Abstract
To enhance the effectiveness of health care, many medical institutions have started transitioning to electronic health and medical records and sharing these records between institutions. The large amount of complex and diverse data makes it difficult to identify and track relationships and trends, such as disease outbreaks, from the data points. INFERD: Information Fusion Engine for Real-Time Decision-Making is an information fusion tool that dynamically correlates and tracks event progressions. This paper presents a methodology that utilizes the efficient and flexible structure of INFERD to create social networks representing progressions of disease outbreaks. Individual symptoms are treated as features allowing multiple hypothesis being tracked and analyzed for effective and comprehensive syndromic surveillance.
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
Sudit, M., Stotz, A., Holender, M.: Situational awareness of a coordinated cyber attack. In: Proceedings of International Data Fusion Conference, Quebec City, Quebec, CA (July 2007)
Health Level 7, http://www.hl7.org/ (accessed 11/4/2009)
NHIN Connect, http://www.connectopensource.org (accessed 11/4/2009)
Syndromic Surveillance: an Applied Approach to Outbreak Detection, http://www.cdc.gov/ncphi/disss/nndss/syndromic.htm (accessed 11/4/2009)
Eubank, S., Guclu, H., Kumar, V.S., Marathe, M.V., Srinivasan, A., Toroczkai, Z., Wang, N.: Modelling disease outbreaks in realistic urban social networks. Nature 429(6988), 180–184 (2004)
Barabasi, A.L., Jeong, H., Neda, Z., Ravasz, E., Schubert, A., Vicsek, T.: Evolution of the social network of scientific collaborations. Physica A 311(3), 590–614 (2002)
Newman, M.E.J.: Analysis of weighted networks. Phys. Rev. E. 70(5) (November 2004)
Girvan, M., Newman, M.E.J.: Community structure in social and biological networks. Proc. Natl. Acad. Sci. USAÂ 99, 7821 (2002)
Girvan, M., Newman, M.E.J.: Community structure in social and biological networks. Proceedings of the National Academy of Sciences of the United States of America 99(12), 7821–7826 (2002)
Wilson, A.G., Wilson, G.D., Olwell, D.H.: Evaluating Statistical Methods for Syndromic Surveillance, pp. 141–172. Springer, New York (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Holsopple, J., Yang, S., Sudit, M., Stotz, A. (2010). Dynamic Creation of Social Networks for Syndromic Surveillance Using Information Fusion. In: Chai, SK., Salerno, J.J., Mabry, P.L. (eds) Advances in Social Computing. SBP 2010. Lecture Notes in Computer Science, vol 6007. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12079-4_41
Download citation
DOI: https://doi.org/10.1007/978-3-642-12079-4_41
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-12078-7
Online ISBN: 978-3-642-12079-4
eBook Packages: Computer ScienceComputer Science (R0)