Spatial pattern evolution of Aedes aegypti breeding sites in an Argentinean city without a dengue vector control programme

Submitted: 1 March 2016
Accepted: 29 July 2016
Published: 21 November 2016
Abstract Views: 3427
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The main objective of this study was to obtain and analyse the space-time dynamics of Aedes aegypti breeding sites in Clorinda City, Formosa Province, Argentina coupled with landscape analysis using the maximum entropy approach in order to generate a dengue vector niche model. In urban areas, without vector control activities, 12 entomologic (larval) samplings were performed during three years (October 2011 to October 2014). The entomologic surveillance area represented 16,511 houses. Predictive models for Aedes distribution were developed using vector breeding abundance data, density analysis, clustering and geoprocessing techniques coupled with Earth observation satellite data. The spatial analysis showed a vector spatial distribution pattern with clusters of high density in the central region of Clorinda with a well-defined high-risk area in the western part of the city. It also showed a differential temporal behaviour among different areas, which could have implications for risk models and control strategies at the urban scale. The niche model obtained for Ae. aegypti, based on only one year of field data, showed that 85.8% of the distribution of breeding sites is explained by the percentage of water supply (48.2%), urban distribution (33.2%), and the percentage of urban coverage (4.4%). The consequences for the development of control strategies are discussed with reference to the results obtained using distribution maps based on environmental variables.

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Manuel O. Espinosa, Fundaciòn Mundo Sano, Buenos Aires

Departamento de Programas y Proyectos

Coordinador de Proyectos

How to Cite

Espinosa, M. O., Polop, F., Rotela, C. H., Abril, M., & Scavuzzo, C. M. (2016). Spatial pattern evolution of Aedes aegypti breeding sites in an Argentinean city without a dengue vector control programme. Geospatial Health, 11(3). https://doi.org/10.4081/gh.2016.471

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