Literature DB >> 15714629

BioSense--a national initiative for early detection and quantification of public health emergencies.

John W Loonsk1.   

Abstract

BioSense is a national initiative to enhance the nation's capability to rapidly detect, quantify, and localize public health emergencies, particularly biologic terrorism, by accessing and analyzing diagnostic and prediagnostic health data. BioSense will establish near real-time electronic transmission of data to local, state, and federal public health agencies from national, regional, and local health data sources (e.g., clinical laboratories, hospital systems, ambulatory care sites, health plans, U.S. Department of Defense and Veterans Administration medical treatment facilities, and pharmacy chains).

Mesh:

Year:  2004        PMID: 15714629

Source DB:  PubMed          Journal:  MMWR Suppl        ISSN: 2380-8942


  21 in total

1.  The Hub Population Health System: distributed ad hoc queries and alerts.

Authors:  Michael D Buck; Sheila Anane; John Taverna; Sam Amirfar; Remle Stubbs-Dame; Jesse Singer
Journal:  J Am Med Inform Assoc       Date:  2011-11-09       Impact factor: 4.497

2.  AEGIS: a robust and scalable real-time public health surveillance system.

Authors:  Ben Y Reis; Chaim Kirby; Lucy E Hadden; Karen Olson; Andrew J McMurry; James B Daniel; Kenneth D Mandl
Journal:  J Am Med Inform Assoc       Date:  2007-06-28       Impact factor: 4.497

3.  State health policy for terrorism preparedness.

Authors:  Leah Z Ziskin; Drew A Harris
Journal:  Am J Public Health       Date:  2007-07-31       Impact factor: 9.308

4.  Using encounters versus episodes in syndromic surveillance.

Authors:  I Jung; M Kulldorff; K P Kleinman; W K Yih; R Platt
Journal:  J Public Health (Oxf)       Date:  2009-05-13       Impact factor: 2.341

5.  Predicting outbreak detection in public health surveillance: quantitative analysis to enable evidence-based method selection.

Authors:  David L Buckeridge; Anna Okhmatovskaia; Samson Tu; Martin O'Connor; Csongor Nyulas; Mark A Musen
Journal:  AMIA Annu Symp Proc       Date:  2008-11-06

6.  Understanding detection performance in public health surveillance: modeling aberrancy-detection algorithms.

Authors:  David L Buckeridge; Anna Okhmatovskaia; Samson Tu; Martin O'Connor; Csongor Nyulas; Mark A Musen
Journal:  J Am Med Inform Assoc       Date:  2008-08-28       Impact factor: 4.497

7.  Using Syndromic Surveillance for All-Hazards Public Health Surveillance: Successes, Challenges, and the Future.

Authors:  Paula W Yoon; Amy I Ising; Julia E Gunn
Journal:  Public Health Rep       Date:  2017 Jul/Aug       Impact factor: 2.792

8.  The Evolution of BioSense: Lessons Learned and Future Directions.

Authors:  Deborah W Gould; David Walker; Paula W Yoon
Journal:  Public Health Rep       Date:  2017 Jul/Aug       Impact factor: 2.792

9.  The value of patient self-report for disease surveillance.

Authors:  Florence T Bourgeois; Stephen C Porter; Clarissa Valim; Tiffany Jackson; E Francis Cook; Kenneth D Mandl
Journal:  J Am Med Inform Assoc       Date:  2007-08-21       Impact factor: 4.497

10.  Code-based syndromic surveillance for influenzalike illness by International Classification of Diseases, Ninth Revision.

Authors:  Nicola Marsden-Haug; Virginia B Foster; Philip L Gould; Eugene Elbert; Hailiang Wang; Julie A Pavlin
Journal:  Emerg Infect Dis       Date:  2007-02       Impact factor: 6.883

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