Skip to main content Accessibility help
×
Hostname: page-component-78c5997874-m6dg7 Total loading time: 0 Render date: 2024-11-10T08:05:26.294Z Has data issue: false hasContentIssue false

11 - Syndromic Surveillance

from PART II - OPERATIONAL ISSUES

Published online by Cambridge University Press:  05 August 2011

Kristi L. Koenig
Affiliation:
University of California, Irvine
Carl H. Schultz
Affiliation:
University of California, Irvine
Get access

Summary

OVERVIEW

Syndromic surveillance has been defined by the U.S. Centers for Disease Control and Prevention (CDC) as “the collection and analysis of health-related data that precede diagnoses or laboratory confirmation and signal with sufficient probability a case or an outbreak for further public health response.” Based on its original definition, the purpose of syndromic surveillance would be to prevent morbidity and mortality by early identification of case clusters in which mitigation would affect the outcome of the disease's natural course. This original definition was designed for early event detection and became prominent in the public domain after the September 11, 2001 terrorist attacks in the United States and the subsequent anthrax illnesses and deaths.

With a heightened sense of urgency related to the so-called “war on terror,” many systems were put into place within the United States for the protection of the public health. These included such diverse programs as vaccine initiatives (BioShield), static detectors located throughout large cities to identify specific organisms of interest in the air (BioWatch), and the beginning of a national syndromic surveillance system for early detection of outbreaks (BioSense). These three initiatives were designed for the following reasons, respectively: 1) prevention of disease if a terrorist attack occurred; 2) early identification of airborne pathogens during the asymptomatic phase of such disease; and 3) early identification of illness prior to definitive diagnosis that would be confirmed either by culture or laboratory tests.

Type
Chapter
Information
Koenig and Schultz's Disaster Medicine
Comprehensive Principles and Practices
, pp. 165 - 173
Publisher: Cambridge University Press
Print publication year: 2009

