Applied Network Science for Relational Chronic Disease Surveillance

Eun Kyong Shin, Arash Shaban-Nejad

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Chronic diseases and conditions are the leading cause of death and disability in the United States. The number of people living with two or more chronic conditions has increased in the last decades and is expected to continue to rise over the upcoming years. Yet, traditional chronic disease surveillance practices have been specialized for a specific symptom or a single health condition. To better understand the complication and complexity of multimorbidity in chronic diseases, this paper suggests the use of network science for multimorbidity network surveillance (MNS). We discuss why the relational perspective in surveillance is critical and how network science can help and be integrated into surveillance and public health practice.

Original languageEnglish (US)
Title of host publicationHealth Informatics Vision
Subtitle of host publicationFrom Data via Information to Knowledge
EditorsMowafa S. Househ, Aikaterini Kolokathi, Arie Hasman, Parisis Gallos, Joseph Liaskos, John Mantas
PublisherIOS Press
Pages336-339
Number of pages4
ISBN (Electronic)9781614999867
DOIs
StatePublished - Jan 1 2019

Publication series

NameStudies in Health Technology and Informatics
Volume262
ISSN (Print)0926-9630
ISSN (Electronic)1879-8365

Fingerprint

Chronic Disease
Comorbidity
Public Health Practice
Public health
Cause of Death
Health

All Science Journal Classification (ASJC) codes

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

Cite this

Shin, E. K., & Shaban-Nejad, A. (2019). Applied Network Science for Relational Chronic Disease Surveillance. In M. S. Househ, A. Kolokathi, A. Hasman, P. Gallos, J. Liaskos, & J. Mantas (Eds.), Health Informatics Vision: From Data via Information to Knowledge (pp. 336-339). (Studies in Health Technology and Informatics; Vol. 262). IOS Press. https://doi.org/10.3233/SHTI190087

Applied Network Science for Relational Chronic Disease Surveillance. / Shin, Eun Kyong; Shaban-Nejad, Arash.

Health Informatics Vision: From Data via Information to Knowledge. ed. / Mowafa S. Househ; Aikaterini Kolokathi; Arie Hasman; Parisis Gallos; Joseph Liaskos; John Mantas. IOS Press, 2019. p. 336-339 (Studies in Health Technology and Informatics; Vol. 262).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Shin, EK & Shaban-Nejad, A 2019, Applied Network Science for Relational Chronic Disease Surveillance. in MS Househ, A Kolokathi, A Hasman, P Gallos, J Liaskos & J Mantas (eds), Health Informatics Vision: From Data via Information to Knowledge. Studies in Health Technology and Informatics, vol. 262, IOS Press, pp. 336-339. https://doi.org/10.3233/SHTI190087
Shin EK, Shaban-Nejad A. Applied Network Science for Relational Chronic Disease Surveillance. In Househ MS, Kolokathi A, Hasman A, Gallos P, Liaskos J, Mantas J, editors, Health Informatics Vision: From Data via Information to Knowledge. IOS Press. 2019. p. 336-339. (Studies in Health Technology and Informatics). https://doi.org/10.3233/SHTI190087
Shin, Eun Kyong ; Shaban-Nejad, Arash. / Applied Network Science for Relational Chronic Disease Surveillance. Health Informatics Vision: From Data via Information to Knowledge. editor / Mowafa S. Househ ; Aikaterini Kolokathi ; Arie Hasman ; Parisis Gallos ; Joseph Liaskos ; John Mantas. IOS Press, 2019. pp. 336-339 (Studies in Health Technology and Informatics).
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