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Methods, Models, and GIS

Temporal Scaling Behavior of Avian Influenza A (H5N1): The Multifractal Detrended Fluctuation Analysis

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Pages 1221-1240 | Received 01 Dec 2009, Accepted 01 Sep 2010, Published online: 27 Jul 2011
 

Abstract

The highly pathogenic avian influenza A H5N1 has become a serious public health problem, fatal to poultry and humans all over the world. Since its detection in 2003, H5N1 viruses have exhibited considerable capability of transmission from wild birds to humans, spreading from southeastern Asia across Europe and into Africa. Avian influenza has been recognized as a potential pandemic by practitioners and scientists and has become an important research issue in virology, molecular biology, phylogeography, and spatial epidemiology. Although avian influenza has explicit spatial and temporal dimensions, rigorous geographical analysis, particular its temporal process, of the outbreaks is at its initial stage. The purpose of this article is to provide an approach to study the temporal behaviors of avian influenza A (H5N1) over multiple time scales by analyzing the global and continental outbreak time series from December 2003 to March 2009. The detection of long-range correlation and multifractality in the outbreak series provide answers to the following questions: (1) whether previous H5N1 outbreaks are responsible for and have long-term effects on current infections; (2) whether H5N1 outbreaks have special temporal patterns manifested by multiscaling behaviors; and (3) whether H5N1 outbreaks over time are heterogeneous in different parts of the world. Multifractal detrended fluctuation analysis is employed in this study to detect long-range correlation and multifractal scaling behaviors of the H5N1 outbreaks. Experimental results show that H5N1 outbreaks are long-range correlated and multifractal. The temporal patterns are heterogeneous over space. This implies that H5N1 outbreaks behave differently under different ecosystems, poultry farm practices, and public health measures.

La altamente patógena gripe aviar A H5N1 se ha convertido en un grave problema de salud pública, fatídica para las aves y los seres humanos en todo el mundo. Desde su detección en el año 2003, los virus H5N1 han demostrado una considerable capacidad para transmitirse de aves silvestres a seres humanos, extendiéndose desde el sureste de Asia cruzando Europa hasta África. La gripe aviar ha sido reconocida por médicos y científicos como una posible pandemia convirtiéndose en un importante tema de investigación en virología, biología molecular, filogeografía y epidemiología espacial. A pesar de que la gripe aviar tiene claras dimensiones espaciales y temporales, rigurosos análisis geográficos de los brotes (especialmente de su proceso temporal) están en su etapa inicial. El propósito de este artículo es proporcionar un enfoque para estudiar el comportamiento temporal de la gripe aviar A (H5N1) a través de múltiples escalas temporales mediante el análisis cronológico del brote continental y global desde diciembre del 2003 a marzo del 2009. La identificación de una correlación de largo plazo y multifractal en la serie de brotes provee respuestas a las preguntas siguientes: (1) si anteriores brotes de H5N1 son patrones responsables manifestados por comportamientos multiescalares, y (3) si los brotes de H5N1 son con el tiempo heterogéneos en distintas partes del mundo. En este estudio se ha empleado un análisis multifractal de fluctuación estacionaria para detectar una correlación de largo plazo y comportamientos de escala multifractal de los brotes de H5N1. Los resultados experimentales muestran que los brotes de H5N1 son multifractales y están correlacionados a largo plazo. Los patrones temporales son heterogéneos en el espacio. Esto implica que los brotes de H5N1 se comportan de manera distinta en diferentes ecosistemas, prácticas de granjas avícolas y medidas de salud pública.

Acknowledgments

This project was supported by the earmarked grant CUHK 447109 of the Hong Kong Research Grants Council. The authors would like to thank the editor and anonymous reviewers for their useful comments and suggestions, Zhou Yu for discussion, and Wong Wai Fung for assistance in data collection.

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