Article | Proceedings from The 16th Scandinavian Conference on Health Informatics 2018, Aalborg, Denmark August 28–29, 2018 | A systematic review of cluster detection mechanisms in syndromic surveillance: Towards developing a framework of cluster detection mechanisms for EDMON system Link�ping University Electronic Press Conference Proceedings
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Title:
A systematic review of cluster detection mechanisms in syndromic surveillance: Towards developing a framework of cluster detection mechanisms for EDMON system
Author:
Prosper Kandabongee Yeng: Department of Computer Science, University of Tromsø – The Arctic University of Norway, Tromsø, Norway Ashenafi Zebene Woldaregay: Department of Computer Science, University of Tromsø – The Arctic University of Norway, Tromsø, Norway Terje Solvoll: Norwegian Centre for E-health Research, University Hospital of North Norway, Tromsø, Norway Gunnar Hartvigsen: Department of Computer Science, University of Tromsø – The Arctic University of Norway, Tromsø, Norway
Download:
Full text (pdf)
Year:
2018
Conference:
Proceedings from The 16th Scandinavian Conference on Health Informatics 2018, Aalborg, Denmark August 28–29, 2018
Issue:
151
Article no.:
011
Pages:
62-69
No. of pages:
8
Publication type:
Abstract and Fulltext
Published:
2018-08-24
ISBN:
978-91-7685-213-2
Series:
Linköping Electronic Conference Proceedings
ISSN (print):
1650-3686
ISSN (online):
1650-3740
Publisher:
Linköping University Electronic Press, Linköpings universitet


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Time lag in detecting disease outbreaks remains a threat to global health security. Currently, our research team is working towards a system called EDMON, which uses blood glucose level and other supporting parameters from people with type 1 diabetes, as indicator variables for outbreak detection. Therefore, this paper aims to pinpoint the state of the art cluster detection mechanism towards developing an efficient framework to be used in EDMON and other similar syndromic surveillance systems. Various challenges such as user mobility, privacy and confidentiality, geographical location estimation and other factors have been considered. To this end, we conducted a systematic review exploring different online scholarly databases. Considering peer reviewed journals and articles, literatures search was conducted between January and March 2018. Relevant literatures were identified using the title, keywords, and abstracts as a preliminary filter with the inclusion criteria and a full text review were done for literatures that were found to be relevant. A total of 28 articles were included in the study. The result indicates that various clustering and aberration detection algorithms have been developed and tested up to the task. In this regard, privacy preserving policies and high computational power requirement were found challenging since it restrict usage of specific locations for syndromic surveillance.

Keywords: Syndromic Surveillance, Spatiotemporal Clustering, Smart Phone, Aberration Detection.

Proceedings from The 16th Scandinavian Conference on Health Informatics 2018, Aalborg, Denmark August 28–29, 2018

Author:
Prosper Kandabongee Yeng, Ashenafi Zebene Woldaregay, Terje Solvoll, Gunnar Hartvigsen
Title:
A systematic review of cluster detection mechanisms in syndromic surveillance: Towards developing a framework of cluster detection mechanisms for EDMON system
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Proceedings from The 16th Scandinavian Conference on Health Informatics 2018, Aalborg, Denmark August 28–29, 2018

Author:
Prosper Kandabongee Yeng, Ashenafi Zebene Woldaregay, Terje Solvoll, Gunnar Hartvigsen
Title:
A systematic review of cluster detection mechanisms in syndromic surveillance: Towards developing a framework of cluster detection mechanisms for EDMON system
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