Models for predicting aedes aegypti larval indices based on satellite images and climatic variables

Autores
Estallo, Elizabet Lilia; Lamfri, Mario; Scavuzzo, Carlos Marcelo; Ludueña Almeida, Francisco; Introini, María V.; Zaidenberg, Mario; Almiron, Walter Ricardo
Año de publicación
2008
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Forecasting models were developed for predicting Aedes aegypti larval indices in an endemic area for dengue (cities of Tartagal and Orn, northwestern Argentina), based on the Breteau and House indices and environmental variables considered with and without time lags. Descriptive models were first developed for each city and each index by multiple linear regressions, followed by a regional model including both cities together. Finally, two forecasting regional models (FRM) were developed and evaluated. FRM2 for the Breteau index and House index fit the data significantly better than FRM1. An evaluation of these models showed a higher correlation FRM1 than for FRM2 for the Breteau index (R 0.83 and 0.62 for 3 months; R 0.86 and 0.67 for 45 days) and the House index (R 0.85 and 0.79 for 3 months; R 0.79 and 0.74 for 45 days). Early warning based on these forecasting models can assist health authorities to improve vector control. © 2008 by The American Mosquito Control Association, Inc.
Fil: Estallo, Elizabet Lilia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones Biológicas y Tecnológicas. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Instituto de Investigaciones Biológicas y Tecnológicas; Argentina. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Centro de Investigaciones Entomológicas de Córdoba; Argentina
Fil: Lamfri, Mario. Comision Nacional de Actividades Espaciales; Argentina
Fil: Scavuzzo, Carlos Marcelo. Comision Nacional de Actividades Espaciales; Argentina
Fil: Ludueña Almeida, Francisco. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Centro de Investigaciones Entomológicas de Córdoba; Argentina
Fil: Introini, María V.. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Centro de Investigaciones Entomológicas de Córdoba; Argentina
Fil: Zaidenberg, Mario. Ministerio de Salud. Dirección de Enfermedades Transmisibles Por Vectores. Centro de Referencia de Vectores; Argentina
Fil: Almiron, Walter Ricardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones Biológicas y Tecnológicas. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Instituto de Investigaciones Biológicas y Tecnológicas; Argentina. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Centro de Investigaciones Entomológicas de Córdoba; Argentina
Materia
Aedes Aegypti
Climatic Variables
Forecasting Models
Larval Indices
Remote Sensing
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/62333
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/62333
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Models for predicting aedes aegypti larval indices based on satellite images and climatic variablesEstallo, Elizabet LiliaLamfri, MarioScavuzzo, Carlos MarceloLudueña Almeida, FranciscoIntroini, María V.Zaidenberg, MarioAlmiron, Walter RicardoAedes AegyptiClimatic VariablesForecasting ModelsLarval IndicesRemote Sensinghttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1Forecasting models were developed for predicting Aedes aegypti larval indices in an endemic area for dengue (cities of Tartagal and Orn, northwestern Argentina), based on the Breteau and House indices and environmental variables considered with and without time lags. Descriptive models were first developed for each city and each index by multiple linear regressions, followed by a regional model including both cities together. Finally, two forecasting regional models (FRM) were developed and evaluated. FRM2 for the Breteau index and House index fit the data significantly better than FRM1. An evaluation of these models showed a higher correlation FRM1 than for FRM2 for the Breteau index (R 0.83 and 0.62 for 3 months; R 0.86 and 0.67 for 45 days) and the House index (R 0.85 and 0.79 for 3 months; R 0.79 and 0.74 for 45 days). Early warning based on these forecasting models can assist health authorities to improve vector control. © 2008 by The American Mosquito Control Association, Inc.Fil: Estallo, Elizabet Lilia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones Biológicas y Tecnológicas. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Instituto de Investigaciones Biológicas y Tecnológicas; Argentina. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Centro de Investigaciones Entomológicas de Córdoba; ArgentinaFil: Lamfri, Mario. Comision Nacional de Actividades Espaciales; ArgentinaFil: Scavuzzo, Carlos Marcelo. Comision Nacional de Actividades Espaciales; ArgentinaFil: Ludueña Almeida, Francisco. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Centro de Investigaciones Entomológicas de Córdoba; ArgentinaFil: Introini, María V.. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Centro de Investigaciones Entomológicas de Córdoba; ArgentinaFil: Zaidenberg, Mario. Ministerio de Salud. Dirección de Enfermedades Transmisibles Por Vectores. Centro de Referencia de Vectores; ArgentinaFil: Almiron, Walter Ricardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones Biológicas y Tecnológicas. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Instituto de Investigaciones Biológicas y Tecnológicas; Argentina. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Centro de Investigaciones Entomológicas de Córdoba; ArgentinaAmerican Mosquito Control Association2008-09info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/62333Estallo, Elizabet Lilia; Lamfri, Mario; Scavuzzo, Carlos Marcelo; Ludueña Almeida, Francisco; Introini, María V.; et al.; Models for predicting aedes aegypti larval indices based on satellite images and climatic variables; American Mosquito Control Association; Journal of the American Mosquito Control Association; 24; 3; 9-2008; 368-3768756-971XCONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://www.bioone.org/doi/abs/10.2987/5705.1info:eu-repo/semantics/altIdentifier/doi/10.2987/5705.1info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-22T11:47:16Zoai:ri.conicet.gov.ar:11336/62333instacron: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:34982025-10-22 11:47:16.392CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Models for predicting aedes aegypti larval indices based on satellite images and climatic variables
title Models for predicting aedes aegypti larval indices based on satellite images and climatic variables
spellingShingle Models for predicting aedes aegypti larval indices based on satellite images and climatic variables
Estallo, Elizabet Lilia
Aedes Aegypti
Climatic Variables
Forecasting Models
Larval Indices
Remote Sensing
title_short Models for predicting aedes aegypti larval indices based on satellite images and climatic variables
title_full Models for predicting aedes aegypti larval indices based on satellite images and climatic variables
title_fullStr Models for predicting aedes aegypti larval indices based on satellite images and climatic variables
title_full_unstemmed Models for predicting aedes aegypti larval indices based on satellite images and climatic variables
title_sort Models for predicting aedes aegypti larval indices based on satellite images and climatic variables
dc.creator.none.fl_str_mv Estallo, Elizabet Lilia
Lamfri, Mario
Scavuzzo, Carlos Marcelo
Ludueña Almeida, Francisco
Introini, María V.
