Literature DB >> 22320664

Assessing the continuum of event-based biosurveillance through an operational lens.

Courtney D Corley1, Mary J Lancaster, Robert T Brigantic, James S Chung, Ronald A Walters, Ray R Arthur, Cynthia J Bruckner-Lea, Augustin Calapristi, Glenn Dowling, David M Hartley, Shaun Kennedy, Amy Kircher, Sara Klucking, Eva K Lee, Taylor McKenzie, Noele P Nelson, Jennifer Olsen, Carmen Pancerella, Teresa N Quitugua, Jeremy Todd Reed, Carla S Thomas.   

Abstract

This research follows the Updated Guidelines for Evaluating Public Health Surveillance Systems, Recommendations from the Guidelines Working Group, published by the Centers for Disease Control and Prevention nearly a decade ago. Since then, models have been developed and complex systems have evolved with a breadth of disparate data to detect or forecast chemical, biological, and radiological events that have a significant impact on the One Health landscape. How the attributes identified in 2001 relate to the new range of event-based biosurveillance technologies is unclear. This article frames the continuum of event-based biosurveillance systems (that fuse media reports from the internet), models (ie, computational that forecast disease occurrence), and constructs (ie, descriptive analytical reports) through an operational lens (ie, aspects and attributes associated with operational considerations in the development, testing, and validation of the event-based biosurveillance methods and models and their use in an operational environment). A workshop was held in 2010 to scientifically identify, develop, and vet a set of attributes for event-based biosurveillance. Subject matter experts were invited from 7 federal government agencies and 6 different academic institutions pursuing research in biosurveillance event detection. We describe 8 attribute families for the characterization of event-based biosurveillance: event, readiness, operational aspects, geographic coverage, population coverage, input data, output, and cost. Ultimately, the analyses provide a framework from which the broad scope, complexity, and relevant issues germane to event-based biosurveillance useful in an operational environment can be characterized.

Entities:  

Mesh:

Year:  2012        PMID: 22320664     DOI: 10.1089/bsp.2011.0096

Source DB:  PubMed          Journal:  Biosecur Bioterror        ISSN: 1538-7135


  9 in total

1.  Using social media and internet data for public health surveillance: the importance of talking.

Authors:  David M Hartley
Journal:  Milbank Q       Date:  2014-03       Impact factor: 4.911

Review 2.  Surveillance systems evaluation: a systematic review of the existing approaches.

Authors:  Clementine Calba; Flavie L Goutard; Linda Hoinville; Pascal Hendrikx; Ann Lindberg; Claude Saegerman; Marisa Peyre
Journal:  BMC Public Health       Date:  2015-05-01       Impact factor: 3.295

3.  Advancing a framework to enable characterization and evaluation of data streams useful for biosurveillance.

Authors:  Kristen J Margevicius; Nicholas Generous; Kirsten J Taylor-McCabe; Mac Brown; W Brent Daniel; Lauren Castro; Andrea Hengartner; Alina Deshpande
Journal:  PLoS One       Date:  2014-01-02       Impact factor: 3.240

4.  Selecting essential information for biosurveillance--a multi-criteria decision analysis.

Authors:  Nicholas Generous; Kristen J Margevicius; Kirsten J Taylor-McCabe; Mac Brown; W Brent Daniel; Lauren Castro; Andrea Hengartner; Alina Deshpande
Journal:  PLoS One       Date:  2014-01-29       Impact factor: 3.240

Review 5.  A review of evaluations of electronic event-based biosurveillance systems.

Authors:  Kimberly N Gajewski; Amy E Peterson; Rohit A Chitale; Julie A Pavlin; Kevin L Russell; Jean-Paul Chretien
Journal:  PLoS One       Date:  2014-10-20       Impact factor: 3.240

6.  KIWI: A technology for public health event monitoring and early warning signal detection.

Authors:  Shamir N Mukhi
Journal:  Online J Public Health Inform       Date:  2016-12-28

Review 7.  Social media and internet-based data in global systems for public health surveillance: a systematic review.

Authors:  Edward Velasco; Tumacha Agheneza; Kerstin Denecke; Göran Kirchner; Tim Eckmanns
Journal:  Milbank Q       Date:  2014-03       Impact factor: 4.911

Review 8.  Disease prediction models and operational readiness.

Authors:  Courtney D Corley; Laura L Pullum; David M Hartley; Corey Benedum; Christine Noonan; Peter M Rabinowitz; Mary J Lancaster
Journal:  PLoS One       Date:  2014-03-19       Impact factor: 3.240

9.  Evaluation of the national tuberculosis surveillance and response systems, 2018 to 2019: National Tuberculosis, Leprosy and Buruli Ulcer Control Programme, Abuja, Nigeria.

Authors:  Ayi Vandi Kwaghe; Chukwuma David Umeokonkwo; Mabel Kamweli Aworh
Journal:  Pan Afr Med J       Date:  2020-02-24
  9 in total

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