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

Rachel Lowe ORCID logo; Caio As Coelho; Christovam Barcellos ORCID logo; Marilia Sá Carvalho; Rafael De Castro Catão; Giovanini E Coelho; Walter Massa Ramalho; Trevor C Bailey; David B Stephenson; Xavier Rodó; (2016) Evaluating probabilistic dengue risk forecasts from a prototype early warning system for Brazil. eLife, 5 (FEBRUA). ISSN 2050-084X DOI: 10.7554/eLife.11285
Copy

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.


picture_as_pdf
Evaluating probabilities in Brazil_GOLD VoR.pdf
subject
Published Version
Available under Creative Commons: 3.0

View Download
picture_as_pdf

Published Version


Atom BibTeX OpenURL ContextObject in Span Multiline CSV OpenURL ContextObject Dublin Core Dublin Core MPEG-21 DIDL EndNote HTML Citation JSON MARC (ASCII) MARC (ISO 2709) METS MODS RDF+N3 RDF+N-Triples RDF+XML RIOXX2 XML Reference Manager Refer Simple Metadata ASCII Citation EP3 XML
Export

Downloads