Table of Contents
ISRN Epidemiology
Volume 2013, Article ID 635971, 5 pages
Research Article

Nonlinear Analysis of Guillain Barré Time Series to Elucidate Its Epidemiology

1Neuromuscular Investigation Group, National Institute of Neurology and Neurosurgery, Vedado CP10400, Cuba
2Bioinformatics Group, Center for Cybernetic Applied to Medicine, Havana 11600, Cuba
3Cybernetic Center Applied to Medicine, Havana 11600, Cuba

Received 24 October 2012; Accepted 26 November 2012

Academic Editors: P. E. Cattan, Q. Chen, and R. Pereira

Copyright © 2012 Zurina Lestayo O'Farrill et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The etiology of Guillain Barré Syndrome (GBS) is not fully clarified, and there is a lack of agreement concerning its putative epidemic character. The low incidence rate of this disease is a disadvantage for employing the traditional statistical methods used in the analysis of epidemics. The objective of this paper is to clarify the GBS epidemic behavior applying a nonlinear time series identification approach. The authors obtained one time series of GBS and nine series of classical infectious epidemics (5 national and 4 international). These data were processed with advanced techniques of statistical time series analysis. This paper shows that GBS behaves similar to the other time series of classical epidemic studied. It corresponds to a nonlinear dynamics, with a point attractor. The spectral analysis pointed to an annual periodicity, and preference for the warmest month of the year was found. These results might suggest that Guillain Barré Syndrome has an epidemic behavior. The adequacy of nonlinear methods for analyzing the dynamics of epidemics, particularly those with low incidence rate, such as GBS was revealed.