Infodemiology of systemic lupus erythematous using Google Trends.

Abstract:

:Objective People affected by chronic rheumatic conditions, such as systemic lupus erythematosus (SLE), frequently rely on the Internet and search engines to look for terms related to their disease and its possible causes, symptoms and treatments. 'Infodemiology' and 'infoveillance' are two recent terms created to describe a new developing approach for public health, based on Big Data monitoring and data mining. In this study, we aim to investigate trends of Internet research linked to SLE and symptoms associated with the disease, applying a Big Data monitoring approach. Methods We analysed the large amount of data generated by Google Trends, considering 'lupus', 'relapse' and 'fatigue' in a 10-year web-based research. Google Trends automatically normalized data for the overall number of searches, and presented them as relative search volumes, in order to compare variations of different search terms across regions and periods. The Menn-Kendall test was used to evaluate the overall seasonal trend of each search term and possible correlation between search terms. Results We observed a seasonality for Google search volumes for lupus-related terms. In the Northern hemisphere, relative search volumes for 'lupus' were correlated with 'relapse' (τ = 0.85; p = 0.019) and with fatigue (τ = 0.82; p = 0.003), whereas in the Southern hemisphere we observed a significant correlation between 'fatigue' and 'relapse' (τ = 0.85; p = 0.018). Similarly, a significant correlation between 'fatigue' and 'relapse' (τ = 0.70; p < 0.001) was seen also in the Northern hemisphere. Conclusion Despite the intrinsic limitations of this approach, Internet-acquired data might represent a real-time surveillance tool and an alert for healthcare systems in order to plan the most appropriate resources in specific moments with higher disease burden.

journal_name

Lupus

journal_title

Lupus

authors

Radin M,Sciascia S

doi

10.1177/0961203317691372

subject

Has Abstract

pub_date

2017-07-01 00:00:00

pages

886-889

issue

8

eissn

0961-2033

issn

1477-0962

journal_volume

26

pub_type

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