Epidemiologic Factors Supporting Triage of Infected Dog Patients Admitted to a Veterinary Hospital Biological Isolation and Containment Unit

SIMPLE SUMMARY: An epidemiologic control of infectious diseases through the creation of infectious disease surveillance systems can be achieved with routine collection and analysis of clinical data. The Biological Isolation and Containment Unit of the teaching hospital from the Faculty of Veterinary Medicine, University of Lisbon is a multispecies facility for the hospitalization of pets with confirmed or suspected infectious diseases and has a database for the routine collection of these patients’ data. With this study, we intend to contribute to optimizing the design of infectious disease control programs and support early triage of these patients through the identification and characterization of the main dog infectious diseases registered over a 7-year period and the identification of potential risk factors for those conditions. The most frequent diagnoses were parvovirosis, leptospirosis, multidrug-resistant (MDR) bacterial infections, and distemper. Some potential risk factors have been identified, with emphasis on age < 2 years old (p < 0.001), incomplete vaccination for parvovirosis (p < 0.001), age ≥ 10 years old (p < 0.001), and presence of a concomitant disorder for MDR-infected cases (p = 0.03). Our results, by improving the knowledge about epidemiology and clinical presentation of these diseases, show the value of the collection, analysis, and sharing of clinical data and contribute for the creation of infectious cases triage tools as algorithms. ABSTRACT: The teaching hospital of the Faculty of Veterinary Medicine at the University of Lisbon hosts a Biological Isolation and Containment Unit (BICU) for the hospitalization of both confirmed and suspected animals of an infectious disease. This study targets the BICU dog population to identify and characterize the most frequent infectious diseases recorded in a 7-year period. Several epidemiologic factors were analyzed for their significance to triage infected cases. During the study period, 534 dogs were admitted, of which 263 (49.3%) had a confirmed infectious disease diagnosis: parvovirosis (49.4%; n = 130); leptospirosis (21.7%; n = 57); multidrug-resistant (MDR) bacterial infection; (10.6%; n = 28), and canine distemper (9.9%; n = 26). Several potential risk factors for these diseases were identified: age under 2 years old (p < 0.001), incomplete vaccination for parvovirosis (p < 0.001), age ≥ 10 years old (p < 0.001), and the presence of concomitant disorders for MDR-infected cases (p = 0.03). Logistic regression models were constructed to classify cases and controls. The sensitivity and specificity estimates were very high (>0.83) for parvovirosis, MDR, and distemper infections. A lower sensitivity (0.77) was obtained for identifying cases with leptospirosis. In conclusion, infectious diseases are frequent, hence, it is essential to decrease their occurrence through effective preventive measures such as vaccination. The constructed logistic models can also help in triaging admitted dogs with a potential infectious disease.