PLoS ONE (Jan 2016)

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

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

DOI
https://doi.org/10.1371/journal.pone.0146600
Journal volume & issue
Vol. 11, no. 1
p. e0146600

Abstract

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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.