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

PLoS One. 2016 Jan 28;11(1):e0146600. doi: 10.1371/journal.pone.0146600. eCollection 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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Communicable Disease Control
  • Communicable Diseases / epidemiology*
  • Epidemiological Monitoring*
  • Humans
  • Models, Statistical

Grants and funding

This project was funded by the Defense Threat Reductions Agency – Joint Science and Technology Office (Grant # CB10007, DTRA10027-10845).