Healthcare-associated infections in veterinary hospitals are commonly attributed to Salmonella enterica, particularly in large animal facilities, and are characteristically associated with widespread environmental contamination. The objective of this study was to investigate factors influencing the likelihood of identifying environmental contamination of a veterinary hospital with S. enterica, while exploring different analytic methods to model complex factors that may influence this ecology. Environmental surveillance samples were collected in a large veterinary hospital as part of a long-term infection control programme. Data were collected retrospectively from the electronic medical records database. Many easily measured variables were complex in nature (i.e., they represented variance that is unmeasured or unidentified as a specific factor) necessitating the use of alternative analytic methods (variable cluster and principal components analyses) to provide perspective regarding the complex data structure and latent factors that may be contributing to this ecology. Subsequently, multivariable logistic regression was performed using generalised estimating equations. Results suggest the probability of detecting Salmonella in the environment increased as demand on personnel increased (e.g., in a busy hospital). Veterinary personnel need to remain vigilant in implementing practices that we believe empirically will mitigate risk for widespread environmental contamination and sustained transmission among patients (i.e., rigorous hygiene for personnel and the environment).
Keywords: Infectious disease control; Salmonella; veterinary epidemiology.