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dc.contributor.author
Espinosa, Manuel  
dc.contributor.author
Di Fino, Eliana Marina Alvarez  
dc.contributor.author
Abril, Marcelo  
dc.contributor.author
Lanfri, Mario  
dc.contributor.author
Periago, Maria Victoria  
dc.contributor.author
Scavuzzo, Carlos Marcelo  
dc.date.available
2020-04-21T15:55:52Z  
dc.date.issued
2018-11  
dc.identifier.citation
Espinosa, Manuel; Di Fino, Eliana Marina Alvarez; Abril, Marcelo; Lanfri, Mario; Periago, Maria Victoria; et al.; Operational satellite-based temporal modelling of Aedes population in Argentina; Univ Naples Federico Ii; Geospatial Health; 13; 2; 11-2018; 247-258  
dc.identifier.issn
1827-1987  
dc.identifier.uri
http://hdl.handle.net/11336/103156  
dc.description.abstract
Aedes aegypti is a vector for Chikungunya, Dengue and Zika viruses in Latin America and is therefore a large public health problem for the region. For this reason, several inter-institutional and multidisciplinary efforts have been made to support vector control actions through the use of geospatial technologies. This study presents the development of an operational system for the application of free access to remotely sensed products capable of assessing the oviposition activity of Ae. aegypti in all of Argentina?s northern region with the specific aim to improve the current Argentine National Dengue risk system. Temporal modelling implemented includes remotely sensed variables like the normalized difference vegetation index, the normalized difference water index, day and night land surface temperature and precipitation data available from NASA?s tropical rainfall measuring mission and global precipitation measurement. As a training data set, four years of weekly mosquito oviposition data from four different cities in Argentina were used. A series of satellite-generated variables was built, downloading and resampling the these products both spatially and temporally. From an initial set of 41 variables chosen based on the correlation between these products and the oviposition series, a subset of 11 variables were preserved to develop temporal forecasting models of oviposition using a lineal multivariate method in the four cities. Subsequently, a general model was generated using data from the cities. Finally, in order to obtain a model that could be broadly used, an extrapolation method using the concept of environmental distance was developed. Although the system was oriented towards the surveillance of dengue fever, the methodology could also be applied to other relevant vector-borne diseases as well as other geographical regions in Latin America.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
Univ Naples Federico Ii  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc/2.5/ar/  
dc.subject
AEDES AEGYPTI  
dc.subject
ARGENTINA  
dc.subject
DENGUE  
dc.subject
MODELLING  
dc.subject
REMOTE SENSING  
dc.subject.classification
Epidemiología  
dc.subject.classification
Ciencias de la Salud  
dc.subject.classification
CIENCIAS MÉDICAS Y DE LA SALUD  
dc.title
Operational satellite-based temporal modelling of Aedes population in Argentina  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2020-02-18T16:03:41Z  
dc.journal.volume
13  
dc.journal.number
2  
dc.journal.pagination
247-258  
dc.journal.pais
Estados Unidos  
dc.description.fil
Fil: Espinosa, Manuel. Fundación Mundo Sano; Argentina  
dc.description.fil
Fil: Di Fino, Eliana Marina Alvarez. Fundación Mundo Sano; Argentina. Universidad Nacional de Córdoba; Argentina  
dc.description.fil
Fil: Abril, Marcelo. Fundación Mundo Sano; Argentina  
dc.description.fil
Fil: Lanfri, Mario. Centro Espacial Teófilo Tabanera; Argentina  
dc.description.fil
Fil: Periago, Maria Victoria. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Fundación Mundo Sano; Argentina  
dc.description.fil
Fil: Scavuzzo, Carlos Marcelo. Centro Espacial Teófilo Tabanera; Argentina  
dc.journal.title
Geospatial Health  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://geospatialhealth.net/index.php/gh/article/view/734