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| Content Provider | PubMed Central |
|---|---|
| Author | Lowe, Rachel Coelho, Caio As Barcellos, Christovam Carvalho, Marilia Sá Castro, Catão Rafael De Coelho, Giovanini E. Ramalho, Walter Massa Bailey, Trevor C. Stephenson, David B. Xavier, Rodó |
| Editor | Hay, Simon I. |
| Copyright Year | 2016 |
| Abstract | 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. |
| Related Links | http://dx.doi.org/10.7554/elife.11285 |
| Starting Page | 11285 |
| File Format | |
| ISSN | 2050084X |
| e-ISSN | 2050084X |
| Journal | eLife |
| Volume Number | 5 |
| Language | English |
| Publisher | eLife Sciences Publications, Ltd |
| Publisher Date | 2016-02-01 |
| Access Restriction | Open |
| Rights Holder | eLife Sciences Publications, Ltd |
| Subject Keyword | Research in Higher Education |
| Content Type | Text |
| Resource Type | Article |
| Subject | Neuroscience Immunology and Microbiology Medicine Biochemistry, Genetics and Molecular Biology |
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