes virus outbreak in Utah [28], have highlighted the potential risk of disease spread as a result of horse movements between locations. In order to better estimate the potential impact of horse movements on disease spread, network analysis can be used to describe and characterise movement patterns [15,16,21,22]. In particular, knowledge of the nature and extent of horse movement patterns can indicate areas to target for disease prevention and control.…”