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Spatiotemporal Modeling of Aedes aegypti Risk: Enhancing Dengue Virus Control through Meteorological and Remote Sensing Data in French Guiana.
Bailly, Sarah; Machault, Vanessa; Beneteau, Samuel; Palany, Philippe; Fritzell, Camille; Girod, Romain; Lacaux, Jean-Pierre; Quénel, Philippe; Flamand, Claude.
Affiliation
  • Bailly S; Epidemiology Unit, Institut Pasteur in French Guiana, Cayenne 97306, French Guiana.
  • Machault V; Aerology Laboratory, Observatoire Midi-Pyrénées (OMP), Université Paul Sabatier, 31062 Toulouse, France.
  • Beneteau S; Epidemiology Unit, Institut Pasteur in French Guiana, Cayenne 97306, French Guiana.
  • Palany P; Météo-France, Direction Antilles-Guyane, Fort-de-France 97262, Martinique.
  • Fritzell C; Epidemiology Unit, Institut Pasteur in French Guiana, Cayenne 97306, French Guiana.
  • Girod R; Medical Entomology Unit, Institut Pasteur in French Guiana, Cayenne 97306, French Guiana.
  • Lacaux JP; Aerology Laboratory, Observatoire Midi-Pyrénées (OMP), Université Paul Sabatier, 31062 Toulouse, France.
  • Quénel P; Epidemiology Unit, Institut Pasteur in French Guiana, Cayenne 97306, French Guiana.
  • Flamand C; University Rennes, Inserm, EHESP, Irset (Institut de Recherche En Santé, Environnement et Travail)-UMR-S 1085, 35000 Rennes, France.
Pathogens ; 13(9)2024 Aug 29.
Article in En | MEDLINE | ID: mdl-39338929
ABSTRACT
French Guiana lacks a dedicated model for developing an early warning system tailored to its entomological contexts. We employed a spatiotemporal modeling approach to predict the risk of Aedes aegypti larvae presence in local households in French Guiana. The model integrated field data on larvae, environmental data obtained from very high-spatial-resolution Pleiades imagery, and meteorological data collected from September 2011 to February 2013 in an urban area of French Guiana. The identified environmental and meteorological factors were used to generate dynamic maps with high spatial and temporal resolution. The study collected larval data from 261 different surveyed houses, with each house being surveyed between one and three times. Of the observations, 41% were positive for the presence of Aedes aegypti larvae. We modeled the Aedes larvae risk within a radius of 50 to 200 m around houses using six explanatory variables and extrapolated the findings to other urban municipalities during the 2020 dengue epidemic in French Guiana. This study highlights the potential of spatiotemporal modeling approaches to predict and monitor the evolution of vector-borne disease transmission risk, representing a major opportunity to monitor the evolution of vector risk and provide valuable information for public health authorities.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Country/Region as subject: America do sul / Caribe ingles / Guyana Language: En Journal: Pathogens Year: 2024 Document type: Article Affiliation country: French Guiana Country of publication: Switzerland

Full text: 1 Collection: 01-internacional Database: MEDLINE Country/Region as subject: America do sul / Caribe ingles / Guyana Language: En Journal: Pathogens Year: 2024 Document type: Article Affiliation country: French Guiana Country of publication: Switzerland