Standardising Syndromic Classification in Animal Health Data

Fernanda C. Dórea, Céline Dupuy, Flavie Vial, Crawford Revie, Ann Lindberg


Data sharing remains a barrier to joint surveillance and the establishment of contingency plans among countries and institutions. Summary statistics are hard to interpret and compare, and nomenclatures for animal disease classification are seldom used. SSynCAHD (Syndromic Classification in Animal Health Data) proposes to harmonise, through the development on an ontology, syndromic surveillance data use rather than data recording. This will be achieved by standardising classification into syndromes, based on records from different sources of animal health data which are (and will continue to be) recorded using an institution own vocabulary.

Full Text:



Online Journal of Public Health Informatics * ISSN 1947-2579 *