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Disease surveillance systems
KTH, School of Information and Communication Technology (ICT), Communication: Services and Infrastucture, Software and Computer Systems, SCS.
2011 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Recent advances in information and communication technologies have made the development and operation of complex disease surveillance systems technically feasible, and many systems have been proposed to interpret diverse data sources for health-related signals. Implementing these systems for daily use and efficiently interpreting their output, however, remains a technical challenge.

This thesis presents a method for understanding disease surveillance systems structurally, examines four existing systems, and discusses the implications of developing such systems. The discussion is followed by two papers. The first paper describes the design of a national outbreak detection system for daily disease surveillance. It is currently in use at the Swedish Institute for Communicable Disease Control. The source code has been licenced under GNU v3 and is freely available. The second paper discusses methodological issues in computational epidemiology, and presents the lessons learned from a software development project in which a spatially explicit micro-meso-macro model for the entire Swedish population was built based on registry data.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology , 2011. , 52 p.
Trita-ICT-ECS AVH, ISSN 1653-6363 ; 11:06
Keyword [en]
disease surveillance, syndromic surveillance, outbreak detection, health informatics, computer science
National Category
Health Care Service and Management, Health Policy and Services and Health Economy Public Health, Global Health, Social Medicine and Epidemiology Information Science
URN: urn:nbn:se:kth:diva-33661ISBN: 978-91-7501-018-2OAI: diva2:416962
2011-06-10, Sal D, Isafjordsgatan 39, Forum 164 40, Kista, Stockholm, 14:00 (English)
QC 20110520Available from: 2011-05-20 Created: 2011-05-13 Last updated: 2011-05-20Bibliographically approved
List of papers
1. CASE: a framework for computer supported outbreak detection
Open this publication in new window or tab >>CASE: a framework for computer supported outbreak detection
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2010 (English)In: BMC Medical Informatics and Decision Making, ISSN 1472-6947, Vol. 10, 14- p.Article in journal (Refereed) Published
Abstract [en]

Background: In computer supported outbreak detection, a statistical method is applied to a collection of cases to detect any excess cases for a particular disease. Whether a detected aberration is a true outbreak is decided by a human expert. We present a technical framework designed and implemented at the Swedish Institute for Infectious Disease Control for computer supported outbreak detection, where a database of case reports for a large number of infectious diseases can be processed using one or more statistical methods selected by the user. Results: Based on case information, such as diagnosis and date, different statistical algorithms for detecting outbreaks can be applied, both on the disease level and the subtype level. The parameter settings for the algorithms can be configured independently for different diagnoses using the provided graphical interface. Input generators and output parsers are also provided for all supported algorithms. If an outbreak signal is detected, an email notification is sent to the persons listed as receivers for that particular disease. Conclusions: The framework is available as open source software, licensed under GNU General Public License Version 3. By making the code open source, we wish to encourage others to contribute to the future development of computer supported outbreak detection systems, and in particular to the development of the CASE framework.

National Category
Biomedical Laboratory Science/Technology
urn:nbn:se:kth:diva-28315 (URN)10.1186/1472-6947-10-14 (DOI)000276394900001 ()2-s2.0-77949430283 (ScopusID)
QC 20110113Available from: 2011-01-13 Created: 2011-01-12 Last updated: 2011-05-20Bibliographically approved

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