Journal Article

Mining local climate data to assess spatiotemporal dengue fever epidemic patterns in French Guiana

Claude Flamand, Mickael Fabregue, Sandra Bringay, Vanessa Ardillon, Philippe Quénel, Jean-Claude Desenclos and Maguelonne Teisseire

in Journal of the American Medical Informatics Association

Volume 21, issue e2, pages e232-e240
Published in print October 2014 | ISSN: 1067-5027
Published online February 2014 | e-ISSN: 1527-974X | DOI:
Mining local climate data to assess spatiotemporal dengue fever epidemic patterns in French Guiana

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Objective To identify local meteorological drivers of dengue fever in French Guiana, we applied an original data mining method to the available epidemiological and climatic data. Through this work, we also assessed the contribution of the data mining method to the understanding of factors associated with the dissemination of infectious diseases and their spatiotemporal spread.

Methods We applied contextual sequential pattern extraction techniques to epidemiological and meteorological data to identify the most significant climatic factors for dengue fever, and we investigated the relevance of the extracted patterns for the early warning of dengue outbreaks in French Guiana.

Results The maximum temperature, minimum relative humidity, global brilliance, and cumulative rainfall were identified as determinants of dengue outbreaks, and the precise intervals of their values and variations were quantified according to the epidemiologic context. The strongest significant correlations were observed between dengue incidence and meteorological drivers after a 4–6-week lag.

Discussion We demonstrated the use of contextual sequential patterns to better understand the determinants of the spatiotemporal spread of dengue fever in French Guiana. Future work should integrate additional variables and explore the notion of neighborhood for extracting sequential patterns.

Conclusions Dengue fever remains a major public health issue in French Guiana. The development of new methods to identify such specific characteristics becomes crucial in order to better understand and control spatiotemporal transmission.

Keywords: Dengue fever; Data Mining; Meteorological factors; Infectious diseases; Epidemiologic surveillance; French Guiana

Journal Article.  5489 words.  Illustrated.

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