Zaidenberg, Mario
Almiron, Walter Ricardo
author Estallo, Elizabet Lilia
author_facet Estallo, Elizabet Lilia
Lamfri, Mario
Scavuzzo, Carlos Marcelo
Ludueña Almeida, Francisco
Introini, María V.
Zaidenberg, Mario
Almiron, Walter Ricardo
author_role author
author2 Lamfri, Mario
Scavuzzo, Carlos Marcelo
Ludueña Almeida, Francisco
Introini, María V.
Zaidenberg, Mario
Almiron, Walter Ricardo
author2_role author
author
author
author
author
author
dc.subject.none.fl_str_mv Aedes Aegypti
Climatic Variables
Forecasting Models
Larval Indices
Remote Sensing
topic Aedes Aegypti
Climatic Variables
Forecasting Models
Larval Indices
Remote Sensing
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Forecasting models were developed for predicting Aedes aegypti larval indices in an endemic area for dengue (cities of Tartagal and Orn, northwestern Argentina), based on the Breteau and House indices and environmental variables considered with and without time lags. Descriptive models were first developed for each city and each index by multiple linear regressions, followed by a regional model including both cities together. Finally, two forecasting regional models (FRM) were developed and evaluated. FRM2 for the Breteau index and House index fit the data significantly better than FRM1. An evaluation of these models showed a higher correlation FRM1 than for FRM2 for the Breteau index (R 0.83 and 0.62 for 3 months; R 0.86 and 0.67 for 45 days) and the House index (R 0.85 and 0.79 for 3 months; R 0.79 and 0.74 for 45 days). Early warning based on these forecasting models can assist health authorities to improve vector control. © 2008 by The American Mosquito Control Association, Inc.
Fil: Estallo, Elizabet Lilia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones Biológicas y Tecnológicas. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Instituto de Investigaciones Biológicas y Tecnológicas; Argentina. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Centro de Investigaciones Entomológicas de Córdoba; Argentina
Fil: Lamfri, Mario. Comision Nacional de Actividades Espaciales; Argentina
Fil: Scavuzzo, Carlos Marcelo. Comision Nacional de Actividades Espaciales; Argentina
Fil: Ludueña Almeida, Francisco. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Centro de Investigaciones Entomológicas de Córdoba; Argentina
Fil: Introini, María V.. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Centro de Investigaciones Entomológicas de Córdoba; Argentina
Fil: Zaidenberg, Mario. Ministerio de Salud. Dirección de Enfermedades Transmisibles Por Vectores. Centro de Referencia de Vectores; Argentina
Fil: Almiron, Walter Ricardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones Biológicas y Tecnológicas. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Instituto de Investigaciones Biológicas y Tecnológicas; Argentina. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Centro de Investigaciones Entomológicas de Córdoba; Argentina
description Forecasting models were developed for predicting Aedes aegypti larval indices in an endemic area for dengue (cities of Tartagal and Orn, northwestern Argentina), based on the Breteau and House indices and environmental variables considered with and without time lags. Descriptive models were first developed for each city and each index by multiple linear regressions, followed by a regional model including both cities together. Finally, two forecasting regional models (FRM) were developed and evaluated. FRM2 for the Breteau index and House index fit the data significantly better than FRM1. An evaluation of these models showed a higher correlation FRM1 than for FRM2 for the Breteau index (R 0.83 and 0.62 for 3 months; R 0.86 and 0.67 for 45 days) and the House index (R 0.85 and 0.79 for 3 months; R 0.79 and 0.74 for 45 days). Early warning based on these forecasting models can assist health authorities to improve vector control. © 2008 by The American Mosquito Control Association, Inc.
publishDate 2008
dc.date.none.fl_str_mv 2008-09
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/11336/62333
Estallo, Elizabet Lilia; Lamfri, Mario; Scavuzzo, Carlos Marcelo; Ludueña Almeida, Francisco; Introini, María V.; et al.; Models for predicting aedes aegypti larval indices based on satellite images and climatic variables; American Mosquito Control Association; Journal of the American Mosquito Control Association; 24; 3; 9-2008; 368-376
8756-971X
CONICET Digital
CONICET
url http://hdl.handle.net/11336/62333
identifier_str_mv Estallo, Elizabet Lilia; Lamfri, Mario; Scavuzzo, Carlos Marcelo; Ludueña Almeida, Francisco; Introini, María V.; et al.; Models for predicting aedes aegypti larval indices based on satellite images and climatic variables; American Mosquito Control Association; Journal of the American Mosquito Control Association; 24; 3; 9-2008; 368-376
8756-971X
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.bioone.org/doi/abs/10.2987/5705.1
info:eu-repo/semantics/altIdentifier/doi/10.2987/5705.1
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv American Mosquito Control Association
publisher.none.fl_str_mv American Mosquito Control Association
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 12.982451

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