title: Evaluating probabilistic dengue risk forecasts from a prototype early warning system for Brazil.
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.
authors.affiliation: Climate Dynamics and Impacts Unit, Institut Català de Ciències del Clima, Barcelona, Spain.
authors.forename: Rachel
authors.identifier: http://orcid.org/0000-0003-3939-7343
authors.initials: R
authors.lastname: Lowe
authors.affiliation: Centro de Previsão de Tempo e Estudos Climáticos, Instituto Nacional de Pesquisas Espaciais, Cachoeira Paulista, Brazil.
authors.forename: Caio As
authors.initials: CA
authors.lastname: Coelho
authors.affiliation: Fundação Oswaldo Cruz, Rio de Janeiro, Brazil.
authors.forename: Christovam
authors.identifier: http://orcid.org/0000-0002-1161-2753
authors.initials: C
authors.lastname: Barcellos
authors.affiliation: Fundação Oswaldo Cruz, Rio de Janeiro, Brazil.
authors.forename: Marilia Sá
authors.initials: MS
authors.lastname: Carvalho
authors.affiliation: Climate Dynamics and Impacts Unit, Institut Català de Ciències del Clima, Barcelona, Spain.|Faculdade de Ciências e Tecnologia, Universidade Estadual Paulista, Presidente Prudente, Brazil.
authors.forename: Rafael De Castro
authors.initials: Rde C
authors.lastname: Catão
authors.affiliation: Coordenação Geral do Programa Nacional de Controle da Dengue, Ministério da Saúde, Brasília, Brazil.
authors.forename: Giovanini E
authors.initials: GE
authors.lastname: Coelho
authors.affiliation: Faculdade de Ceilândia, Universidade de Brasília, Brasília, Brazil.
authors.forename: Walter Massa
authors.initials: WM
authors.lastname: Ramalho
authors.affiliation: Exeter Climate Systems, College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, United Kingdom.
authors.forename: Trevor C
authors.initials: TC
authors.lastname: Bailey
authors.affiliation: Exeter Climate Systems, College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, United Kingdom.
authors.forename: David B
authors.initials: DB
authors.lastname: Stephenson
authors.affiliation: Climate Dynamics and Impacts Unit, Institut Català de Ciències del Clima, Barcelona, Spain.|Institució Catalana de Recerca i Estudis Avançats, Barcelona, Spain.
authors.forename: Xavier
authors.initials: X
authors.lastname: Rodó
mesh_terms: D001938:Brazil / Q000453:epidemiology; D003140:Communicable Disease Control / Q000379:methods; D003715:Dengue / Q000453:epidemiology* / Q000517:prevention & control; D018562:Disease Transmission, Infectious / Q000517:prevention & control; D004812:Epidemiologic Methods; D005544:Forecasting; D015233:Models, Statistical
keywords: climate; dengue; early warning system; epidemiology; evaluation; global health; infectious disease; microbiology; model; none; probabilistic