Feasibility of applying syndrome surveillance algorithms to animal health and production data to improve emerging animal disease surveillance

Abstract

This paper presents the results of a feasibility study on applying syndrome surveillance algorithms to animal health and production data to enhance early detection of emerging animal diseases. The case of the introduction of bluetongue virus serotype 8 in Northern Europe in 2006 was investigated while looking at historical mortality data that collected on a daily bases by the rendering plant. Several candidate algorithms were identified from literature and applied to the data. This study shows that it is technically feasible to apply existing syndrome surveillance algorithms to animal health and production data. The application of syndrome surveillance methodology on animal disease and production data needs further investigation to clearly assess their sensitivity and specificity.