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Evaluating probabilistic dengue risk forecasts from a prototype early warning system for Brazil

Recently, a prototype dengue early warning system was developed to produce probabilistic forecasts of dengue risk three months ahead of the 2014 World Cup in Brazil. Here, we evaluate the categorical dengue forecasts across all microregions in Brazil, using dengue cases reported in June 2014 to vali...

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Autores principales: Lowe, Rachel, Coelho, Caio AS, Barcellos, Christovam, Carvalho, Marilia Sá, Catão, Rafael De Castro, Coelho, Giovanini E, Ramalho, Walter Massa, Bailey, Trevor C, Stephenson, David B, Rodó, Xavier
Formato: Online Artículo Texto
Lenguaje:English
Publicado: eLife Sciences Publications, Ltd 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4775211/
https://www.ncbi.nlm.nih.gov/pubmed/26910315
http://dx.doi.org/10.7554/eLife.11285
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author Lowe, Rachel
Coelho, Caio AS
Barcellos, Christovam
Carvalho, Marilia Sá
Catão, Rafael De Castro
Coelho, Giovanini E
Ramalho, Walter Massa
Bailey, Trevor C
Stephenson, David B
Rodó, Xavier
author_facet Lowe, Rachel
Coelho, Caio AS
Barcellos, Christovam
Carvalho, Marilia Sá
Catão, Rafael De Castro
Coelho, Giovanini E
Ramalho, Walter Massa
Bailey, Trevor C
Stephenson, David B
Rodó, Xavier
author_sort Lowe, Rachel
collection PubMed
description Recently, a prototype dengue early warning system was developed to produce probabilistic forecasts of dengue risk three months ahead of the 2014 World Cup in Brazil. Here, we evaluate the categorical dengue forecasts across all microregions in Brazil, using dengue cases reported in June 2014 to validate the model. We also compare the forecast model framework to a null model, based on seasonal averages of previously observed dengue incidence. When considering the ability of the two models to predict high dengue risk across Brazil, the forecast model produced more hits and fewer missed events than the null model, with a hit rate of 57% for the forecast model compared to 33% for the null model. This early warning model framework may be useful to public health services, not only ahead of mass gatherings, but also before the peak dengue season each year, to control potentially explosive dengue epidemics. DOI: http://dx.doi.org/10.7554/eLife.11285.001
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spelling pubmed-47752112016-03-07 Evaluating probabilistic dengue risk forecasts from a prototype early warning system for Brazil Lowe, Rachel Coelho, Caio AS Barcellos, Christovam Carvalho, Marilia Sá Catão, Rafael De Castro Coelho, Giovanini E Ramalho, Walter Massa Bailey, Trevor C Stephenson, David B Rodó, Xavier eLife Epidemiology and Global Health Recently, a prototype dengue early warning system was developed to produce probabilistic forecasts of dengue risk three months ahead of the 2014 World Cup in Brazil. Here, we evaluate the categorical dengue forecasts across all microregions in Brazil, using dengue cases reported in June 2014 to validate the model. We also compare the forecast model framework to a null model, based on seasonal averages of previously observed dengue incidence. When considering the ability of the two models to predict high dengue risk across Brazil, the forecast model produced more hits and fewer missed events than the null model, with a hit rate of 57% for the forecast model compared to 33% for the null model. This early warning model framework may be useful to public health services, not only ahead of mass gatherings, but also before the peak dengue season each year, to control potentially explosive dengue epidemics. DOI: http://dx.doi.org/10.7554/eLife.11285.001 eLife Sciences Publications, Ltd 2016-02-24 /pmc/articles/PMC4775211/ /pubmed/26910315 http://dx.doi.org/10.7554/eLife.11285 Text en © 2016, Lowe et al http://creativecommons.org/licenses/by/4.0/ This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited.
spellingShingle Epidemiology and Global Health
Lowe, Rachel
Coelho, Caio AS
Barcellos, Christovam
Carvalho, Marilia Sá
Catão, Rafael De Castro
Coelho, Giovanini E
Ramalho, Walter Massa
Bailey, Trevor C
Stephenson, David B
Rodó, Xavier
Evaluating probabilistic dengue risk forecasts from a prototype early warning system for Brazil
title Evaluating probabilistic dengue risk forecasts from a prototype early warning system for Brazil
title_full Evaluating probabilistic dengue risk forecasts from a prototype early warning system for Brazil
title_fullStr Evaluating probabilistic dengue risk forecasts from a prototype early warning system for Brazil
title_full_unstemmed Evaluating probabilistic dengue risk forecasts from a prototype early warning system for Brazil
title_short Evaluating probabilistic dengue risk forecasts from a prototype early warning system for Brazil
title_sort evaluating probabilistic dengue risk forecasts from a prototype early warning system for brazil
topic Epidemiology and Global Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4775211/
https://www.ncbi.nlm.nih.gov/pubmed/26910315
http://dx.doi.org/10.7554/eLife.11285
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