Hidden Cluster Detection for Infectious Disease Control and Quarantine Management
Infectious diseases that are caused by pathogenic microorganisms can spread fast and far, from one person to another, directly or indirectly. Prompt quarantining of the infected from the rest, coupled with contact tracing, has been an effective measure to encounter outbreaks. However, urban life and international travel make containment difficult. Furthermore, the length of incubation periods of some contagious diseases like SARS enable infected passengers to elude health screenings before first symptoms appear and thus to carry the disease further. Detecting and visualizing contact–tracing networks, and immediately identifying the routes of infection, are thus important. We apply information visualization and hidden cluster detection for finding cliques of potentially infected people during incubation. Preemptive control and early quarantine are hence possible by our method. Our prototype Infectious Disease Detection and Quarantine Management System (IDDQMS), which can identify and trace clusters of infection by mining patients’ history, is introduced in this paper.
KeywordsInfectious Disease Cluster Detection Contact Tracing SARS Health Care Information System
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This work is funded by the University of Macau Research Grant “Hidden Cluster Detection and Visual Data Mining Framework for Infectious Disease Control and Quarantine Management”. The authors thank Dr. Lam Chong, Coordinator for Control of Communicable Disease and Surveillance of Diseases, CDC, Government of Special Administrative Region Health Bureau, Macau, for his insightful comments on the project.
- 1.World Health Organization: Summary of probable SARS cases with onset of illness from 1 November 2002 to 31 July 2003. http://www.who.int/csr/sars/country/table2004_04_21/en/
- 2.World Health Organization: Ten things you need to know about pandemic influenza. http://www.who.int/csr/disease/influenza/pandemic10things/en/
- 3.Zeng, D., Chen, H., Tseng, C., Larson, C.A., Eidson, M., Gotham, I., Lynch, C., Ascher, M.: Towards a national infectious disease information infrastructure: a case study in West Nile virus and botulism. In: 2004 Annual National Conference on Digital Government Research, Seattle, WA, IEEE (2004) 1–10Google Scholar
- 4.SAHANA, Free and open source disaster management system. http://www.sahana.lk/
- 7.Torgerson, W.S.: Multidimensional scaling: I. Theory and method. Psychometrika 17 (1952)Google Scholar
- 8.JUNG, Java Universal Network/Graph Framework. http://jung.sourceforge.net/
- 9.MySQL homepage. http://www.mysql.com/
- 10.Goddard, N.L., Delpecha, V.C., Watsona, J.M., Reganb, M., , A., N.: Lessons learned from SARS: The experience of the health protection agency, England. Public Health 120(1) (2006) 27–32Google Scholar
- 12.Leong, K.I., Si, Y.W., Biuk-Aghai, R.P., Fong, S.: Contact tracing in health-care digital ecosystems for infectious disease control and quarantine management. In: Third IEEE International Conference on Digital Ecosystems and Technologies (DEST 2009), IEEE (2009) 210–215Google Scholar
- 13.Tsang, K.W., Ho, P.L., Ooi, G.C., Yee, W.K., Wang, T., Chan-Yeung, M., Lam, W.K., Seto, W.H., Yam, L.Y., Cheung, T.M., Wong, P.C., Lam, B., Ip, M.S., Chan, J., Yuen, K.Y., Lai, K.N.: A cluster of cases of severe acute respiratory syndrome in Hong Kong. The New England Journal of Medicine 348(20) (2003) 1977–85CrossRefGoogle Scholar
- 14.Abraham, T.: Twenty–First Century Plague -The Story of SARS. Johns Hopkins University Press (2005)Google Scholar
- 15.The SARS Expert Committee of Hong Kong: Report of the SARS expert committee -SARS in hong kong: from experience to action. http://www.sarsexpertcom.gov.hk/english/reports/reports.html (2003)
- 16.The Hong Kong Legislative Council: Report of the select committee to inquire into the handling of the severe acute respiratory syndrome outbreak by the government and the hospital authority. http://www.legco.gov.hk/yr03-04/english/sc/sc_sars/reports/sars_rpt.htm (July 2004)
- 17.Huxtable, N.: Population density hinders fight against TB. Macau Daily Times (28 June 2008)Google Scholar
- 18.Centers for Disease Control and Prevention: Interim guidance for clinicians on identifying and caring for patients with Swine–origin Influenza A (H1N1) virus infection. http://www.cdc.gov/h1n1flu/identifyingpatients.htm
- 19.Wang, T.D., Plaisant, C., Quinn, A.J., Stanchak, R., Murphy, S., Shneiderman, B.: Aligning temporal data by sentinel events: discovering patterns in electronic health records. In: The twenty-sixth annual SIGCHI conference on Human factors in computing systems, CHI ’08, New York, NY, USA, ACM (2008) 457–466CrossRefGoogle Scholar
- 20.LingPipe. http://www.alias-i.com/lingpipe/