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

K. J. Margevicius , N. Generous , E. Abeyta , B. Althouse , H. Burkom , L. Castro, A. Daughton, S. Y. Del Valle , G. Fairchild , J. M. Hyman, R. Kiang, A. P. Morse, C. M. Pancerella , L. Pullum , A. Ramanathan , J. Schlegelmilch, A. Scott, K. J Taylor-McCabe , A. Vespignani, A. Deshpande
11(1): e0146600 (2016)
January 28, 2016


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;, 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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