Data modeling for detection of epidemic outbreak

Holger M. Jaenisch; James W. Handley; Kristina L. Jaenisch; Michael S. Conn; Jeffrey P. Faucheux

doi:10.1117/12.603374

20 May 2005 Data modeling for detection of epidemic outbreak

Holger M. Jaenisch, James W. Handley, Kristina L. Jaenisch, Michael S. Conn, Jeffrey P. Faucheux

Proceedings Volume 5778, Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense IV; (2005) https://doi.org/10.1117/12.603374
Event: Defense and Security, 2005, Orlando, Florida, United States

Abstract

Data Modeling is successfully applied to outbreak detection using epidemicological time series data. With proper selection of features, same day detection was demonstrated. Predictive Data Models are derived from the features in the form of integro-differential equations or their solution. These models are used as real-time change detectors. Data Modeling enables change detection using only nominal (no-outbreak) examples for training. Modeling naturally occurring dynamics due to assignable causes such as flu season enables distinction to be made of chemical and biological (chem-bio) causes.

Citation Download Citation

Holger M. Jaenisch, James W. Handley, Kristina L. Jaenisch, Michael S. Conn, and Jeffrey P. Faucheux "Data modeling for detection of epidemic outbreak", Proc. SPIE 5778, Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense IV, (20 May 2005); https://doi.org/10.1117/12.603374

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