Cristin-resultat-ID: 1606596
Sist endret: 27. mars 2019 14:55
NVI-rapporteringsår: 2018
Resultat
Vitenskapelig oversiktsartikkel/review
2018

A systematic review of cluster detection mechanisms in syndromic surveillance: Towards developing a framework of cluster detection mechanisms for EDMON system

Bidragsytere:
  • Prosper Kandabongee Yeng
  • Ashenafi Zebene Woldaregay
  • Terje Solvoll og
  • Gunnar Hartvigsen

Tidsskrift

Linköping Electronic Conference Proceedings
ISSN 1650-3686
e-ISSN 1650-3740
NVI-nivå 1

Om resultatet

Vitenskapelig oversiktsartikkel/review
Publiseringsår: 2018
Sider: 62 - 69
Open Access

Beskrivelse Beskrivelse

Tittel

A systematic review of cluster detection mechanisms in syndromic surveillance: Towards developing a framework of cluster detection mechanisms for EDMON system

Sammendrag

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.

Bidragsytere

Prosper Yeng

Bidragsyterens navn vises på dette resultatet som Prosper Kandabongee Yeng
  • Tilknyttet:
    Forfatter
    ved Institutt for informatikk ved UiT Norges arktiske universitet

Ashenafi Zebene Woldaregay

  • Tilknyttet:
    Forfatter
    ved Institutt for informatikk ved UiT Norges arktiske universitet

Terje Geir Solvoll

Bidragsyterens navn vises på dette resultatet som Terje Solvoll
  • Tilknyttet:
    Forfatter
    ved Nasjonalt senter for e-helseforskning ved Universitetssykehuset Nord-Norge HF
Aktiv cristin-person

Gunnar Hartvigsen

  • Tilknyttet:
    Forfatter
    ved Institutt for informatikk ved UiT Norges arktiske universitet
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