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AEGIS: A Robust and Scalable Real-time Public Health Surveillance System

^a Children’s Hospital Informatics Program at the Harvard-MIT Division of Health Sciences and Technology, Boston, MA
^b Harvard Medical School, Boston, MA
^c Department of Public Health, Boston, MA.

^_* Correspondence and reprints: Ben Y. Reis, PhD, Children’s Hospital Informatics Program at the Harvard-MIT Division of Health Sciences and Technology, 1 Autumn Street, Room 540.1, Boston, MA 02115 (Email: reis{at}mit.edu).

Received for publication: 12/02/06; accepted for publication: 06/11/07.

In this report, we describe the Automated Epidemiological Geotemporal Integrated Surveillance system (AEGIS), developed for real-time population health monitoring in the state of Massachusetts. AEGIS provides public health personnel with automated near-real-time situational awareness of utilization patterns at participating healthcare institutions, supporting surveillance of bioterrorism and naturally occurring outbreaks. As real-time public health surveillance systems become integrated into regional and national surveillance initiatives, the challenges of scalability, robustness, and data security become increasingly prominent. A modular and fault tolerant design helps AEGIS achieve scalability and robustness, while a distributed storage model with local autonomy helps to minimize risk of unauthorized disclosure. The report includes a description of the evolution of the design over time in response to the challenges of a regional and national integration environment.