Abstract
The Real-time Outbreak and Disease Surveillance (RODS) system was initiated by the RODS Laboratory at the University of Pittsburgh in 1999. The system is now an open source project under the GNU license. The RODS development effort has been organized into seven functional areas: overall design, data collection, syndrome classification, database and data warehousing, outbreak detection algorithms, data access, and user interfaces. Each functional area has a coordinator for the open source project, and there is an overall coordinator responsible for the architecture, overall integration of components, and overall quality of the JAVA source code. Figure 8-1 illustrates the RODS' system architecture.
The RODS system as a syndromic surveillance application was originally deployed in Pennsylvania, Utah, and Ohio. As of 2006, RODS performs emergency department surveillance for other states of California, Illinois, Kentucky, Michigan, New Jersey, Nevada, and Wyoming through an ASP model at the University of Pittsburgh, and through local installations in Taiwan, Canada, Mississippi, Michigan, California, and Texas. As of June 2006, about 20 regions with more than 200 healthcare facilities connected to RODS in real-time. It was also deployed during the 2002 Winter Olympics (Espino et al., 2004). It also serves as the user interface for national over-the-counter medication sales surveillance data collected through the NRDM.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsImportant readings:
Wu, T. S., F. Y. Shih, M. Y. Yen, J. S. Wu, S. W. Lu, K. C. Chang, C. Hsiung, J. H. Chou, Y. T. Chu, H. Chang, C. H. Chiu, F. C. Tsui, M. M. Wagner, I. J. Su, and C. C. King (2008), “Establishing a nationwide emergency department-based syndromic surveillance system for better public health responses in Taiwan,” BMC Public Health, 8, p 18.
Shen, Y., C. Adamou, J. N. Dowling, and G. F. Cooper (2008), “Estimating the joint disease outbreak-detection time when an automated biosurveillance system is augmenting traditional clinical case finding,” Journal of Biomedical Informatics, 41, pp 224–231.
Wallstrom, G. L., and W. R. Hogan (2007), “Unsupervised clustering of over-the-counter healthcare products into product categories,” Journal of Biomedical Informatics, 40(6), pp 642–648.
Dara, J., J. N. Dowling, D. Travers, G. F. Cooper, and W. W. Chapman (2007), “Evaluation of preprocessing techniques for chief complaint classification,” Journal of Biomedical Informatics, 41(4), pp 613–623.
Espino, J. U., M. M. Wagner, F. C. Tsui, H. D. Su, R. T. Olszewski, Z. Lie, W. Chapman, X. Zeng, L. Ma, Z. W. Lu, and J. Dara (2004), “The RODS Open Source Project: removing a barrier to syndromic surveillance,” Medinfo, 11(Pt 2), pp 1192–1196.
Tsui, F. C., J. U. Espino, M. M. Wagner, P. Gesteland, O. Ivanov, R. T. Olszewski, Z. Liu, X. Zeng, W. Chapman, W. K. Wong, and A. Moore (2002), “Data, network, and application: technical description of the Utah RODS Winter Olympic Biosurveillance System.” Proceedings of the AMIA Symposium, pp 815–819.
References
Chapman, W.W., Christensen, L., Wagner, M.M., Haug, P., Ivanov, O., Dowling, J., and Olszewski, R. 2005. "Classifying Free-Text Triage Chief Complaints into Syndromic Categories with Natural Language Processing," Artificial Intelligence in Medicine (33:1), pp. 31–40.
Espino, J.U., Wagner, M.M., Szczepaniak, C., Tsui, F.-C., Su, H., Olszewski, R., Liu, Z., Chapman, W.W., Zeng, X., Ma, L., Lu, Z., and Dara, J. 2004. "Removing a Barrier to Computer-Based Outbreak and Disease Surveillance-the Rods Open Source Project," MMWR (CDC) (53(Suppl)), pp. 34–41.
Kaufman, Z., Cohen, E., Peled-Leviatan, T., Lavi, C., Aharonowitz, G., Dichtiar, R., Bromberg, M., Havkin, O., Shalev, Y., Marom, R., Shalev, V., Shemer, J., and Green, M. 2005. "Using Data on an Influenza B Outbreak to Evaluate a Syndromic Surveillance System - Israel, June 2004 [Abstract]," MMWR (CDC) (54(Suppl)), p. 191.
Olszewski, R.T. 2003. "Bayesian Classification of Triage Diagnoses for the Early Detection of Epidemics," 16th Int FLAIRS Conference, pp. 412–416.
Wagner, M.M., Espino, J., Tsui, F.C., Gesteland, P., Chapman, W.W., Ivanov, O., Moore, A., Wong, W., Dowling, J., and Hutman, J. 2004a. "Syndrome and Outbreak Detection Using Chief-Complaint Data - Experience of the Real-Time Outbreak and Disease Surveillance Project," MMWR (CDC) (53(Suppl)), pp. 28–32.
Wallstrom, G.L., Wagner, M., and Hogan, W. 2005. "High-Fidelity Injection Detectability Experiments: A Tool for Evaluating Syndromic Surveillance Systems," MMWR (CDC) (54:Suppl), pp 85–91.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer Science+Business Media, LLC
About this chapter
Cite this chapter
Chen, H., Zeng, D., Yan, P. (2010). RODS. In: Infectious Disease Informatics. Integrated Series in Information Systems, vol 21. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-1278-7_8
Download citation
DOI: https://doi.org/10.1007/978-1-4419-1278-7_8
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4419-1277-0
Online ISBN: 978-1-4419-1278-7
eBook Packages: MedicineMedicine (R0)