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  • Print publication year: 2009
  • Online publication date: August 2011

11 - Syndromic Surveillance

from PART II - OPERATIONAL ISSUES

Summary

The concept of syndromic surveillance is relatively straightforward, although the proof of concept and/or value is yet to be shown. There are multiple syndromic surveillance systems in use around the globe and even across the U.S. Syndromic surveillance contrasts with the "knowledgeable intermediary" the single clinician who, recognizing that a patient or group of patients arriving for care display an unusual set of signs or symptoms, activates public health authorities. This chapter gives a brief listing of several U.S. surveillance systems, past and present, using a variety of methodologies to achieve certain goals. To add value to any syndromic surveillance system, the addition of nonhuman data might also be useful. There are a variety of mathematical data analysis formulae in place in the extant syndromic surveillance systems. Syndromic surveillance is necessary because of difficulty establishing a diagnosis in a timely manner for human infectious diseases.
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.
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.
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.
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.
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.
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.
Buehler, J, Berkelman, R, Hartley, D, Peters, C. Syndromic surveillance and bioterrorism-related epidemics. Emerg Infect Dis. 2003;9(10):1197–1204.
,Centers for Disease Control and Prevention. What is syndromic surveillance? MMWR. 2004;53(Suppl):7–11.
,Centers for Disease Control and Prevention. New York City syndromic surveillance systems. MMWR. 2004;53(Suppl):25–27.
,Centers for Disease Control and Prevention. Progress in understanding and using over-the-counter pharmaceuticals for syndromic surveillance. MMWR. 2004;53(Suppl):117–122.
,Centers for Disease Control and Prevention. Use of Medicaid prescription data for syndromic surveillance – New York. MMWR. 2005;54(Suppl):31–4.
,Centers for Disease Control and Prevention. Poison control center-based syndromic surveillance for foodborne illness. MMWR. 2005;54(Suppl):35–40.
,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.
,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.
Vergu, E, Grais, R, Sarter, H, et al. Medication sales and syndromic surveillance, France. Emerg Infect Dis. 2006;12(3):416–421.
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.
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.
,Centers for Disease Control and Prevention. Taming variability in free text: application to health surveillance. MMWR. 2004;53(Suppl):95–100.
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.
,Centers for Disease Control and Prevention. ESSENCE II and the framework for evaluating syndromic surveillance systems. MMWR. 2004;53(Suppl):159–165.
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.
,Centers for Disease Control and Prevention. Information system architectures for syndromic surveillance. MMWR. 2004;53(Suppl):203–208.
Forslund, D, Joyce, E, Burr, T, et al. Setting standards for improved syndromic surveillance. IEEE Eng Med Biol Mag. 2004;23(1):65–70.
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.
Reis, B, Mandl, K. Time series modeling for syndromic surveillance. BMC Med Inform Decis Making. 2003;3:2.
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.
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.
Feinberg, S, Shmueli, G. Statistical issues and challenges associated with rapid detection of bio-terrorist attacks. Statist Med. 2005;24:513–529.
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.
,Centers for Disease Control and Prevention. Bivariate method for spatio-temporal syndromic surveillance. MMWR. 2004;53(Suppl);61–66.
,Centers for Disease Control and Prevention. Role of data aggregation in biosurveillance detection strategies with applications from ESSENCE. MMWR. 2004;53(Suppl):67–73.
,Centers for Disease Control and Prevention. Scan statistics for temporal surveillance for biologic terrorism. MMWR. 2004;53(Suppl):74–78.
,Centers for Disease Control and Prevention. Approaches to syndromic surveillance when data consist of small regional counts. MMWR. 2004;53(Suppl):79–85.
,Centers for Disease Control and Prevention. Measuring outbreak-detection performance by using controlled feature set simulations. MMWR. 2004;53(Suppl):130–136.
,Centers for Disease Control and Prevention. Benchmark data and power calculations for evaluating disease outbreak detection methods. MMWR. 2004;53(Suppl):144–151.
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.
,Centers for Disease Control and Prevention. Use of multiple data streams to conduct Bayesian biologic surveillance. MMWR. 2005;54(Suppl):63–69.
,Centers for Disease Control and Prevention. Deciphering data anomalies in BioSense. MMWR. 2005;54(Suppl):133–139.
Najmi, A-H, Magruder, S. An adaptive prediction and detection algorithm for multistream syndromic surveillance. BMC Med Inform Decis Making. 2005;5:33.
,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.
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.
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.
,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.
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.
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.
,Centers for Disease Control and Prevention. Syndromic surveillance at hospital emergency departments – southeastern Virginia. MMWR. 2004;53(Suppl):56–58.
,Centers for Disease Control and Prevention. Hospital admissions syndromic surveillance – Connecticut, October 2001-June 2004. MMWR. 2005;54(Suppl):169–173.
,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.
Mostashari, F, Hartman, J. Syndromic surveillance: a local perspective. J Urban Health. 2003;80(2 Suppl 1):i1–i7.
,Centers for Disease Control and Prevention. High-fidelity injection detectability experiments: a tool for evaluating syndromic surveillance systems. MMWR. 2005;54(Suppl):85–91.
,Centers for Disease Control and Prevention. Initial evaluation of the early aberration reporting system – Florida. MMWR. 2005;54(Suppl):123–130.
,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.
,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.
,Centers for Disease Control and Prevention. Simulation for assessing statistical methods of biologic terrorism surveillance. MMWR. 2005;54(Suppl):101–108.
Stoto, M, Schonlau, M, Mariano, L. Syndromic surveillance: is it worth the effort? CHANCE. 2004;17(1):19–24.
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.
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.
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.