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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...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2016
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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 |
format | Online Article Text |
id | pubmed-4775211 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
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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