Article | Proceedings from The 14th Scandinavian Conference on Health Informatics 2016, Gothenburg, Sweden, April 6-7 2016 | Electronic Disease Surveillance System Based on Input from People with Diabetes: An Early Outbreak Detection Mechanism
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Title:
Electronic Disease Surveillance System Based on Input from People with Diabetes: An Early Outbreak Detection Mechanism
Author:
Ashenafi Zebene Woldaregay: Department of Computer Science, University of Tromsø – The Arctic University of Norway, Tromsø, Norway Klaske van Vuurden: Department of Computer Science, University of Tromsø – The Arctic University of Norway, Tromsø, Norway Eirik Årsand: Department of Clinical Medicine, University of Tromsø – The Arctic University of Norway, Tromsø, Norway / Norwegian Centre for eHealth Research, University Hospital of North Norway, Tromsø Taxiarchis Botsis: Department of Computer Science, University of Tromsø – The Arctic University of Norway, Tromsø, Norway Gunnar Hartvigsen: Department of Computer Science, University of Tromsø – The Arctic University of Norway, Tromsø, Norway / Norwegian Centre for eHealth Research, University Hospital of North Norway, Tromsø
Download:
Full text (pdf)
Year:
2016
Conference:
Proceedings from The 14th Scandinavian Conference on Health Informatics 2016, Gothenburg, Sweden, April 6-7 2016
Issue:
122
Article no.:
004
Pages:
23-27
No. of pages:
6
Publication type:
Abstract and Fulltext
Published:
2016-03-31
ISBN:
978-91-7685-776-2
Series:
Linköping Electronic Conference Proceedings
ISSN (print):
1650-3686
ISSN (online):
1650-3740
Publisher:
Linköping University Electronic Press, Linköpings universitet


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Major infectious disease threat to the public health are either naturally occurring or artificially induced bioterrorist attack. Whether it is pandemics or epidemics, both are the burden of any public health authority, which needs well preparedness, proper monitoring and early detection of an outbreak before it has gone so far. Nowadays, syndromic surveillance is the most practiced approach, which uses data prior to laboratory or physicians verification including absenteeism, over-the-counter and prescription pharmacy sales, internet search volumes and others. Moreover, various bio-sensors networks for disease surveillance purpose have been put in place. However, disease surveillance systems, which detects outbreak during incubation period (before the onset of the first symptoms) is an ongoing research topic. According to recent findings, the presence of illness and elevated blood glucose values are found to be highly correlated. Therefore, the purpose of this project is to use either the continuous blood glucose measurements or mobile phone based diabetic patient’s historical data, such as blood glucose, insulin, diet, and meal, to develop an algorithm that is cable of detecting a cluster of people with an elevated blood glucose levels within a specific areas. We have developed an interval prediction mechanisms that can predict a step ahead blood glucose values of the individual patient. Thus, the goal of the prediction interval model is to obtain a 100(1 a) % forecast interval single-step-ahead into the future for glucose response at a given input level of past blood glucose, insulin, physical exercise and carbohydrate. Therefore, the measured blood glucose value can be compared against the interval predicted by our model. At this point, we have carried out simulation using continuous blood glucose measurements (CGM) from some group of diabetes patients, which shows the effectiveness of our approach. The single step point prediction is found to be accurate with a root mean square error (RMSE) of 0.2121 mmol/l. Moreover, we are capable of following the individual blood glucose evolution accurately with a significance level of a =0.01. The system is currently under experiments and is not yet tested fully at a prototype stage.

Keywords: diabetes mellitus, continuous blood glucose measurement (cgm), diabetes diary, blood glucose prediction, outbreak detection, electronic disease surveillance.

Proceedings from The 14th Scandinavian Conference on Health Informatics 2016, Gothenburg, Sweden, April 6-7 2016

Author:
Ashenafi Zebene Woldaregay, Klaske van Vuurden, Eirik Ă…rsand, Taxiarchis Botsis, Gunnar Hartvigsen
Title:
Electronic Disease Surveillance System Based on Input from People with Diabetes: An Early Outbreak Detection Mechanism
References:

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Proceedings from The 14th Scandinavian Conference on Health Informatics 2016, Gothenburg, Sweden, April 6-7 2016

Author:
Ashenafi Zebene Woldaregay, Klaske van Vuurden, Eirik Ă…rsand, Taxiarchis Botsis, Gunnar Hartvigsen
Title:
Electronic Disease Surveillance System Based on Input from People with Diabetes: An Early Outbreak Detection Mechanism
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