Please use this identifier to cite or link to this item:
https://www.arca.fiocruz.br/handle/icict/59846
Type
ArticleCopyright
Restricted access
Embargo date
2099-12-31
Collections
Metadata
Show full item record23
CITATIONS
23
Total citations
3
Recent citations
1.51
Field Citation Ratio
0.85
Relative Citation Ratio
THE ASSOCIATION BETWEEN THE GEOGRAPHIC DISTRIBUTION OF TRIATOMA PSEUDOMACULATA AND TRIATOMA WYGODZINSKYI (HEMIPTERA: REDUVIIDAE) WITH ENVIRONMENTAL VARIABLES RECORDED BY REMOTE SENSORS
Triatoma wygodzinskyi
Geographic distribution
Environmental variables
Remote sensing
GIS
Chagas disease
Author
Affilliation
Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Departamento. Entomologia. Rio de Janeiro, Brazil
Centro Regional de Investigaciones Científicas y Transferencia Tecnológica. Anillaco, La Rioja, Argentina
Institut de Recherche pour le Développement. Montpellier, France/IIBISMED. Facultad de Medicina. UMSS. Cochabamba, Bolivia
Fundação Oswaldo Cruz. Centro de Pesquisa René Rachou. Belo Horizonte, MG, Brazil
Centro Regional de Investigaciones Científicas y Transferencia Tecnológica. Anillaco, La Rioja, Argentina
Centro Regional de Investigaciones Científicas y Transferencia Tecnológica. Anillaco, La Rioja, Argentina
Institut de Recherche pour le Développement. Montpellier, France/IIBISMED. Facultad de Medicina. UMSS. Cochabamba, Bolivia
Fundação Oswaldo Cruz. Centro de Pesquisa René Rachou. Belo Horizonte, MG, Brazil
Centro Regional de Investigaciones Científicas y Transferencia Tecnológica. Anillaco, La Rioja, Argentina
Abstract
In this Study, predictive models, of geographic distribution patterns of Triatoma pseudomaculata (Tps) and T. wygodzinskyi (Twy) were carried out. They were based oil biophysical variables estimated from information provided by the satellite remote sensors AVHRR (Advanced Very High Resolution Radiometer) and MODIS (MODerate-resolution Imaging Spectroradiometer). Our goal was to analyze the potential geographic distribution of Tps and Twy and to assess the performance of three predictive models (one for each species and one for both species together) based oil temperature, vapour pressure deficit. vegetation and altitude. The geographic distribution analysis shows that all models performed well (>85.7% of overall correct classification of presence and absence point data). The MODIS-based models showed lower correct classifications than the AVHRR-based models. The results strongly suggest that environmental information provided by remote sensors call be successfully used in studies oil the geographic distribution of poorly understood Chagas disease vector species.
Keywords
Triatoma pseudomaculataTriatoma wygodzinskyi
Geographic distribution
Environmental variables
Remote sensing
GIS
Chagas disease
Share