@article{fdi:010080523,
  title = {{T}oward an early warning system for health issues related to particulate matter exposure in {B}razil : the feasibility of using global {PM}2.5 concentration forecast products},
  author = {{R}oux, {E}mmanuel and {I}gnotti, {E}. and {B}egue, {N}. and {B}encherif, {H}. and {C}atry, {T}hibault and {D}essay, {N}adine and {G}racie, {R}. and {G}urgel, {H}. and {H}acon, {S}. {D}. and {M}agalhaes, {M}dfm and {M}onteiro, {A}. {M}. {V}. and {R}evillion, {C}. and {V}illela, {D}. {A}. {M}. and {X}avier, {D}. and {B}arcellos, {C}.},
  editor = {},
  language = {{ENG}},
  abstract = {{PM}2.5 severely affects human health. {R}emotely sensed ({RS}) data can be used to estimate {PM}2.5 concentrations and population exposure, and therefore to explain acute respiratory disorders. {H}owever, available global {PM}2.5 concentration forecast products derived from models assimilating {RS} data have not yet been exploited to generate early alerts for respiratory problems in {B}razil. {W}e investigated the feasibility of building such an early warning system. {F}or this, {PM}2.5 concentrations on a 4-day horizon forecast were provided by the {C}opernicus {A}tmosphere {M}onitoring {S}ervice ({CAMS}) and compared with the number of severe acute respiratory disease ({SARD}) cases. {C}onfounding effects of the meteorological conditions were considered by selecting the best linear regression models in terms of {A}kaike {I}nformation {C}riterion ({AIC}), with meteorological features and their two-way interactions as explanatory variables and {PM}2.5 concentrations and {SARD} cases, taken separately, as response variables. {P}earson and {S}pearman correlation coefficients were then computed between the residuals of the models for {PM}2.5 concentration and {SARD} cases. {T}he results show a clear tendency to positive correlations between {PM}2.5 and {SARD} in all regions of {B}razil but the {S}outh one, with {S}pearman's correlation coefficient reaching 0.52 (p < 0.01). {P}ositive significant correlations were also found in the {S}outh region by previously correcting the effects of viral infections on the {SARD} case dynamics. {T}he possibility of using {CAMS} global {PM}2.5 concentration forecast products to build an early warning system for pollution-related effects on human health in {B}razil was therefore established. {F}urther investigations should be performed to determine alert threshold(s) and possibly build combined risk indicators involving other risk factors for human respiratory diseases. {T}his is of particular interest in {B}razil, 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.},
  keywords = {particulate matter forecasts ; severe acute respiratory diseases ; {B}razil ; early warning system ; remotely sensed observation assimilation ; {BRESIL}},
  booktitle = {},
  journal = {{R}emote {S}ensing},
  volume = {12},
  numero = {24},
  pages = {4074 [45 ]},
  year = {2020},
  DOI = {10.3390/rs12244074},
  URL = {https://www.documentation.ird.fr/hor/fdi:010080523},
}