Close

1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitemtc-m16c.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP8W/35NLKN5
Repositorysid.inpe.br/mtc-m18@80/2009/07.27.12.41   (restricted access)
Last Update2009:07.27.12.41.01 (UTC) administrator
Metadata Repositorysid.inpe.br/mtc-m18@80/2009/07.27.12.41.03
Metadata Last Update2021:01.02.22.18.20 (UTC) administrator
Secondary KeyINPE--PRE/
Citation KeyLoweBaStGrCoCaBa:2009:ClDePr
TitleClimate-based dengue predictions for Brazil
FormatOn-line
Year2009
Access Date2024, Apr. 28
Secondary TypePRE CI
Number of Files1
Size606 KiB
2. Context
Author1 Lowe, Rachel
2 Bailey, Trevor C.
3 Stephenson, David B.
4 Graham, Richard
5 Coelho, Caio Augusto dos Santos
6 Carvalho, Marilia Sá
7 Barcellos, Christovam
Group1
2
3
4
5 DOP-CPT-INPE-MCT-BR
Affiliation1
2
3
4
5 Instituto Nacional de Pesquisas Espaciais (INPE)
6 Fundação Oswaldo Cruz
e-Mail Addressdeicy.farabello@cptec.inpe.br
Conference NameInternational Conference: GeoInformatics for Environmental Surveillance, (Fourth StatGIS '2009).
Conference LocationMilos island, Greece
Date17-19 jun.
Tertiary TypeSessão Técnica Oral
History (UTC)2009-07-27 12:52:51 :: deicy.farabello -> administrator ::
2021-01-02 22:18:20 :: administrator -> simone :: 2009
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Keywordsdengue transmission
climatic
forecasts
Amazon region
AbstractThe purpose of this study is to assess the potential for using seasonal climate forecasts in an early warning system (EWS) for dengue fever incidence in Brazil. Data at heterogeneous spatial scales were combined in a negative binomial model using dengue fever data at the microregion level for the period January 2001- April 2008, gridded observed climate data with time lags relevant to dengue transmission and other socio-economic and environmental covariates. The same model was then refitted replacing observed climate with seasonal climate forecasts of the same variables issued 5 months previous to the dengue month of interest. Predictions from both models were tested by using the first 7 years as a training dataset to predict the first 4 months of 2008 when a dengue epidemic occurred in Brazil. Both models were able to capture high dengue incidence along the densely populated eastern coast of Brazil and low incidence in the South. The models did not perform so well in the Amazon region. We conclude that seasonal climate forecasts could have potential value in the context of a dengue EWS to predict the climatic conditions that may influence dengue incidence up to 5 months ahead of an epidemic in Brazil.
AreaMET
Arrangementurlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDOP > Climate-based dengue predictions...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Contentthere are no files
4. Conditions of access and use
Languageen
Target FileSTATGIS09-Rachel-Lowe-finalversion-140509.pdf
User Groupadministrator
deicy.farabello
administrator
Visibilityshown
Read Permissiondeny from all and allow from 150.163
5. Allied materials
Mirror Repositorysid.inpe.br/mtc-m18@80/2008/03.17.15.17.24
Next Higher Units8JMKD3MGPCW/43SQKNE
Host Collectionsid.inpe.br/mtc-m18@80/2008/03.17.15.17
6. Notes
Empty Fieldsarchivingpolicy archivist booktitle callnumber copyholder copyright creatorhistory descriptionlevel dissemination documentstage doi edition editor electronicmailaddress isbn issn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project publisher publisheraddress readergroup resumeid rightsholder schedulinginformation secondarydate secondarymark serieseditor session shorttitle sponsor subject tertiarymark type url versiontype volume
7. Description control
e-Mail (login)simone
update 


Close