Tkachenko, Nataliya, Chotvijit, Sarunkorn, Gupta, Neha, Bradley, Emma, Gilks, Charlotte, Guo, Weisi, Crosby, Henry James, Shore, Eliot, Thiarai, Malkiat, Procter, Rob and Jarvis, Stephen A. (2017) Google trends can improve surveillance of Type 2 diabetes. Scientific Reports, 7 . 4993. doi:10.1038/s41598-017-05091-9 ISSN 2045-2322.

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Abstract

Recent studies demonstrate that people are increasingly looking online to assess their health, with reasons varying from personal preferences and beliefs to inability to book a timely appointment with their local medical practice. Records of these activities represent a new source of data about the health of populations, but which is currently unaccounted for by disease surveillance models. This could potentially be useful as evidence of individuals’ perception of bodily changes and self-diagnosis of early symptoms of an emerging disease. We make use of the Experian geodemographic Mosaic dataset in order to extract Type 2 diabetes candidate risk variables and compare their temporal relationships with the search keywords, used to describe early symptoms of the disease on Google. Our results demonstrate that Google Trends can detect early signs of diabetes by monitoring combinations of keywords, associated with searches for hypertension treatment and poor living conditions; Combined search semantics, related to obesity, how to quit smoking and improve living conditions (deprivation) can be also employed, however, may lead to less accurate results.

Item Type:	Journal Article
Divisions:	Faculty of Science, Engineering and Medicine > Science > Computer Science Faculty of Science, Engineering and Medicine > Science > Mathematics
Journal or Publication Title:	Scientific Reports
Publisher:	Nature Publishing Group
ISSN:	2045-2322
Official Date:	10 July 2017
Dates:	Date Event 10 July 2017 Published 31 May 2017 Accepted
Volume:	7
Article Number:	4993
DOI:	10.1038/s41598-017-05091-9
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Open Access (Creative Commons)
Date of first compliant deposit:	21 June 2017
Date of first compliant Open Access:	11 July 2017

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