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Title: The Biosurveillance Analytics Resource Directory (BARD): Facilitating the use of epidemiological models for infectious disease surveillance

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.
Authors:
 [1] ;  [1] ;  [1] ;  [2] ;  [3] ;  [1] ;  [1] ;  [1] ;  [1] ;  [4] ;  [5] ;  [6] ;  [7] ;  [8] ;  [8] ;  [9] ;  [10] ;  [1] ;  [11] ;  [1] more »;  [12] « less
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  2. Santa Fe Inst. (SFI), Santa Fe, NM (United States)
  3. Johns Hopkins Univ., Laurel, MD (United States)
  4. Tulane Univ., New Orleans, LA (United States)
  5. National Aeronautics and Space Administration, Greenbelt, MD (United States)
  6. Univ. of Liverpool, Liverpool (United Kingdom); NIHR Health Protection Research Unit in Emerging and Zoonotic Infections, Liverpool (United Kingdom)
  7. Sandia National Lab. (SNL-CA), Livermore, CA (United States)
  8. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
  9. Columbia Univ., New York, NY (United States)
  10. USDA APHIS Veterinary Services, Science, Technology, and Analysis Services, Fort Collins, CO (United States)
  11. Northeastern Univ., Boston, MA (United States)
  12. Univ. of Erlangen-Nuremberg (Germany)
Publication Date:
OSTI Identifier:
1246952
Report Number(s):
LA-UR--14-28011
Journal ID: ISSN 1932-6203
Grant/Contract Number:
AC52-06NA25396
Type:
Accepted Manuscript
Journal Name:
PLoS ONE
Additional Journal Information:
Journal Volume: 11; Journal Issue: 1; Journal ID: ISSN 1932-6203
Publisher:
Public Library of Science
Research Org:
Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
Sponsoring Org:
USDOE
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES disease surveillance; epidemiological models; infectious disease modeling; infectious disease epidemiology; infectious disease control; infectious disease surveillance; spatial epidemiology; public and occupational health; decision making; malaria