An Ontology-based Framework for Syndromic Surveillance Method Selection

Syndromic surveillance is the detection of a disease outbreak or bioterrorist attack. The process of surveillance includes various steps: data collection, data analysis and result interpretation. The goal of syndromic surveillance is to be able to make a rapid and accurate diagnostic of a potential outbreak. Method types range from traditional statistical approaches to algorithms which have been adapted from other fields. With a variety of options it can be difficult selecting the method best suited for analysis on a given set of data. This paper will focus on developing an ontology-based framework for selecting the best suited method(s) for data analysis, focusing on the end-users perspective.

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