Skip to main content

Advertisement

Log in

Assessing seasonal dynamics of Guillain-Barré syndrome with search engine query data

  • Original Article
  • Published:
Neurological Sciences Aims and scope Submit manuscript

Abstract

Background and objective

In previous studies, data deriving from Google Trends showed promising correlation with disease incidence trends assessed with public health control systems. The aim of this work is to use search engine query data to investigate seasonal dynamics in Guillain-Barré syndrome (GBS) in the USA.

Methods

Average Google monthly search volumes for GBS from 2008 to 2017 were analysed for the USA overall and on regional base with generalized estimating equation models. Association with monthly historical temperature variations was tested.

Results

Monthly search volume for GBS displayed the greatest positive anomaly for October, clustering with September and November. Region-wide analysis confirmed this pattern and showed secondary spring (Feb/Apr) subpeaks in Pacific and Midwest. Association of GBS search volume with month-to-month temperature variations showed J-shaped relationship, with the highest peak occurring in months with greatest temperature falls, and subpeak in months with sharpest temperature rises.

Conclusions

This study represents the first approach in investigating digital epidemiology of GBS and establishing possible links with traditional epidemiology. Cold season GBS peak has been observed by some traditional studies; hypothetical pathogenic relationship with infectious antecedents is supported from finding GBS peaks clustering with greatest temperature change. Further studies are needed to compare these findings to traditional public health approaches.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

References

  1. Van den Berg B, Walgaard C, Drenthen J, Fokke C, Jacobs BC, van Doorn PA (2014) Guillain-Barré syndrome: pathogenesis, diagnosis, treatment and prognosis. Nat Rev Neurol 10(8):469–482. https://doi.org/10.1038/nrneurol.2014.121

    Article  CAS  PubMed  Google Scholar 

  2. Wijdicks EF, Klein CJ (2017) Guillain-Barré syndrome. Mayo Clin Proc 92(3):467–479. https://doi.org/10.1016/j.mayocp.2016.12.002

    Article  PubMed  Google Scholar 

  3. Alshekhlee A, Hussain Z, Sultan B, Katirji B (2008) Guillain-Barré syndrome: incidence and mortality rates in US hospitals. Neurology 70(18):1608–1613. https://doi.org/10.1212/01.wnl.0000310983.38724.d4

    Article  PubMed  Google Scholar 

  4. Shui IM, Rett MD, Weintraub E, Marcy M, Amato AA, Sheikh SI, Ho D, Lee GM, Yih WK, Vaccine Safety Datalink Research Team (2012) Guillain-Barré syndrome incidence in a large United States cohort (2000-2009). Neuroepidemiology 39(2):109–115. https://doi.org/10.1159/000339248

    Article  PubMed  Google Scholar 

  5. Webb AJ, Brain SA, Wood R, Rinaldi S, Turner MR (2015) Seasonal variation in Guillain-Barré syndrome: a systematic review, meta-analysis and Oxfordshire cohort study. J Neurol Neurosurg Psychiatry 86(11):1196–1201. https://doi.org/10.1136/jnnp-2014-309056

    Article  PubMed  Google Scholar 

  6. Kwong JC, Vasa PP, Campitelli MA, Hawken S, Wilson K, Rosella LC, Stukel TA, Crowcroft NS, McGeer AJ, Zinman L, Deeks SL (2013) Risk of Guillain-Barré syndrome after seasonal influenza vaccination and influenza health-care encounters: a self-controlled study. Lancet Infect Dis 13(9):769–776. https://doi.org/10.1016/S1473-3099(13)70104-X

    Article  CAS  PubMed  Google Scholar 

  7. Ginsberg J, Mohebbi MH, Patel RS, Brammer L, Smolinski MS, Brilliant L (2009) Detecting influenza epidemics using search engine query data. Nature 457(7232):1012–1014

    Article  CAS  PubMed  Google Scholar 

  8. Dalla Costa G, Giordano A, Romeo M, Sangalli F, Comi G, Martinelli V (2018) Digital epidemiology confirms a latitude gradient of MS in France. Mult Scler Relat Disord 20:129–131. https://doi.org/10.1016/j.msard.2018.01.009

    Article  CAS  PubMed  Google Scholar 

  9. Moccia M, Palladino R, Falco A, Saccà F, Lanzillo R, Brescia Morra V (2016) Google Trends: new evidence for seasonality of multiple sclerosis. J Neurol Neurosurg Psychiatry 87(9):1028–1029. https://doi.org/10.1136/jnnp-2016-313260

    Article  PubMed  Google Scholar 

  10. Sipilä JOT, Soilu-Hänninen M, Ruuskanen JO, Rautava P, Kytö V (2017) Epidemiology of Guillain-Barré syndrome in Finland 2004-2014. J Peripher Nerv Syst 22(4):440–445. https://doi.org/10.1111/jns.12239

    Article  PubMed  PubMed Central  Google Scholar 

  11. Sivadon-Tardy V, Orlikowski D, Rozenberg F, Caudie C, Sharshar T, Lebon P, Annane D, Raphaël JC, Porcher R, Gaillard JL (2006) Guillain-Barré syndrome, greater Paris area. Emerg Infect Dis 12(6):990–993. https://doi.org/10.3201/eid1206.051369

    Article  PubMed  PubMed Central  Google Scholar 

  12. Rees J, Soudain S, Gregson NA, Hughes RAC (1995) Campylobacter jejuni infection and Guillain-Barré syndrome. N Engl J Med 333:1374–1379. https://doi.org/10.1056/NEJM199511233332102

    Article  CAS  PubMed  Google Scholar 

  13. Lehmann HC, Hartung HP, Kieseier BC, Hughes RA (2010) Guillain-Barré syndrome after exposure to influenza virus. Lancet Infect Dis 10(9):643–651. https://doi.org/10.1016/S1473-3099(10)70140-7

    Article  PubMed  Google Scholar 

  14. Olson DR, Konty KJ, Paladini M, Viboud C, Simonsen L (2013) Reassessing Google Flu Trends data for detection of seasonal and pandemic influenza: a comparative epidemiological study at three geographic scales. PLoS Comput Biol 9(10):e1003256. Published online 2013 Oct 17. https://doi.org/10.1371/journal.pcbi.1003256

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Contributions

A.G. and M.V. equally contributed to the conception and design of the study; acquisition, analysis and interpretation of data; and drafting of the article. G.D.C. contributed to the conception and design of the study. F.C., G.C., V.M. and R.F. contributed to the analysis and interpretation of data. All authors contributed to the critical revision of the article.

Corresponding author

Correspondence to Antonino Giordano.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Giordano, A., Vabanesi, M., Dalla Costa, G. et al. Assessing seasonal dynamics of Guillain-Barré syndrome with search engine query data. Neurol Sci 40, 1015–1018 (2019). https://doi.org/10.1007/s10072-019-03757-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10072-019-03757-y

Keywords

Navigation