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

ABSTRACT: 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 p

SUBMITTER: Hale AC 

PROVIDER: S-EPMC6882870 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature