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
Climate Dynamics and Impacts Unit, Institut Català de Ciències del Clima, Barcelona, Spain.
Centro de Previsão de Tempo e Estudos Climáticos, Instituto Nacional de Pesquisas Espaciais, Cachoeira Paulista, Brazil.
Elife. 2016 Feb 24;5:e11285. doi: 10.7554/eLife.11285.
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.
最近,开发了一种登革热早期预警系统原型,用于在2014年巴西世界杯前三个月对登革热风险进行概率预测。在此,我们利用2014年6月报告的登革热病例来验证该模型,评估巴西所有微区域的分类登革热预测。我们还将预测模型框架与基于先前观察到的登革热发病率季节性平均值的零模型进行比较。在考虑这两种模型预测巴西全境高登革热风险的能力时,预测模型比零模型产生了更多的命中事件和更少的漏报事件,预测模型的命中率为57%,而零模型为33%。这种早期预警模型框架可能不仅在大型活动之前,而且在每年登革热季节高峰之前,对公共卫生服务控制潜在的登革热爆发流行有用。