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

http://www.eurosurveillance.org/ViewArticle.aspx?ArticleId=667. Accessed November 29, 2008.
http://www.css.drdc-rddc.gc.ca/symposium/symposium/2008/06-0234TA-eng.asp. Accessed November 29, 2008.
http://www.chi.unsw.edu.au/CHIweb.nsf/pageprintfriendly/Syndromic%20Surveillance?opendocument. Accessed November 29, 2008.
http://www.invs.sante.fr/agenda/syndromic_surveillance_eu/information.htm. Accessed November 29, 2008.
http://www.eurosurveillance.org/ViewArticle.aspx?ArticleId=668. Accessed November 29, 2008.
http://www.ncbi.nlm.nih.gov/pubmed/16796513. Accessed November 29, 2008.
http://www.cdc.gov/mmwr/pdf/wk/mm54su01.pdf, pg 47. Accessed November 29, 2008.
http://www.biomedcentral.com/1471-2458/8/18. Accessed November 29, 2008.
Bravata, D, McDonald, K, Smith, W, et al. Systematic review: surveillance systems for early detection of bioterrorism-related diseases. Ann Intern Med. 2004;140(11):910–922.Google Scholar
Green, M, Kaufman, Z. Surveillance for early detection and monitoring of infectious disease outbreaks associated with bioterrorism. Isr Med Assoc J. 2002:4(7):503–506.Google Scholar
Irvin, C, Nouhan, P, Rice, K. Syndromic analysis of computerized emergency department patients' chief complaints: an opportunity for bioterrorism and influenza surveillance. Ann Emerg Med. 2003;41(4):447–452.Google Scholar
Begier, E, Sockwell, D, Branch, L, et al. The National Capitol Region's Emergency Department Syndromic Surveillance System: do chief complaint and discharge diagnosis yield different results? Emerg Infect Dis. 2003;9(3):393–396.Google Scholar
Platt, R, Bocchino, C, Caldwell, B, et al. Syndromic surveillance using minimum transfer of identifiable data: the example of the National Bioterrorism Syndromic Surveillance Demonstration Program. J Urban Health. 2003;80(2Suppl 1):i25–i31.Google Scholar
Lober, W, Trigg, L, Karras, B, et al. Syndromic surveillance using automated collection of computerized discharge diagnoses. J Urban Health. 2003;80(2 Suppl 1):i97–i106.Google Scholar
Buehler, J, Berkelman, R, Hartley, D, Peters, C. Syndromic surveillance and bioterrorism-related epidemics. Emerg Infect Dis. 2003;9(10):1197–1204.Google Scholar
,Centers for Disease Control and Prevention. What is syndromic surveillance? MMWR. 2004;53(Suppl):7–11.Google Scholar
,Centers for Disease Control and Prevention. New York City syndromic surveillance systems. MMWR. 2004;53(Suppl):25–27.Google Scholar
,Centers for Disease Control and Prevention. Progress in understanding and using over-the-counter pharmaceuticals for syndromic surveillance. MMWR. 2004;53(Suppl):117–122.Google Scholar
,Centers for Disease Control and Prevention. Use of Medicaid prescription data for syndromic surveillance – New York. MMWR. 2005;54(Suppl):31–4.Google Scholar
,Centers for Disease Control and Prevention. Poison control center-based syndromic surveillance for foodborne illness. MMWR. 2005;54(Suppl):35–40.Google Scholar
,Centers for Disease Control and Prevention. Monitoring over-the-counter medication sales for early detection of disease outbreaks – New York City. MMWR. 2005;54(Suppl):41–46.Google Scholar
,Centers for Disease Control and Prevention. Experimental surveillance using data on sales of over-the-counter medications – Japan, November 2003–April 2004. MMWR. 2005;54(Suppl):47–52.
,Centers for Disease Control and Prevention. Increased antiviral medication sales before the 2005–06 influenza season – New York City. MMWR. 2006;55(10):277–279.Google Scholar
Vergu, E, Grais, R, Sarter, H, et al. Medication sales and syndromic surveillance, France. Emerg Infect Dis. 2006;12(3):416–421.Google Scholar
Hope, K, Durrheim, DN, d'Espaignet, ET, Dalton, C. 2006. Syndromic surveillance: is it a useful tool for local outbreak detection? J Epidemiol Community Health. 60:374–375.Google Scholar
Chapman, W, Christensen, L, Wagner, M, et al. Classifying free-text triage chief complaints into syndromic categories with natural language processing. Artif Intell Med. 2005;33(1):1–10.Google Scholar
,Centers for Disease Control and Prevention. Taming variability in free text: application to health surveillance. MMWR. 2004;53(Suppl):95–100.Google Scholar
Lombardo, J, Burkom, H, Elbert, E, et al. A systems overview of the electronic surveillance system for the early notification of community-based epidemics (ESSENCE II). J Urban Health. 2003;80(2 Suppl 1):i32–i42.Google Scholar
,Centers for Disease Control and Prevention. ESSENCE II and the framework for evaluating syndromic surveillance systems. MMWR. 2004;53(Suppl):159–165.Google Scholar
Vourc'h, G, Bridges, V, Gibbens, J, et al. Detecting emerging diseases in farm animals through clinical observations. Emerg Infect Dis. 2006;12(2):204–210.Google Scholar
,Centers for Disease Control and Prevention. Information system architectures for syndromic surveillance. MMWR. 2004;53(Suppl):203–208.Google Scholar
Forslund, D, Joyce, E, Burr, T, et al. Setting standards for improved syndromic surveillance. IEEE Eng Med Biol Mag. 2004;23(1):65–70.Google Scholar
Mandl, K, Overhage, JM, Wagner, M, et al. Implementing syndromic surveillance: a practical guide informed by the early experience. J Am Med Inform Assoc. 2004;11(2):141–150.Google Scholar
Reis, B, Mandl, K. Time series modeling for syndromic surveillance. BMC Med Inform Decis Making. 2003;3:2.Google Scholar
Kleinman, K, Lazarus, R, Platt, R. A generalized linear mixed models approach for detecting incident clusters of disease in small areas, with an application to biological terrorism. Am J Epidemiol. 2004;159(3):217–224.Google Scholar
Reis, B, Mandl, K. Syndromic Surveillance: The effects of syndrome grouping on model accuracy and outbreak detection. Ann Emerg Med. 2004;44(3):235–241.Google Scholar
