author = "Lowe, Rachel and Carvalho, Marilia S{\'a} and Coelho, Caio 
                         Augusto dos Santos and Barcellos, Christovam and Bailey, Trevor C. 
                         and Stephenson, David B. and Rod{\'o}, Xavier",
          affiliation = "{Institut Catal{\`a} de Ci{\'e}ncies del Clima} and 
                         {Funda{\c{c}}{\~a}o Oswaldo Cruz (FIOCRUZ)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Funda{\c{c}}{\~a}o 
                         Oswaldo Cruz (FIOCRUZ)} and {Instituci{\'o} Catalana de Recerca i 
                         Estudis Avan{\c{c}}ats} and {} and {Institut Catal{\`a} de 
                         Ci{\'e}ncies del Clima}",
                title = "Interpretation of probabilistic forecasts of epidemics",
              journal = "The Lancet",
                 year = "2015",
               volume = "15",
               number = "1",
                pages = "20",
             keywords = "Forecasts.",
             abstract = "We are grateful to Eduardo Massad and colleagues1 for discussing 
                         the results of our study2 that addressed the potential for a 
                         dengue epidemic during the World Cup in Brazil. We believe our 
                         results are not comparable to point estimates obtained using 
                         deterministic models; however, we welcome the opportunity to 
                         discuss and clarify the interpretation of probabilistic forecasts 
                         of dengue risk. The approaches (including aim, methodological 
                         framework, data, and population) that we used2 differ in several 
                         ways from those used by Massad and colleagues3 to estimate the 
                         risk of acquiring dengue fever during the 2014 FIFA World Cup in 
                         Brazil. Massad and colleagues used a mathematical modelling 
                         approach, which was based on weekly notified cases in previous 
                         weeks, to estimate the number of cases of dengue in foreign 
                         visitors to Brazil. We used a spatiotemporal statistical model, 
                         driven by climate information and dengue incidence 4 months 
                         previously, to predict the probability of exceeding given 
                         thresholds for the whole Brazilian population.",
                  doi = "10.1016/S1473-3099(14)71031-X",
                  url = "http://dx.doi.org/10.1016/S1473-3099(14)71031-X",
                 issn = "0140-6736",
             language = "en",
           targetfile = "Interpretation of probabilistic.pdf",
        urlaccessdate = "25 nov. 2020"