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1. Identificação
Tipo de ReferênciaArtigo em Revista Científica (Journal Article)
Sitemtc-m21b.sid.inpe.br
Código do Detentorisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identificador8JMKD3MGP5W34M/3HE6FDM
Repositóriosid.inpe.br/mtc-m21b/2014/11.18.23.58.31   (acesso restrito)
Última Atualização2014:12.16.13.01.17 (UTC) administrator
Repositório de Metadadossid.inpe.br/mtc-m21b/2014/11.18.23.58.32
Última Atualização dos Metadados2021:01.02.22.17.08 (UTC) administrator
DOI10.1016/S1473-3099(14)70781-9
ISSN1473-3099
Rótuloscopus 2014-11 LoweBCBCGJRCSR:2014:EaWaMo
Chave de CitaçãoLoweBCBCGJRCSR:2014:EaWaMo
TítuloDengue outlook for the World Cup in Brazil: An early warning model framework driven by real-time seasonal climate forecasts
Ano2014
MêsJuly
Data de Acesso11 maio 2024
Tipo de Trabalhojournal article
Tipo SecundárioPRE PI
Número de Arquivos1
Tamanho2764 KiB
2. Contextualização
Autor 1 Lowe, R.
 2 Barcellos, C.
 3 Coelho, Caio Augusto dos Santos
 4 Bailey, T. C.
 5 Coelho, G. E.
 6 Graham, R.
 7 Jupp, T.
 8 Ramalho, W. M.
 9 Carvalho, M. S.
10 Stephenson, D. B.
11 Rodó, X.
Grupo 1
 2
 3 DOP-CPT-INPE-MCTI-GOV-BR
Afiliação 1 Climate Dynamics and Impacts Unit, Institut Català de Ciències del Clima (IC3), Barcelona, Spain
 2 Fundação Oswaldo Cruz (FIOCRUZ), Rio de Janeiro, RJ, Brazil
 3 Instituto Nacional de Pesquisas Espaciais (INPE)
 4 Exeter Climate Systems, College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, United Kingdom
 5 Coordenação Geral do Programa Nacional de Controle da Dengue, Ministério da Saúde, Brasília, DF, Brazil
 6 Met Office Hadley Centre, Exeter, Devon, United Kingdom
 7 Exeter Climate Systems, College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, United Kingdom
 8 Faculdade de Ceilândia, Universidade de Brasília, Brasília, DF, Brazil
 9 Fundação Oswaldo Cruz (FIOCRUZ), Rio de Janeiro, RJ, Brazil
10 Exeter Climate Systems, College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, United Kingdom
11 Climate Dynamics and Impacts Unit, Institut Català de Ciències del Clima (IC3), Barcelona, Spain; Institució Catalana de Recerca i Estudis Avançats, Barcelona, Spain
Endereço de e-Mailmarcelo.pazos@inpe.br
RevistaLancet Infectious Diseases
Volume14
Número7
Páginas619-626
Nota SecundáriaA1_MEDICINA_II A1_CIÊNCIAS_BIOLÓGICAS_III A1_SAÚDE_COLETIVA A1_CIÊNCIAS_BIOLÓGICAS_II A1_MEDICINA_I
Histórico (UTC)2021-01-02 22:17:08 :: administrator -> marciana :: 2014
3. Conteúdo e estrutura
É a matriz ou uma cópia?é a matriz
Estágio do Conteúdoconcluido
Transferível1
Tipo do ConteúdoExternal Contribution
Tipo de Versãopublisher
Palavras-Chavealertness
article
Brazil
climate change
conceptual framework
dengue
disease transmission
epidemic
epidemiological monitoring
forecasting
high risk population
human
incidence
information processing
population density
priority journal
real time seasonal climate forecast
risk assessment
risk factor
seasonal variation
spatiotemporal analysis
Bayes Theorem
Brazil
Climate
Dengue
Forecasting
Humans
Risk
Seasons
Soccer
ResumoBackground: With more than a million spectators expected to travel among 12 different cities in Brazil during the football World Cup, June 12-July 13, 2014, the risk of the mosquito-transmitted disease dengue fever is a concern. We addressed the potential for a dengue epidemic during the tournament, using a probabilistic forecast of dengue risk for the 553 microregions of Brazil, with risk level warnings for the 12 cities where matches will be played. Methods: We obtained real-time seasonal climate forecasts from several international sources (European Centre for Medium-Range Weather Forecasts [ECMWF], Met Office, Meteo-France and Centro de Previsão de Tempo e Estudos Climáticos [CPTEC]) and the observed dengue epidemiological situation in Brazil at the forecast issue date as provided by the Ministry of Health. Using this information we devised a spatiotemporal hierarchical Bayesian modelling framework that enabled dengue warnings to be made 3 months ahead. By assessing the past performance of the forecasting system using observed dengue incidence rates for June, 2000-2013, we identified optimum trigger alert thresholds for scenarios of medium-risk and high-risk of dengue. Findings: Our forecasts for June, 2014, showed that dengue risk was likely to be low in the host cities Brasília, Cuiabá, Curitiba, Porto Alegre, and São Paulo. The risk was medium in Rio de Janeiro, Belo Horizonte, Salvador, and Manaus. High-risk alerts were triggered for the northeastern cities of Recife (phigh = 19%), Fortaleza (phigh = 46%), and Natal (phigh=48%). For these high-risk areas, particularly Natal, the forecasting system did well for previous years (in June, 2000-13). Interpretation: This timely dengue early warning permits the Ministry of Health and local authorities to implement appropriate, city-specific mitigation and control actions ahead of the World Cup. Funding: European Commission's Seventh Framework Research Programme projects DENFREE, EUPORIAS, and SPECS; Conselho Nacional de Desenvolvimento Científico e Tecnológico and Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro. © 2014 Elsevier Ltd.
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5. Fontes relacionadas
VinculaçãoTrabalho não Vinculado à Tese/Dissertação
Repositório Espelhoiconet.com.br/banon/2006/11.26.21.31
Unidades Imediatamente Superiores8JMKD3MGPCW/43SQKNE
Lista de Itens Citando
DivulgaçãoWEBSCI; SCOPUS.
Acervo Hospedeirosid.inpe.br/mtc-m21b/2013/09.26.14.25.20
6. Notas
Campos Vaziosalternatejournal archivingpolicy archivist callnumber copyholder copyright creatorhistory descriptionlevel electronicmailaddress format isbn lineage mark nextedition notes orcid parameterlist parentrepositories previousedition previouslowerunit progress project resumeid rightsholder schedulinginformation secondarydate secondarykey session shorttitle sponsor subject targetfile tertiarytype url
7. Controle da descrição
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