Antimicrobial resistance of spp. isolated from canine specimens submitted to a veterinary diagnostic laboratory in South Africa.

BACKGROUND AND AIM

The rising burden of antimicrobial resistance (AMR) in veterinary medicine poses significant threats to animal and public health. In South Africa, inadequate surveillance exacerbates the challenge, particularly regarding spp. infections in companion animals. This study aimed to investigate the patterns and predictors of AMR and multidrug resistance (MDR) in isolated from dogs between 2012 and 2017.

MATERIALS AND METHODS

A retrospective cross-sectional study was conducted on 1627 isolates. Data regarding animal demographics and antimicrobial susceptibility were extracted, cleaned, and analyzed. Intermediate susceptibility results were classified as resistant. AMR was defined as resistance to at least one antimicrobial from one class and MDR as resistance to antimicrobials from three or more classes. Descriptive statistics, Cochran-Armitage trend analysis, and binary logistic regression models were employed to assess trends and predictors of AMR and MDR.

RESULTS

Overall, 61.2% of isolates exhibited resistance to at least one antimicrobial, and 39.0% were classified as MDR. The highest resistance was observed against penicillins (39.64%), followed by aminoglycosides (22.31%). Significant predictors of AMR included species, specimen type, and year of isolation, while MDR was significantly associated with specimen type and the age of the dog. Notably, showed a markedly higher likelihood of resistance (Adjusted Odds Ratio = 2.23, p < 0.001) compared to other species. Temporal trends indicated a decrease in AMR but an increase in MDR across the study period.

CONCLUSION

The high prevalence of AMR and MDR among canine isolates, particularly in skin infections and among younger dogs, underscores the urgent need to strengthen antimicrobial stewardship, enhance surveillance systems, and target interventions in veterinary practice. These findings serve as critical baseline data for future assessments of AMR trends and can be used to inform strategies to mitigate the dissemination of resistant pathogens between animals and humans.