Operational satellite-based temporal modelling of Aedes population in Argentina

Autores
Espinosa, Manuel; Di Fino, Eliana Marina Alvarez; Abril, Marcelo; Lanfri, Mario; Periago, Maria Victoria; Scavuzzo, Carlos Marcelo
Año de publicación
2018
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
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.
Fil: Espinosa, Manuel. Fundación Mundo Sano; Argentina
Fil: Di Fino, Eliana Marina Alvarez. Fundación Mundo Sano; Argentina. Universidad Nacional de Córdoba; Argentina
Fil: Abril, Marcelo. Fundación Mundo Sano; Argentina
Fil: Lanfri, Mario. Centro Espacial Teófilo Tabanera; Argentina
Fil: Periago, Maria Victoria. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Fundación Mundo Sano; Argentina
Fil: Scavuzzo, Carlos Marcelo. Centro Espacial Teófilo Tabanera; Argentina
Materia
AEDES AEGYPTI
ARGENTINA
DENGUE
MODELLING
REMOTE SENSING
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/103156
Acceder
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network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Operational satellite-based temporal modelling of Aedes population in ArgentinaEspinosa, ManuelDi Fino, Eliana Marina AlvarezAbril, MarceloLanfri, MarioPeriago, Maria VictoriaScavuzzo, Carlos MarceloAEDES AEGYPTIARGENTINADENGUEMODELLINGREMOTE SENSINGhttps://purl.org/becyt/ford/3.3https://purl.org/becyt/ford/3Aedes 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.Fil: Espinosa, Manuel. Fundación Mundo Sano; ArgentinaFil: Di Fino, Eliana Marina Alvarez. Fundación Mundo Sano; Argentina. Universidad Nacional de Córdoba; ArgentinaFil: Abril, Marcelo. Fundación Mundo Sano; ArgentinaFil: Lanfri, Mario. Centro Espacial Teófilo Tabanera; ArgentinaFil: Periago, Maria Victoria. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Fundación Mundo Sano; ArgentinaFil: Scavuzzo, Carlos Marcelo. Centro Espacial Teófilo Tabanera; ArgentinaUniv Naples Federico Ii2018-11info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/103156Espinosa, 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; 247-2581827-1987CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://geospatialhealth.net/index.php/gh/article/view/734info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:42:26Zoai:ri.conicet.gov.ar:11336/103156instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:42:26.421CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Operational satellite-based temporal modelling of Aedes population in Argentina
title Operational satellite-based temporal modelling of Aedes population in Argentina
spellingShingle Operational satellite-based temporal modelling of Aedes population in Argentina
Espinosa, Manuel
AEDES AEGYPTI
ARGENTINA
DENGUE
MODELLING
REMOTE SENSING
title_short Operational satellite-based temporal modelling of Aedes population in Argentina
title_full Operational satellite-based temporal modelling of Aedes population in Argentina
title_fullStr Operational satellite-based temporal modelling of Aedes population in Argentina
title_full_unstemmed Operational satellite-based temporal modelling of Aedes population in Argentina
title_sort Operational satellite-based temporal modelling of Aedes population in Argentina
dc.creator.none.fl_str_mv Espinosa, Manuel
Di Fino, Eliana Marina Alvarez
Abril, Marcelo
Lanfri, Mario
Periago, Maria Victoria
Scavuzzo, Carlos Marcelo
author Espinosa, Manuel
author_facet Espinosa, Manuel
Di Fino, Eliana Marina Alvarez
Abril, Marcelo
Lanfri, Mario
Periago, Maria Victoria
Scavuzzo, Carlos Marcelo
author_role author
author2 Di Fino, Eliana Marina Alvarez
Abril, Marcelo
Lanfri, Mario
Periago, Maria Victoria
Scavuzzo, Carlos Marcelo
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv AEDES AEGYPTI
ARGENTINA
DENGUE
MODELLING
REMOTE SENSING
topic AEDES AEGYPTI
ARGENTINA
DENGUE
MODELLING
REMOTE SENSING
purl_subject.fl_str_mv https://purl.org/becyt/ford/3.3
https://purl.org/becyt/ford/3
dc.description.none.fl_txt_mv 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.
Fil: Espinosa, Manuel. Fundación Mundo Sano; Argentina
Fil: Di Fino, Eliana Marina Alvarez. Fundación Mundo Sano; Argentina. Universidad Nacional de Córdoba; Argentina
Fil: Abril, Marcelo. Fundación Mundo Sano; Argentina
Fil: Lanfri, Mario. Centro Espacial Teófilo Tabanera; Argentina
Fil: Periago, Maria Victoria. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Fundación Mundo Sano; Argentina
Fil: Scavuzzo, Carlos Marcelo. Centro Espacial Teófilo Tabanera; Argentina
description 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.
publishDate 2018
dc.date.none.fl_str_mv 2018-11
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/103156
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
1827-1987
CONICET Digital
CONICET
url http://hdl.handle.net/11336/103156
identifier_str_mv 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
1827-1987
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://geospatialhealth.net/index.php/gh/article/view/734
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Univ Naples Federico Ii
publisher.none.fl_str_mv Univ Naples Federico Ii
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.070432

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