Abstract
Syndromic Surveillance is typically a system used for early detection of bioterrorism attacks, pandemic flu or other emerging diseases, which monitors symptoms of outpatients or is conducted in the Emergency Department. However, if we monitor symptoms of inpatients, we can apply Syndromic Surveillance to early detection of nosocomial infection. To test this possibility, we constructed and are performing a Syndromic Surveillance System for inpatients who have fever, respiratory symptoms, diarrhea, vomiting or rash. We will then evaluate its statistical properties and its usefulness.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Henning, K.J.: What is Syndromic Surveillance? MMWR 53(Suppl.), 7–11 (2004)
Siegist, D.W., Tennyson, S.L.: Technologically-Based Biodefense, Potomac Institute fof Policy Studies (2003)
Buehler, J.W., et al.: Syndromic surveillance and bioterrorism-related epidemics. Emerg. Infect. Dis. 9, 1197–1204 (2003)
Kikuchi, K., et al.: Examination of Syndromic Surveillance for Early Detection of Nosocomial Outbreaks. Presented at National Syndromic Surveillance Conference (2006)
Mandel, K.D., Reis, B., Cassa, C.: Measuring Outbreak-Detection Performance by using Controlled Feature Set Simulation. MMWR, 130–136 (2004)
Nordin, J.D., et al.: Simulated anthrax attacks and syndromic surveillance. Emerg Infect Dis. (Sep. 2005), Available from http://www.cdc.gov/ncidod/EID/vol11no09/05-0223.htm
Buckeridge, D.L., et al.: Evaluation of syndromic surveillance systems design of an epidemic simulation model. MMWR 53(Suppl.),137–143 (2004)
Kulldorff, M., et al.: Benchmark data and power calculations for evaluating disease outbreak detection methods. MMWR 53(Suppl.), 144–151 (2004)
Hutwagner, L., et al.: The bioterrorism preparedness and response Early Aberration Reporting System (EARS). J. Urban Health 80, 89–96 (2003)
Hutwagner, L., et al.: Comparing Aberration Detection Methods with Simulated Data. Emerging Infectious Diseases 11(2), 314–316 (2005)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer Berlin Heidelberg
About this paper
Cite this paper
Kikuchi, K., Ohkusa, Y., Sugawara, T., Taniguchi, K., Okabe, N. (2007). Syndromic Surveillance for Early Detection of Nosocomial Outbreaks. In: Zeng, D., et al. Intelligence and Security Informatics: Biosurveillance. BioSurveillance 2007. Lecture Notes in Computer Science, vol 4506. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72608-1_20
Download citation
DOI: https://doi.org/10.1007/978-3-540-72608-1_20
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72607-4
Online ISBN: 978-3-540-72608-1
eBook Packages: Computer ScienceComputer Science (R0)