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The Biosurveillance Analytics Resource Directory (BARD): Facilitating the Use of Epidemiological Models for Infectious Disease Surveillance

Margevicius, Kristen J.; Generous, Nicholas; Abeyta, Esteban; Althouse, Ben; Burkom, Howard; Castro, Lauren; Daughton, Ashlynn; Del Valle, Sara Y.; Fairchild, Geoffrey; Hyman, James M.; Kiang, Richard; Morse, Andrew P.; Pancerella, Carmen M.; Pullum, Laura; Ramanathan, Arvind; Schlegelmilch, Jeffrey; Scott, Aaron; Taylor-McCabe, Kirsten J.; Vespignani, Alessandro; Deshpande, Alina

Epidemiological modeling for infectious disease is important for disease management and its routine implementation needs to be facilitated through better description of models in an operational context. A standardized model characterization process that allows selection or making manual comparisons of available models and their results is currently lacking. A key need is a universal framework to facilitate model description and understanding of its features. Los Alamos National Laboratory (LANL) has developed a comprehensive framework that can be used to characterize an infectious disease model in an operational context. The framework was developed through a consensus among a panel of subject matter experts. In this paper, we describe the framework, its application to model characterization, and the development of the Biosurveillance Analytics Resource Directory (BARD; http://brd.bsvgateway.org/brd/), to facilitate the rapid selection of operational models for specific infectious/communicable diseases. We offer this framework and associated database to stakeholders of the infectious disease modeling field as a tool for standardizing model description and facilitating the use of epidemiological models.

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Academic Units
Earth Institute
Publisher
Public Library of Science
Published Here
March 14, 2016