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)

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Abstract

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.
Status:Published
Refereed:Yes
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:1465-4644
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

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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