Skip to main content Accessibility help
×
Hostname: page-component-76fb5796d-vvkck Total loading time: 0 Render date: 2024-04-25T10:15:39.243Z Has data issue: false hasContentIssue false

13 - Syndromic Surveillance

from Part II - Operational Issues

Published online by Cambridge University Press:  05 April 2016

Kristi L. Koenig
Affiliation:
University of California, Irvine
Carl H. Schultz
Affiliation:
University of California, Irvine
Get access
Type
Chapter
Information
Koenig and Schultz's Disaster Medicine
Comprehensive Principles and Practices
, pp. 199 - 207
Publisher: Cambridge University Press
Print publication year: 2016

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

Centers for Disease Control and Prevention. Public Health Information Network. PHIN Messaging Guide for Syndromic Surveillance: Emergency Department, Urgent Care, Inpatient and Ambulatory Care Settings. ADT Messages A01, A03, A04 and A08. Optional ORU^R01 Message Notation for Laboratory Data. HL7 Version 2.5.1 (Version 2.3.1 Compatible) Release 2.0. April 21, 2015. http://www.cdc.gov/nssp/documents/guides/syndrsurvmessagguide2_messagingguide_phn.pdfGoogle Scholar
Elliott, AJ, Hughes, HE, Hughes, TC, et al. Establishing an emergency department syndromic surveillance system to support the London 2012 Olympic and Paralympic Games. Emerg Med J 2012; 29(12): 954960.CrossRefGoogle Scholar
Smith, GE, Cooper, DL, Loveridge, P. A national syndromic surveillance system for England and Wales using calls to a telephone helpline. Eurosurveillance 2006; 11(12): 220224.CrossRefGoogle ScholarPubMed
Triple S Project. Assessment of syndromic surveillance in Europe. Lancet 2011; 378(9806): 18331834.CrossRefGoogle Scholar
Josseran, L, Nicolau, J, Caillère, N, et al. Syndromic surveillance based on emergency department activity and crude mortality: two examples. Euro Surveil 2006; 11(12): 225229.CrossRefGoogle ScholarPubMed
Rockx, B, van Asten, L, van den Wijngaard, C, et al. Syndromic surveillance in the Netherlands for the early detection of West Nile virus epidemics. Vector Borne Zoonotic Dis 2006; 6(2): 161169.CrossRefGoogle ScholarPubMed
Wu, TSJ, Shih, FYF, Yen, MY, et al. Establishing a nationwide emergency department-based syndromic surveillance system for better public health responses in Taiwan. BMC Public Health 2008; 8: 18.CrossRefGoogle ScholarPubMed
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): 910922.CrossRefGoogle ScholarPubMed
Green, M, Kaufman, Z. Surveillance for early detection and monitoring of infectious disease outbreaks associated with bioterrorism. Isr Med Assoc J 2002; 4(7): 503506.Google ScholarPubMed
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): 447452.CrossRefGoogle ScholarPubMed
Begier, E, Sockwell, D, Branch, L, et al. The National Capitol Region's Emergency Department Syndromic Surveillance System: do chief complain and discharge diagnosis yield different results? Emerg Infect Dis 2003; 9(3): 393396.CrossRefGoogle 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(2 Suppl. 1): i25i31.CrossRefGoogle ScholarPubMed
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): i97i106.CrossRefGoogle ScholarPubMed
Buehler, J, Berkelman, R, Hartley, D, Peters, C. Syndromic surveillance and bioterrorism-related epidemics. Emerg Infect Dis 2003; 9(10): 11971204.CrossRefGoogle ScholarPubMed
Centers for Disease Control and Prevention. What is syndromic surveillance? MMWR 2004; 53(Suppl.): 711.Google Scholar
Centers for Disease Control and Prevention. New York City syndromic surveillance systems. MMWR 2004; 53(Suppl.): 2527.Google Scholar
Centers for Disease Control and Prevention. Progress in understanding and using over-the-counter pharmaceuticals for syndromic surveillance. MMWR 2004; 53(Suppl.): 117122.Google Scholar
Hope, K, Durrheim, DN, d'Espaignet, ET, Dalton, C. Syndromic surveillance: is it a useful tool for local outbreak detection? J Epidemiol Community Health 2006; 60: 374375.CrossRefGoogle ScholarPubMed
Buehler, JW, Whitney, EA, Smith, D, et al. Situational uses of syndromic surveillance. Biosecur and Bioterror: Biodefense Strategy, Practice, and Science 2009; 7(2): 165177.CrossRefGoogle ScholarPubMed
