Outbreak of Severe Vomiting in Dogs Associated with a Canine Enteric Coronavirus, United Kingdom.

The lack of population health surveillance for companion animal populations leaves them vulnerable to the effects of novel diseases without means of early detection. We present evidence on the effectiveness of a system that enabled early detection and rapid response a canine gastroenteritis outbreak in the United Kingdom. In January 2020, prolific vomiting among dogs was sporadically reported in the United Kingdom. Electronic health records from a nationwide sentinel network of veterinary practices confirmed a significant increase in dogs with signs of gastroenteric disease. Male dogs and dogs living with other vomiting dogs were more likely to be affected. Diet and vaccination status were not associated with the disease; however, a canine enteric coronavirus was significantly associated with illness. The system we describe potentially fills a gap in surveillance in neglected populations and could provide a blueprint for other countries.

A real-time spatio-temporal syndromic surveillance system with application to small companion animals.

Lack of disease surveillance in small companion animals worldwide has contributed to a deficit in our ability to detect and respond to outbreaks. In this paper we describe the first real-time syndromic surveillance system that conducts integrated spatio-temporal analysis of data from a national network of veterinary premises for the early detection of disease outbreaks in small animals. We illustrate the system's performance using data relating to gastrointestinal disease in dogs and cats. The data consist of approximately one million electronic health records for dogs and cats, collected from 458 UK veterinary premises between March 2014 and 2016. For this illustration, the system predicts the relative reporting rate of gastrointestinal disease amongst all presentations, and updates its predictions as new data accrue. The system was able to detect simulated outbreaks of varying spatial geometry, extent and severity. The system is flexible: it generates outcomes that are easily interpretable; the user can set their own outbreak detection thresholds. The system provides the foundation for prompt detection and control of health threats in companion animals.