Literature DB >> 12791773

Draft framework for evaluating syndromic surveillance systems.

Daniel M Sosin1.   

Abstract

Interest in public health surveillance to detect outbreaks from terrorism is driving the exploration of nontraditional data sources and development of new performance priorities for surveillance systems. A draft framework for evaluating syndromic surveillance systems will help researchers and public health practitioners working on nontraditional surveillance to review their work in a systematic way and communicate their efforts. The framework will also guide public health practitioners in their efforts to compare and contrast aspects of syndromic surveillance systems and decide whether and how to develop and maintain such systems. In addition, a common framework will allow the identification and prioritization of research and evaluation needs. The evaluation framework is comprised of five components: a thorough description of the system (e.g., purpose, stakeholders, how the system works); system performance experience (e.g., usefulness, acceptability to stakeholders, generalizability to other settings, operating stability, costs); capacity for outbreak detection (e.g., flexibility to adapt to changing risks and data inputs, sensitivity to detect outbreaks, predictive value of system alarms for true outbreaks, timeliness of detection); assessment of data quality (e.g., representativeness of the population covered by the system, completeness of data capture, reliability of data captured over time); and conclusions and recommendations. The draft framework is intended to evolve into guidance to support public health practice for terrorism preparedness and outbreak detection.

Mesh:

Year:  2003        PMID: 12791773      PMCID: PMC3456539          DOI: 10.1007/pl00022309

Source DB:  PubMed          Journal:  J Urban Health        ISSN: 1099-3460            Impact factor:   3.671


  3 in total

1.  Updated guidelines for evaluating public health surveillance systems: recommendations from the Guidelines Working Group.

Authors:  R R German; L M Lee; J M Horan; R L Milstein; C A Pertowski; M N Waller
Journal:  MMWR Recomm Rep       Date:  2001-07-27

2.  Surveillance of influenza-like illness in France. The example of the 1995/1996 epidemic.

Authors:  F Carrat; A Flahault; E Boussard; N Farran; L Dangoumau; A J Valleron
Journal:  J Epidemiol Community Health       Date:  1998-04       Impact factor: 3.710

3.  Poliomyelitis in Oman: acute flaccid paralysis surveillance leading to early detection and rapid response to a type 3 outbreak.

Authors:  S E Robertson; A J Suleiman; F R Mehta; S H al-Dhahry; M S el-Bualy
Journal:  Bull World Health Organ       Date:  1994       Impact factor: 9.408

  3 in total
  25 in total

1.  Evaluating real-time syndromic surveillance signals from ambulatory care data in four states.

Authors:  W Katherine Yih; Swati Deshpande; Candace Fuller; Dawn Heisey-Grove; John Hsu; Benjamin A Kruskal; Martin Kulldorff; Michael Leach; James Nordin; Jessie Patton-Levine; Ella Puga; Edward Sherwood; Irene Shui; Richard Platt
Journal:  Public Health Rep       Date:  2010 Jan-Feb       Impact factor: 2.792

2.  Timeliness of data sources used for influenza surveillance.

Authors:  Lynne Dailey; Rochelle E Watkins; Aileen J Plant
Journal:  J Am Med Inform Assoc       Date:  2007-06-28       Impact factor: 4.497

3.  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

4.  Risk Assessment During the Pan American and Parapan American Games, Toronto, 2015.

Authors:  Adam van Dijk; Emily Dawson; Kieran Michael Moore; Paul Belanger
Journal:  Public Health Rep       Date:  2017 Jul/Aug       Impact factor: 2.792

5.  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

6.  Clinical evaluation of the Emergency Medical Services (EMS) ambulance dispatch-based syndromic surveillance system, New York City.

Authors:  Jane Greenko; Farzad Mostashari; Annie Fine; Marci Layton
Journal:  J Urban Health       Date:  2003-06       Impact factor: 3.671

7.  Evaluating multi-purpose syndromic surveillance systems - a complex problem.

Authors:  Roger Morbey; Gillian Smith; Isabel Oliver; Obaghe Edeghere; Iain Lake; Richard Pebody; Dan Todkill; Noel McCarthy; Alex J Elliot
Journal:  Online J Public Health Inform       Date:  2021-12-24

8.  Implementing syndromic surveillance: a practical guide informed by the early experience.

Authors:  Kenneth D Mandl; J Marc Overhage; Michael M Wagner; William B Lober; Paola Sebastiani; Farzad Mostashari; Julie A Pavlin; Per H Gesteland; Tracee Treadwell; Eileen Koski; Lori Hutwagner; David L Buckeridge; Raymond D Aller; Shaun Grannis
Journal:  J Am Med Inform Assoc       Date:  2003-11-21       Impact factor: 4.497

Review 9.  Public health delivery in the information age: the role of informatics and technology.

Authors:  F Williams; A Oke; I Zachary
Journal:  Perspect Public Health       Date:  2019-02-13

10.  Unknown Disease Outbreaks Detection: A Pilot Study on Feature-Based Knowledge Representation and Reasoning Model.

Authors:  Rui Feng; Qiping Hu; Yingan Jiang
Journal:  Front Public Health       Date:  2021-05-13
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