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Anopheles fauna of coastal Cayenne, French Guiana: modelling and mapping of species presence using remotely sensed land cover data

Little is known about the Anopheles species of the coastal areas of French Guiana, or their spatiotemporal distribution or environmental determinants. The present study aimed to (1) document the distribution of Anopheles fauna in the coastal area around Cayenne, and (2) investigate the use of remote...

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Detalles Bibliográficos
Autores principales: Adde, Antoine, Dusfour, Isabelle, Roux, Emmanuel, Girod, Romain, Briolant, Sébastien
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Instituto Oswaldo Cruz, Ministério da Saúde 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5146740/
https://www.ncbi.nlm.nih.gov/pubmed/27982304
http://dx.doi.org/10.1590/0074-02760160272
Descripción
Sumario:Little is known about the Anopheles species of the coastal areas of French Guiana, or their spatiotemporal distribution or environmental determinants. The present study aimed to (1) document the distribution of Anopheles fauna in the coastal area around Cayenne, and (2) investigate the use of remotely sensed land cover data as proxies of Anopheles presence. To characterise the Anopheles fauna, we combined the findings of two entomological surveys that were conducted during the period 2007-2009 and in 2014 at 37 sites. Satellite imagery data were processed to extract land cover variables potentially related to Anopheles ecology. Based on these data, a methodology was formed to estimate a statistical predictive model of the spatial-seasonal variations in the presence of Anopheles in the Cayenne region. Two Anopheles species, known as main malaria vectors in South America, were identified, including the more dominant An. aquasalis near town and rural sites, and An. darlingi only found in inland sites. Furthermore, a cross-validated model of An. aquasalis presence that integrated marsh and forest surface area was extrapolated to generate predictive maps. The present study supports the use of satellite imagery by health authorities for the surveillance of malaria vectors and planning of control strategies.