Epidemiology and antimicrobial resistance of Staphylococcus spp. Isolated from clinical canine cases presented at Onderstepoort Veterinary Hospital

Abstract

Canine Staphylococcus spp. have been isolated from several clinical conditions including pyoderma, otitis, wound and post-surgical infections. Studies have shown that transmission from dogs to humans occurs, and infected dogs play an important role in the epidemiology of human infections. Understanding the epidemiology of these infections and their antimicrobial resistance profiles is important in guiding control strategies. Therefore, the objective of this study was to investigate the epidemiology and antimicrobial resistance of Staphylococcus spp. isolated from canine clinical cases presented at the Onderstepoort veterinary hospital in South Africa between 2007 and 2012. Records of 1,497 clinical canine samples submitted to the bacteriology laboratory at the veterinary academic hospital between 2007 and 2012 were included in this study. Crude and factor-specific proportions of Staphylococcus spp. infections and antimicrobial resistance and their 95% confidence intervals were estimated. Associations between proportions of Staphylococcus spp. and a number of suspected predictors were assessed using Chi-square or Fisher’s exact tests as appropriate. Cochran–Armitage trend tests were used to assess temporal trends in the proportion of resistant isolates to each antimicrobial agent. Multinomial logistic models were used to investigate and identify predictors of the polytomous Staphylococcus spp. infections variable categorized as S. pseudintermedius, S. aureus and Staphylococcus negative. However, the predictors of antimicrobial resistance (AMR) and multidrug resistance (MDR) were assessed using ordinary logistic models. In this study, AMR was defined as resistance to at least one class of antimicrobial agent while MDR was defined as resistance to at least three classes of antimicrobial agents. Spatial Empirical Bayesian (SEB) smoothing was used to investigate spatial patterns of Staphylococcus spp. infections, AMR and MDR, while spatial scan statistics were used to identify their geographic hotspots. Twenty-seven percent of the samples were positive for Staphylococcus spp. There was a significant (p=0.0027) increasing temporal trend in the risk of S. pseudintermedius. Dogs ≤8 years of age compared to dogs >8 years old were significantly more likely to test positive for S. aureus or S. pseudintermedius. Ear canal and skin specimens compared to other specimens were more likely to test positive for S. pseudintermedius and S. aureus than test negative. The overall level of isolates that were AMR and MDR was 80.5% and 28.7% respectively. There were significant increases in the proportions of S. pseudintermedius isolates that were resistant to trimethoprim-sulphamethoxazole (p=0.004), clindamycin (p=0.022) and orbifloxacin (p=0.042) during the study period. A significant (p=0.0052) increase in the proportion of S. aureus isolates resistant to enrofloxacin was also observed. Both AMR and MDR isolates were more common among S. aureus (98.2%; 42.9%) than S. pseudintermedius (76.98; 25.9%) isolates. At the municipality spatial scale, hot-spots of AMR were identified in the City of Johannesburg, Emfuleni, Westonaria, Midvaal, Randfontein and Ekurhuleni local municipalities. Significant hot-spots of AMR were also identified at the town spatial scale in several towns including Walkerville and Boksburg. The observed increasing temporal trend in Staphylococcus spp. resistant to sulphonamides, lincosamides and fluoroquinolones is concerning and requires more detailed investigations using primary-base studies. Development of antimicrobial stewardship programs are warranted to address the increasing temporal trend in antimicrobial resistance. For instance, a requirement of an antibiogram before prescription of antimicrobials could be made mandatory to reduce treatment failures and slow down development of antimicrobial resistance. Finally, since Staphylococcus spp. infections and AMR tended to cluster in certain geographical areas, future studies need to investigate local socio-economic and environmental factors responsible for these hotspots to guide control efforts.