@Article{RouxIBBCDGGHMMRVXB:2020:FeUsGl,
               author = "Roux, Emmanuel and Ignotti, Eliane and B{\`e}gue, Nelson and 
                         Bencherif, Hassan and Catry, Thibault and Dessay, Nadine and 
                         Gracie, Renata and Gurgel, Helen and Hacon, Sandra de Sousa and 
                         Magalh{\~a}es, M{\^o}nica de Avelar Figueiredo Mafra and 
                         Monteiro, Ant{\^o}nio Miguel Vieira and Revillion, Christophe and 
                         Villela, Daniel Antunes Maciel and Xavier, Diego Ricardo and 
                         Barcellos, Christovam",
          affiliation = "{Universit{\'e} de la R{\'e}union} and {Universidade do Estado 
                         de Mato Grosso (UNEMAT)} and {Universit{\'e} de la R{\'e}union} 
                         and {Universit{\'e} de la R{\'e}union} and {Universit{\'e} de 
                         la R{\'e}union} and {Universit{\'e} de la R{\'e}union} and 
                         {Funda{\c{c}}{\~a}o Oswaldo Cruz (FIOCRUZ)} and {Universidade de 
                         Bras{\'{\i}}lia (UnB)} and {Funda{\c{c}}{\~a}o Oswaldo Cruz 
                         (FIOCRUZ)} and {Funda{\c{c}}{\~a}o Oswaldo Cruz (FIOCRUZ)} and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)} and 
                         {Universit{\'e} de la R{\'e}union} and {Funda{\c{c}}{\~a}o 
                         Oswaldo Cruz (FIOCRUZ)} and {Funda{\c{c}}{\~a}o Oswaldo Cruz 
                         (FIOCRUZ)} and {Funda{\c{c}}{\~a}o Oswaldo Cruz (FIOCRUZ)}",
                title = "Toward an early warning system for health issues related to 
                         particulate matter exposure in brazil: the feasibility of using 
                         global pm2.5 concentration forecast products",
              journal = "Remote Sensing",
                 year = "2020",
               volume = "12",
               number = "24",
                pages = "e4074",
                month = "Dec.",
             keywords = "particulate matter forecasts, severe acute respiratory diseases, 
                         Brazil, early warning system, remotely sensed observation 
                         assimilation.",
             abstract = "PM2.5 severely affects human health. Remotely sensed (RS) data can 
                         be used to estimate PM2.5 concentrations and population exposure, 
                         and therefore to explain acute respiratory disorders. However, 
                         available global PM2.5 concentration forecast products derived 
                         from models assimilating RS data have not yet been exploited to 
                         generate early alerts for respiratory problems in Brazil. We 
                         investigated the feasibility of building such an early warning 
                         system. For this, PM2.5 concentrations on a 4-day horizon forecast 
                         were provided by the Copernicus Atmosphere Monitoring Service 
                         (CAMS) and compared with the number of severe acute respiratory 
                         disease (SARD) cases. Confounding effects of the meteorological 
                         conditions were considered by selecting the best linear regression 
                         models in terms of Akaike Information Criterion (AIC), with 
                         meteorological features and their two-way interactions as 
                         explanatory variables and PM2.5 concentrations and SARD cases, 
                         taken separately, as response variables. Pearson and Spearman 
                         correlation coefficients were then computed between the residuals 
                         of the models for PM2.5 concentration and SARD cases. The results 
                         show a clear tendency to positive correlations between PM2.5 and 
                         SARD in all regions of Brazil but the South one, with Spearmans 
                         correlation coefficient reaching 0.52 (p < 0.01). Positive 
                         significant correlations were also found in the South region by 
                         previously correcting the effects of viral infections on the SARD 
                         case dynamics. The possibility of using CAMS global PM2.5 
                         concentration forecast products to build an early warning system 
                         for pollution-related effects on human health in Brazil was 
                         therefore established. Further investigations should be performed 
                         to determine alert threshold(s) and possibly build combined risk 
                         indicators involving other risk factors for human respiratory 
                         diseases. This is of particular interest in Brazil, where the 
                         COVID-19 pandemic and biomass burning are occurring concomitantly, 
                         to help minimize the effects of PM emissions and implement 
                         mitigation actions within populations.",
                  doi = "10.3390/rs12244074",
                  url = "http://dx.doi.org/10.3390/rs12244074",
                 issn = "2072-4292",
             language = "en",
           targetfile = "roux_toward.pdf",
        urlaccessdate = "25 abr. 2024"
}