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
PLoS ONE
11(1): e0146600 (2016)
January 28, 2016

Abstract

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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