Exploiting textual source information for epidemiosurveillance

In recent years as a complement to the traditional surveillance reporting systems there is a great interest in developing methodologies for early detection of potential health threats from unstructured text present on the Internet. In this context, we examined the relevance of the combination of expert knowledge and automatic term extraction in the creation of appropriate Internet search queries for the acquisition of disease outbreak news. We propose a measure that is the number of relevant disease outbreak news detected in function of the terms automatically extracted from a set of example Google and PubMED corpora. Due to the recent emergence we have used the African swine fever as a disease example. (Résumé d'auteur