Dynamic mapping of the probability of infestation by arbovirus urban vectors in the municipalities of Rio Grande do Sul state, Brazil, 2016-2017

Detalhes bibliográficos
Autor(a) principal: Luza, André Luís
Data de Publicação: 2021
Outros Autores: Gualdi, Carolina Brandt, Diefenbach, Lúcia Maria Lopes de Almeida Guedes, Schüler-Faccini, Lavinia, Ferraz, Gonçalo
Tipo de documento: preprint
Idioma: por
Título da fonte: SciELO Preprints
Texto Completo: https://preprints.scielo.org/index.php/scielo/preprint/view/1637
Resumo: Objective: To compare the official mapping with the probabilistic mapping of infestation by Aedes spp. in Rio Grande do Sul municipalities, Brazil. Methods: Ecological study analyzing samples of mosquito breeding sites collected in 2016-2017; official classification was obtained from epidemiological reports, and infestation per municipality and week was estimated by fitting a dynamic site-occupancy model to data from municipal epidemiological surveillance. Results: 187,245 samples collected in 473 municipalities returned 10,648 detections of Aedes aegypti, and 8,414 detections of Aedes albopictus.; official mapping agrees with the probabilistic mapping in municipalities from northwestern and western regions. These mappings disagree in eastern, center, northeastern and southern regions, revealing municipalities not officially infested with high infestation probability and notification of arbovirus. Conclusion: While official classification correctly identifies critically infested municipalities from northwestern and western regions, it did not identify infestation in municipalities with false negative errors and where infestation varies over time.
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spelling Dynamic mapping of the probability of infestation by arbovirus urban vectors in the municipalities of Rio Grande do Sul state, Brazil, 2016-2017Mapeo dinámico de la probabilidad de infestación por vectores urbanos de arbovirus en los municipios de Rio Grande do Sul, Brasil, 2016-2017Mapeamento dinâmico da probabilidade de infestação por vetores urbanos de arbovírus nos municípios do Rio Grande do Sul, 2016-2017AedesEstudos EcológicosModelos TeóricosVetores de DoençasVigilância EpidemiológicaAedesDisease VectorsEcological StudiesEpidemiological SurveillanceTheoretical ModelsObjective: To compare the official mapping with the probabilistic mapping of infestation by Aedes spp. in Rio Grande do Sul municipalities, Brazil. Methods: Ecological study analyzing samples of mosquito breeding sites collected in 2016-2017; official classification was obtained from epidemiological reports, and infestation per municipality and week was estimated by fitting a dynamic site-occupancy model to data from municipal epidemiological surveillance. Results: 187,245 samples collected in 473 municipalities returned 10,648 detections of Aedes aegypti, and 8,414 detections of Aedes albopictus.; official mapping agrees with the probabilistic mapping in municipalities from northwestern and western regions. These mappings disagree in eastern, center, northeastern and southern regions, revealing municipalities not officially infested with high infestation probability and notification of arbovirus. Conclusion: While official classification correctly identifies critically infested municipalities from northwestern and western regions, it did not identify infestation in municipalities with false negative errors and where infestation varies over time.Objetivo: Comparar o mapeamento oficial com um mapeamento probabilístico da infestação por Aedes spp. nos municípios do Rio Grande do Sul, Brasil. Métodos: Estudo ecológico com dados de amostras de criadouros em 2016-2017; obteve-se a classificação oficial em boletins epidemiológicos e estimou-se a probabilidade de infestação por município e semana, ajustando-se um modelo dinâmico de ocupação de sítios aos dados da vigilância epidemiológica municipal. Resultados: 187.245 amostras coletadas em 473 municípios originaram 10.648 detecções de Aedes aegypti e 8.414 de Aedes albopictus; o mapeamento oficial concorda com o probabilístico em municípios da região noroeste e oeste do RS; os mapeamentos discordam nas regiões leste, centro, nordeste e sul, revelando municípios oficialmente não infestados com alta probabilidade de infestação e notificação de arboviroses. Conclusão: A classificação oficial identificou infestação nos municípios infestados do noroeste e oeste; e não identificou infestação em municípios com possíveis falsos zeros e onde ela varia temporalmente.SciELO PreprintsSciELO PreprintsSciELO Preprints2021-01-07info:eu-repo/semantics/preprintinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://preprints.scielo.org/index.php/scielo/preprint/view/163710.1590/S1679-49742021000200006porhttps://preprints.scielo.org/index.php/scielo/article/view/1637/2603Copyright (c) 2021 André Luís Luza, Carolina Brandt Gualdi, Lúcia Maria Lopes de Almeida Guedes Diefenbach, Lavinia Schüler-Faccini, Gonçalo Ferrazhttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessLuza, André Luís Gualdi, Carolina Brandt Diefenbach, Lúcia Maria Lopes de Almeida Guedes Schüler-Faccini, Lavinia Ferraz, Gonçalo reponame:SciELO Preprintsinstname:SciELOinstacron:SCI2020-12-18T18:42:26Zoai:ops.preprints.scielo.org:preprint/1637Servidor de preprintshttps://preprints.scielo.org/index.php/scieloONGhttps://preprints.scielo.org/index.php/scielo/oaiscielo.submission@scielo.orgopendoar:2020-12-18T18:42:26SciELO Preprints - SciELOfalse
