Document Detail

Time-dependent spectral analysis of epidemiological time-series with wavelets.
MedLine Citation:
PMID:  17301013     Owner:  NLM     Status:  MEDLINE    
In the current context of global infectious disease risks, a better understanding of the dynamics of major epidemics is urgently needed. Time-series analysis has appeared as an interesting approach to explore the dynamics of numerous diseases. Classical time-series methods can only be used for stationary time-series (in which the statistical properties do not vary with time). However, epidemiological time-series are typically noisy, complex and strongly non-stationary. Given this specific nature, wavelet analysis appears particularly attractive because it is well suited to the analysis of non-stationary signals. Here, we review the basic properties of the wavelet approach as an appropriate and elegant method for time-series analysis in epidemiological studies. The wavelet decomposition offers several advantages that are discussed in this paper based on epidemiological examples. In particular, the wavelet approach permits analysis of transient relationships between two signals and is especially suitable for gradual change in force by exogenous variables.
Bernard Cazelles; Mario Chavez; Guillaume Constantin de Magny; Jean-Francois Guégan; Simon Hales
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Publication Detail:
Type:  Journal Article; Review    
Journal Detail:
Title:  Journal of the Royal Society, Interface / the Royal Society     Volume:  4     ISSN:  1742-5689     ISO Abbreviation:  J R Soc Interface     Publication Date:  2007 Aug 
Date Detail:
Created Date:  2007-07-03     Completed Date:  2007-09-06     Revised Date:  2013-06-06    
Medline Journal Info:
Nlm Unique ID:  101217269     Medline TA:  J R Soc Interface     Country:  England    
Other Details:
Languages:  eng     Pagination:  625-36     Citation Subset:  IM    
CNRS UMR 7625, Ecole Normale Supérieure, 46 rue d'Ulm, 75230 Paris, France IRD UR GEODES, 93143 Bondy, France.
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MeSH Terms
Epidemiologic Studies*
Models, Statistical*

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