Feinberg, S, Shmueli, G. Statistical issues and challenges associated with rapid detection of bio-terrorist attacks. Statist Med. 2005;24:513–529.Google Scholar
Hutwagner, L, Thompson, W, Seeman, G, Treadwell, T. A simulation model for assessing aberration detection methods used in public health surveillance for systems with limited baselines. Statist Med. 2005;24:543–550.Google Scholar
,Centers for Disease Control and Prevention. Bivariate method for spatio-temporal syndromic surveillance. MMWR. 2004;53(Suppl);61–66.Google Scholar
,Centers for Disease Control and Prevention. Role of data aggregation in biosurveillance detection strategies with applications from ESSENCE. MMWR. 2004;53(Suppl):67–73.Google Scholar
,Centers for Disease Control and Prevention. Scan statistics for temporal surveillance for biologic terrorism. MMWR. 2004;53(Suppl):74–78.Google Scholar
,Centers for Disease Control and Prevention. Approaches to syndromic surveillance when data consist of small regional counts. MMWR. 2004;53(Suppl):79–85.Google Scholar
,Centers for Disease Control and Prevention. Measuring outbreak-detection performance by using controlled feature set simulations. MMWR. 2004;53(Suppl):130–136.Google Scholar
,Centers for Disease Control and Prevention. Benchmark data and power calculations for evaluating disease outbreak detection methods. MMWR. 2004;53(Suppl):144–151.Google Scholar
Kleinman, K, Abrams, A, Kulldorff, M, Platt, R. A model-adjusted space-time scan statistic with an application to syndromic surveillance. Epidemiol Infect. 2005;133(3):409–419.Google Scholar
,Centers for Disease Control and Prevention. Use of multiple data streams to conduct Bayesian biologic surveillance. MMWR. 2005;54(Suppl):63–69.Google Scholar
,Centers for Disease Control and Prevention. Deciphering data anomalies in BioSense. MMWR. 2005;54(Suppl):133–139.Google Scholar
Najmi, A-H, Magruder, S. An adaptive prediction and detection algorithm for multistream syndromic surveillance. BMC Med Inform Decis Making. 2005;5:33.Google Scholar
,Centers for Disease Control and Prevention. Syndromic surveillance for bioterrorism following the attacks on the World Trade Center – New York City, 2001. MMWR. 2002;51(SI):13–15.Google Scholar
Das, D, Weiss, D, Mostashari, F, et al. Enhanced drop-in syndromic surveillance in New York City following September 11, 2001. J Urban Health. 2003;80(2 Suppl 1):i76–i88.Google Scholar
Gesteland, P, Gardner, R, Tsui, F-C, et al. Automated syndromic surveillance for the 2002 Winter Olympics. J Am Med Inform Assoc. 2003;10(6):547–554.Google Scholar
,Centers for Disease Control and Prevention. Surveillance for early detection of disease outbreaks at an outdoor mass gathering – Virginia, 2005. MMWR. 2006;55(3):71–74.Google Scholar
Muscatello, D, Churches, T, Kaldor, J, et al. An automated, broad-based, near real-time public health surveillance system using presentations to hospital emergency departments in New South Wales, Australia. BMC Public Health. 2005;5:141.Google Scholar
Marx, M, Rodriguez, C, Greenko, J, et al. Diarrheal illness detected through syndromic surveillance after a massive power outage: New York City, August 2003. Am J Pub Health. 2006;96(3):547–553.Google Scholar
,Centers for Disease Control and Prevention. Syndromic surveillance at hospital emergency departments – southeastern Virginia. MMWR. 2004;53(Suppl):56–58.Google Scholar
,Centers for Disease Control and Prevention. Hospital admissions syndromic surveillance – Connecticut, October 2001-June 2004. MMWR. 2005;54(Suppl):169–173.Google Scholar
,Centers for Disease Control and Prevention. Framework for evaluating public health surveillance systems for early detection of outbreaks. MMWR. 2004;53(No. RR-5):1–11.Google Scholar
Mostashari, F, Hartman, J. Syndromic surveillance: a local perspective. J Urban Health. 2003;80(2 Suppl 1):i1–i7.Google Scholar
,Centers for Disease Control and Prevention. High-fidelity injection detectability experiments: a tool for evaluating syndromic surveillance systems. MMWR. 2005;54(Suppl):85–91.Google Scholar
,Centers for Disease Control and Prevention. Initial evaluation of the early aberration reporting system – Florida. MMWR. 2005;54(Suppl):123–130.Google Scholar
,Centers for Disease Control and Prevention. Evaluation of syndromic surveillance based on National Health Service direct derived data – England and Wales. MMWR. 2005;54(Suppl):117–122.Google Scholar
,Centers for Disease Control and Prevention. An evaluation model for syndromic surveillance: assessing the performance of a temporal algorithm. MMWR. 2005;54(Suppl):109–115.Google Scholar
,Centers for Disease Control and Prevention. Simulation for assessing statistical methods of biologic terrorism surveillance. MMWR. 2005;54(Suppl):101–108.Google Scholar
Stoto, M, Schonlau, M, Mariano, L. Syndromic surveillance: is it worth the effort? CHANCE. 2004;17(1):19–24.Google Scholar
Chapman, WW, Dowling, JN, Wagner, MM. Classification of emergency department chief complaints into 7 syndromes: a retrospective analysis of 527, 288 patients. Ann Emerg Med. 2005;46(5):445–455.Google Scholar
Shih, F-Y, Yen, M-Y, Wu, J-S, et al. Challenges faced by hospital healthcare workers in using a syndrome-based surveillance system during the 2003 outbreak of severe acute respiratory syndrome in Taiwan. Infect Control Hosp Epidemiol. 2007;28(3):354–357.Google Scholar
Turner, K, Shaw, K, Coleman, D, Misrachi, A. Augmentation of influenza surveillance with rapid antigen detection at the point-of-care: results of a pilot study in Tasmania, 2004. Commun Dis Intell. 2006;30(2):201–204.Google Scholar

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×