dc.title.none.fl_str_mv Dynamic mapping of the probability of infestation by arbovirus urban vectors in the municipalities of Rio Grande do Sul state, Brazil, 2016-2017
Mapeo dinámico de la probabilidad de infestación por vectores urbanos de arbovirus en los municipios de Rio Grande do Sul, Brasil, 2016-2017
Mapeamento dinâmico da probabilidade de infestação por vetores urbanos de arbovírus nos municípios do Rio Grande do Sul, 2016-2017
title Dynamic mapping of the probability of infestation by arbovirus urban vectors in the municipalities of Rio Grande do Sul state, Brazil, 2016-2017
spellingShingle Dynamic mapping of the probability of infestation by arbovirus urban vectors in the municipalities of Rio Grande do Sul state, Brazil, 2016-2017
Luza, André Luís
Aedes
Estudos Ecológicos
Modelos Teóricos
Vetores de Doenças
Vigilância Epidemiológica
Aedes
Disease Vectors
Ecological Studies
Epidemiological Surveillance
Theoretical Models
title_short Dynamic mapping of the probability of infestation by arbovirus urban vectors in the municipalities of Rio Grande do Sul state, Brazil, 2016-2017
title_full Dynamic mapping of the probability of infestation by arbovirus urban vectors in the municipalities of Rio Grande do Sul state, Brazil, 2016-2017
title_fullStr Dynamic mapping of the probability of infestation by arbovirus urban vectors in the municipalities of Rio Grande do Sul state, Brazil, 2016-2017
title_full_unstemmed Dynamic mapping of the probability of infestation by arbovirus urban vectors in the municipalities of Rio Grande do Sul state, Brazil, 2016-2017
title_sort Dynamic mapping of the probability of infestation by arbovirus urban vectors in the municipalities of Rio Grande do Sul state, Brazil, 2016-2017
author Luza, André Luís
author_facet Luza, André Luís
Gualdi, Carolina Brandt
Diefenbach, Lúcia Maria Lopes de Almeida Guedes
Schüler-Faccini, Lavinia
Ferraz, Gonçalo
author_role author
author2 Gualdi, Carolina Brandt
Diefenbach, Lúcia Maria Lopes de Almeida Guedes
Schüler-Faccini, Lavinia
Ferraz, Gonçalo
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Luza, André Luís
Gualdi, Carolina Brandt
Diefenbach, Lúcia Maria Lopes de Almeida Guedes
Schüler-Faccini, Lavinia
Ferraz, Gonçalo
dc.subject.por.fl_str_mv Aedes
Estudos Ecológicos
Modelos Teóricos
Vetores de Doenças
Vigilância Epidemiológica
Aedes
Disease Vectors
Ecological Studies
Epidemiological Surveillance
Theoretical Models
topic Aedes
Estudos Ecológicos
Modelos Teóricos
Vetores de Doenças
Vigilância Epidemiológica
Aedes
Disease Vectors
Ecological Studies
Epidemiological Surveillance
Theoretical Models
description Objective: To compare the official mapping with the probabilistic mapping of infestation by Aedes spp. in Rio Grande do Sul municipalities, Brazil. Methods: Ecological study analyzing samples of mosquito breeding sites collected in 2016-2017; official classification was obtained from epidemiological reports, and infestation per municipality and week was estimated by fitting a dynamic site-occupancy model to data from municipal epidemiological surveillance. Results: 187,245 samples collected in 473 municipalities returned 10,648 detections of Aedes aegypti, and 8,414 detections of Aedes albopictus.; official mapping agrees with the probabilistic mapping in municipalities from northwestern and western regions. These mappings disagree in eastern, center, northeastern and southern regions, revealing municipalities not officially infested with high infestation probability and notification of arbovirus. Conclusion: While official classification correctly identifies critically infested municipalities from northwestern and western regions, it did not identify infestation in municipalities with false negative errors and where infestation varies over time.
publishDate 2021
dc.date.none.fl_str_mv 2021-01-07
dc.type.driver.fl_str_mv info:eu-repo/semantics/preprint
info:eu-repo/semantics/publishedVersion
format preprint
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://preprints.scielo.org/index.php/scielo/preprint/view/1637
10.1590/S1679-49742021000200006
url https://preprints.scielo.org/index.php/scielo/preprint/view/1637
identifier_str_mv 10.1590/S1679-49742021000200006
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://preprints.scielo.org/index.php/scielo/article/view/1637/2603
dc.rights.driver.fl_str_mv https://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv SciELO Preprints
SciELO Preprints
SciELO Preprints
publisher.none.fl_str_mv SciELO Preprints
SciELO Preprints
SciELO Preprints
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repository.mail.fl_str_mv scielo.submission@scielo.org
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