TY - JOUR
T1 - A rigorous statistical framework for spatio-temporal pollution prediction and estimation of its long-term impact on health
AU - Lee, Duncan
AU - Mukhopadhyay, Sabyasachi
AU - Rushworth, Alastair
AU - Sahu, Sujit K.
N1 - © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: [email protected].
PY - 2017/4/30
Y1 - 2017/4/30
N2 - In the United Kingdom, air pollution is linked to around 40000 premature deaths each year, but estimating its health effects is challenging in a spatio-temporal study. The challenges include spatial misalignment between the pollution and disease data; uncertainty in the estimated pollution surface; and complex residual spatio-temporal autocorrelation in the disease data. This article develops a two-stage model that addresses these issues. The first stage is a spatio-temporal fusion model linking modeled and measured pollution data, while the second stage links these predictions to the disease data. The methodology is motivated by a new five-year study investigating the effects of multiple pollutants on respiratory hospitalizations in England between 2007 and 2011, using pollution and disease data relating to local and unitary authorities on a monthly time scale.
AB - In the United Kingdom, air pollution is linked to around 40000 premature deaths each year, but estimating its health effects is challenging in a spatio-temporal study. The challenges include spatial misalignment between the pollution and disease data; uncertainty in the estimated pollution surface; and complex residual spatio-temporal autocorrelation in the disease data. This article develops a two-stage model that addresses these issues. The first stage is a spatio-temporal fusion model linking modeled and measured pollution data, while the second stage links these predictions to the disease data. The methodology is motivated by a new five-year study investigating the effects of multiple pollutants on respiratory hospitalizations in England between 2007 and 2011, using pollution and disease data relating to local and unitary authorities on a monthly time scale.
KW - air pollution estimation
KW - Bayesian spatio-temporal modeling
KW - health effects analysis
KW - spatio-temporal fusion model
KW - disease data
KW - respiratory hospitalizations
UR - https://academic.oup.com/biostatistics
U2 - 10.1093/biostatistics/kxw048
DO - 10.1093/biostatistics/kxw048
M3 - Article
C2 - 28025181
SN - 1465-4644
VL - 18
SP - 370
EP - 385
JO - Biostatistics
JF - Biostatistics
IS - 2
ER -