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A combination of climatic conditions determines major within-season dengue outbreaks in Guangdong Province, China

BACKGROUND: China’s Guangdong Province experienced a major dengue outbreak in 2014. Here we investigate if the weather conditions contributing to the outbreak can be elucidated by multi-scale models. METHODS: A multi-scale modelling framework, parameterized by available weather, vector and human cas...

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Detalles Bibliográficos
Autores principales: Wang, Xia, Tang, Sanyi, Wu, Jianhong, Xiao, Yanni, Cheke, Robert A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6341621/
https://www.ncbi.nlm.nih.gov/pubmed/30665469
http://dx.doi.org/10.1186/s13071-019-3295-0
Descripción
Sumario:BACKGROUND: China’s Guangdong Province experienced a major dengue outbreak in 2014. Here we investigate if the weather conditions contributing to the outbreak can be elucidated by multi-scale models. METHODS: A multi-scale modelling framework, parameterized by available weather, vector and human case data, was used to examine the integrative effect of temperature and precipitation variation on the effective reproduction number (ERN) of dengue fever. RESULTS: With temperature in the range of 25–30 °C, increasing precipitation leads to an increase in the ERN with an average lag of 10 days. With monthly precipitation fixed, the more regular the pattern of rainfall (i.e. higher numbers of rainy days), the larger is the total number of adult mosquitoes. A rainfall distribution peaking in June and July produces a large ERN, beneficial to transmission. Climate conditions conducive to major outbreaks within a season are a combination of relatively high temperature, high precipitation peaking in June and July, and uninterrupted drizzle or regular rainfall. CONCLUSIONS: Evaluating a set of weather conditions favourable to a future major dengue outbreak requires near-future prediction of temperature variation, total rainfall and its peaking times. Such information permits seasonal rapid response management decisions due to the lags between the precipitation events and the realisation of the ERN. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13071-019-3295-0) contains supplementary material, which is available to authorized users.