International Society for Disease Surveillance. Syndromic Surveillance for meaningful use: background and resources. ISDS Brief. April 2012. www.syndromic.org (Accessed November 16, 2012).Google Scholar
Lenert, L, Sundwall, DN. Opportunity Forged by Crisis: Public Health Surveillance and Meaningful Use Regulations: A Crisis of Opportunity. Am J Public Health 2012; 102(3): e1e7.CrossRefGoogle Scholar
Chen, H, Zeng, D. Yan, P. Public Health Syndromic Surveillance Systems. In: Infectious Disease Informatics: Syndromic Surveillance for Public Health and BioDefense, Springer Science + Business Media, LLC, New York, 2010. http://www.springer.com/us/book/9781441912770 (Accessed August 20, 2015).CrossRefGoogle Scholar
Centers for Disease Control and Prevention. BioSense 2.0. http://www.cdc.gov/biosense/biosense20.html (Accessed July 16, 2014).Google Scholar
Chan, EH, Brewer, TF, Madoff, LC, et al. Global capacity for emerging infectious disease detection. Proceedings of the National Academy of Sciences of the United States of America 2010; 107(50): 2170121706.CrossRefGoogle ScholarPubMed
Donahue, DA. BioWatch and the Brown Cap. Journal of Homeland Security and Emergency Management 2011; 8(1): Article 5.CrossRefGoogle Scholar
Campbell, TC, Hodanics, CJ, Babin, SM, et al. Developing open source, self-contained disease surveillance software applications for use in resource-limited settings. BMC Med Inform and Decis Making 2012; 12: 99.CrossRefGoogle ScholarPubMed
Lewis, SL, Feighner, BH, Loschen, WA, et al. SAGES: A suite of freely-available software tools for electronic disease surveillance in resource-limited settings. PLoS One 2011; 6(5): e19750. DOI: 10.1371/journal.pone.0019750.CrossRefGoogle ScholarPubMed
Yan, W, Nie, S, Xu, B, et al. Establishing a web-based integrated surveillance system for early detection of infectious disease epidemic in rural China: a field experimental study. BMC Med Inform and Decis Making 2012; 12: 4.CrossRefGoogle 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): 204210.CrossRefGoogle ScholarPubMed
Centers for Disease Control and Prevention. Information system architectures for syndromic surveillance. MMWR 2004; 53(Suppl.): 203208.Google Scholar
Forslund, D, Joyce, E, Burr, T, et al. Setting standards for improved syndromic surveillance. IEEE Eng Med Biol Mag 2004; 23(1): 6570.CrossRefGoogle ScholarPubMed
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): 141150.CrossRefGoogle ScholarPubMed
Department of Homeland Security. National Biosurveillance Integration Center. http://www.dhs.gov/national-biosurveillance-integration-center (Accessed July 16, 2014).Google Scholar
Reis, B, Mandl, K. Time series modeling for syndromic surveillance. BMC Med Inform Decis Making 2003; 3: 2.CrossRefGoogle ScholarPubMed
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): 217224.CrossRefGoogle ScholarPubMed
Reis, B, Mandl, K. Syndromic Surveillance: The effects of syndrome grouping on model accuracy and outbreak detection. Ann Emerg Med 2004; 44(3): 235241.CrossRefGoogle ScholarPubMed
Feinberg, S, Shmueli, G. Statistical issues and challenges associated with rapid detection of bio-terrorist attacks. Statist Med 2005; 24: 513529.CrossRefGoogle 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: 543550.CrossRefGoogle ScholarPubMed
Centers for Disease Control and Prevention. Bivariate method for spatio-temporal syndromic surveillance MMWR 2004; 53(Suppl.): 6166.Google Scholar
Centers for Disease Control and Prevention. Role of data aggregation in biosurveillance detection strategies with applications from ESSENCE. MMWR 2004; 53(Suppl.): 6773.Google Scholar
Centers for Disease Control and Prevention. Scan statistics for temporal surveillance for biologic terrorism. MMWR 2004; 53(Suppl.): 7478.Google Scholar
Centers for Disease Control and Prevention. Approaches to syndromic surveillance when data consist of small regional counts. MMWR 2004; 53(Suppl.): 7985.Google Scholar
