A review of the development of veterinary syndromic surveillance in 2011 indicated that the field was incipient, but fast growing. Many countries are starting to explore different sources of data for syndromic surveillance. Some of the data streams evaluated share similarities with those used in public health syndromic surveillance, such as clinical records and laboratory data. However, many unique animal data sources have arisen, such as abattoir and carcass collection data. We suggest there are three main challenges in the current development of animal syndromic surveillance: The lack of standards in disease classification; The development of statistical methods appropriate to deal with animal data; The creation of ready-to-use tools that employ these statistical methods.
Objective
To summarize the challenges in the development of syndromic surveillance tools in veterinary medicine, and describe the development of an R package to address some of the current gaps.