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First published June 28, 2007 as JAMIA PrePrint; doi:10.1197/jamia.M2342
Journal of the American Medical Informatics Association 2007;14(5):581-588
© 2007 American Medical Informatics Association


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Submitted on December 2, 2006
Accepted on June 11, 2007

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

Ben Y. Reis PhD1*, Chaim Kirby MA2, Lucy E. Hadden PhD2, Karen Olson PhD2, Andrew J. McMurry2, James B. Daniel : MPH3, and Kenneth D. Mandl MD, MPH1

Affiliation of the authors: 1 Children's Hospital Informatics Program at the Harvard-MIT Division of Health Science and Technology, Boston, MA; Harvard Medical School, Boston, MA ; 2 Children's Hospital Informatics Program at the Harvard-MIT Division of Health Science and Technology, Boston, MA ; 3 Massachusetts Department of Public Health, Boston, MA

* To whom correspondence should be addressed.

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.







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