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

نویسندگان

  • Rachel Lowe
  • Caio As Coelho
  • Christovam Barcellos
  • Marilia Sá Carvalho
  • Rafael De Castro Catão
  • Giovanini E Coelho
  • Walter Massa Ramalho
  • Trevor C Bailey
  • David B Stephenson
  • Xavier Rodó
چکیده

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.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Dengue outlook for the World Cup in Brazil: an early warning model framework driven by real-time seasonal climate forecasts.

BACKGROUND With more than a million spectators expected to travel among 12 different cities in Brazil during the football World Cup, June 12-July 13, 2014, the risk of the mosquito-transmitted disease dengue fever is a concern. We addressed the potential for a dengue epidemic during the tournament, using a probabilistic forecast of dengue risk for the 553 microregions of Brazil, with risk level...

متن کامل

The development of an early warning system for climate-sensitive disease risk with a focus on dengue epidemics in Southeast Brazil.

Previous studies demonstrate statistically significant associations between disease and climate variations, highlighting the potential for developing climate-based epidemic early warning systems. However, limitations include failure to allow for non-climatic confounding factors, limited geographical/temporal resolution, or lack of evaluation of predictive validity. Here, we consider such issues...

متن کامل

Spatio-temporal modelling of climate-sensitive disease risk: Towards an early warning system for dengue in Brazil

This paper considers the potential for using seasonal climate forecasts in developing an early warning system for dengue fever epidemics in Brazil. In the first instance, a generalised linear model (GLM) is used to select climate and other covariates which are both readily available and prove significant in prediction of confirmed monthly dengue cases based on data collected across the whole of...

متن کامل

Evaluation of the traditional and revised world health organization classifications of dengue cases in Brazil

OBJECTIVE Dengue is a worldwide public health problem with approximately 50 million cases reported annually. The World Health Organization proposed a revised classification system in 2008 to more effectively identify the patients who are at increased risk of complications from dengue. Few studies have validated this new classification system in clinical practice. We conducted a cross-sectional ...

متن کامل

Design and Development of Early Warning System for Desertification and Land Degradation

Early warning systems are key components of strategies to reduce risk. This research, by adopting a systematic approach in the management of the risk of desertification and by including previously developed models and systems, offers an integrated efficient structure in terms of early warning for the risk of desertification as a pilot system for semi-arid areas of west Golestan Province in IRAN...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره 5  شماره 

صفحات  -

تاریخ انتشار 2016