A comprehensive definition of a syndrome is composed of direct (911 calls, emergency departments, primary care providers, sensor, veterinary, agricultural and animal data) and indirect evidence (data from schools, drug stores, weather etc.). Syndromic surveillance will benefit from quickly integrating such data. There are three critical areas to address to build an effective syndromic surveillance system that is dynamic, organic and alert, capable of continuous growth, adaptability and vigilance: (1) timely collection of high quality data (2) timely integration and analysis of information (data in context) (3) applying innovative thinking and deriving deep insights from information analysis. In our view there is excessive emphasis on algorithms and applications to work on the collected data and insufficient emphasis on solving the integration challenges. Therefore, this paper is focused on information integration.

Objective

EII is the virtual consolidation of data from multiple systems into a unified, consistent and accurate representation. An analyst working in an EII environment can simultaneously view and analyze data from multiple data sources as if it were coming from one large local data warehouse. This paper posits that EII is a viable solution to implement a system covering large areas and disparate data sources for syndromic surveillance and discusses case studies from environments external to health.