Mandl, KD, Reis, B, Cassa C: Measuring Outbreak-Detection Performance by Using Controlled Feature Set Simulations. Centers for Disease Control and Prevention, MMWR 2004; 53(Suppl): 130136. http://www.cdc.gov/mmwr/preview/mmwrhtml/su5301a26.htm (Accessed August 20, 2015).Google Scholar
Centers for Disease Control and Prevention. Benchmark data and power calculations for evaluating disease outbreak detection methods. MMWR 2004; 53(Suppl.): 144151.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): 409419.CrossRefGoogle ScholarPubMed
Centers for Disease Control and Prevention. Use of multiple data streams to conduct Bayesian biologic surveillance. MMWR 2005; 54(Suppl.): 6369.Google Scholar
Centers for Disease Control and Prevention. Deciphering data anomalies in BioSense. MMWR 2005; 54(Suppl.): 133139.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.CrossRefGoogle ScholarPubMed
Ginsberg, J, Mohebbi, MH, Patel, RS, et al. Detecting influenza epidemics using search engine query data. Nature 2009; 457(7232): 10121014.CrossRefGoogle ScholarPubMed
Brownstein, JS, Freifeld, CC, Madoff, LC. Digital Disease Detection – Harnessing the web for public health surveillance. N Engl J Med 2009; 360(21): 21532157.CrossRefGoogle ScholarPubMed
Corley, CD, Cook, DJ, Mikler, AR, Singh, KP. Using web and social media for influenza surveillance. Adv Exp Med Biol 2010; 680: 559564.CrossRefGoogle ScholarPubMed
Butler, D. When Google got flu wrong. Nature 2013; 494(7436): 155156.CrossRefGoogle ScholarPubMed
Freifeld, CC, Chunara, R, Mekaru, SR, et al. Participatory epidemiology : use of mobile phones for community based health reporting. PLoS Medicine 2010; 7(12): e1000376.CrossRefGoogle ScholarPubMed
Fuller, S. Tracking the global express: new tools addressing disease threats across the world. Epidemiology 2010; 21(6): 769771.CrossRefGoogle Scholar
Yang, M, Li, Y-J, Kiang, M. Uncovering social media data for public health surveillance. PACIS 201 Proceedings, Paper 218. 2011. http://aisel.aisnet.org/pacis2011/218 (Accessed November 16, 2012).Google Scholar
Kool, JL, Paterson, B, Pavlin, BI, et al. Pacific-wide simplified syndromic surveillance for early warning of outbreaks. Global Public Health: An International Journal for Research, Policy and Practice 2012; 7(7): 670681.CrossRefGoogle ScholarPubMed
Paul, MJ, Dredze, M. You are what you tweet: analyzing Twitter for public health. Proceedings of the 5th International AAAI Conference on Weblogs and Social Media. Association for the Advancement of Artificial Intelligence. 2011. http://www.aaai.org/ocs/index.php/ICWSM/ICWSM11/paper/view/2880/3264 (Accessed August 20, 2015).Google Scholar
Potts, JA, Gibbons, RV, Rothman, AL, et al. Prediction of Dengue disease severity among pediatric Thai patients using early clinical laboratory indicators. Negl Trop Dis 2010; 4(8): e769.CrossRefGoogle ScholarPubMed
Gharbi, M, Quenel, P, Gustave, J, et al. Time series analysis of dengue incidence in Guadeloupe, French West Indies: forecasting models using climate variables as predictors. BMC Infect Dis 2011; 11: 166.CrossRefGoogle ScholarPubMed
Gamage, S, Mohtashemi, M, Simbartl, L, Kralovic, S, Wallace, K, Roselle, G. Analysis of dengue in Department of Veterans Affairs (VA) patients in Puerto Rico. Emerging Health Threats Journal 2011; 4: 11184.CrossRefGoogle Scholar
Liu, Q, Liu, X, Jiang, B, Yang, W. Forecasting incidence of hemorrhagic fever with renal syndrome in China using ARIMA model. BMC Infect Dis 2011; 11: 218.CrossRefGoogle Scholar
Stoto, MA, Dempsey, JX, Baer, A, et al. Expert meeting on privacy, confidentiality and other legal ethical issues in syndromic surveillance. Report from an International Society for Disease Surveillance Consultation, Washington, DC, October 4–5, 2007. Advances in Disease Surveillance 2009; 7(2). http://faculty.washington.edu/lober/www.isdsjournal.org/htdocs/articles/6217.pdf (Accessed August 21, 2015).Google Scholar
Francis, LP, Battin, MP, Jacobson, J, Smith, C. Syndromic surveillance and patients as victims and vectors. Bioethical Inquiry 2009; 6: 187195. http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1517420 (Accessed August 21, 2015).CrossRefGoogle 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
×