J Am Med Inform Assoc - Mining local climate data to assess spatiotemporal dengue fever epidemic patterns in French Guiana.

Tópicos

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Resumo

JECTIVE: 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.

Resumo Limpo

jectiv identifi local meteorolog driver dengu fever french guiana appli origin data mine method avail epidemiolog climat data work also assess contribut data mine method understand factor associ dissemin infecti diseas spatiotempor spreadmethod appli contextu sequenti pattern extract techniqu epidemiolog meteorolog data identifi signific climat factor dengu fever investig relev extract pattern earli warn dengu outbreak french guianaresult maximum temperatur minimum relat humid global brillianc cumul rainfal identifi determin dengu outbreak precis interv valu variat quantifi accord epidemiolog context strongest signific correl observ dengu incid meteorolog driver week lagdiscuss demonstr use contextu sequenti pattern better understand determin spatiotempor spread dengu fever french guiana futur work integr addit variabl explor notion neighborhood extract sequenti patternsconclus dengu fever remain major public health issu french guiana develop new method identifi specif characterist becom crucial order better understand control spatiotempor transmiss

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