A rigorous statistical framework for spatio-temporal pollution prediction and estimation of its long-term impact on health

Lee, D. , Mukhopadhyay, S., Rushworth, A. and Sahu, S. K. (2017) A rigorous statistical framework for spatio-temporal pollution prediction and estimation of its long-term impact on health. Biostatistics, 18(2), pp. 370-385. (doi: 10.1093/biostatistics/kxw048) (PMID:28025181)

130027.pdf - Published Version
Available under License Creative Commons Attribution.



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.

Item Type:Articles
Additional Information:The work was funded by the Engineering and Physical Sciences Research Council (EPSRC) grant numbers EP/J017442/1 and EP/J017485/1.
Glasgow Author(s) Enlighten ID:Rushworth, Mr Alastair and Lee, Professor Duncan
Authors: Lee, D., Mukhopadhyay, S., Rushworth, A., and Sahu, S. K.
College/School:College of Science and Engineering > School of Mathematics and Statistics > Statistics
Journal Name:Biostatistics
Publisher:Oxford University Press
ISSN (Online):1468-4357
Published Online:24 December 2016
Copyright Holders:Copyright © 2016 The Authors
First Published:First published in Proteome Science 18(2):370-385
Publisher Policy:Reproduced under a Creative Commons License

University Staff: Request a correction | Enlighten Editors: Update this record

Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
588351A rigorous statistical framework for estimating the long-term health effects of air pollution.Duncan LeeEngineering & Physical Sciences Research Council (EPSRC)EP/J017442/1M&S - STATISTICS