Huang, G., Lee, D. and Scott, M. (2015) An integrated Bayesian model for estimating the long-term health effects of air pollution by fusing modelled and measured pollution data: a case study of nitrogen dioxide concentrations in Scotland. Spatial and Spatio-Temporal Epidemiology, 14-15, pp. 63-74. (doi: 10.1016/j.sste.2015.09.002) (PMID:26530824)
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Abstract
The long-term health effects of air pollution can be estimated using a spatio-temporal ecological study, where the disease data are counts of hospital admissions from populations in small areal units at yearly intervals. Spatially representative pollution concentrations for each areal unit are typically estimated by applying Kriging to data from a sparse monitoring network, or by computing averages over grid level concentrations from an atmospheric dispersion model. We propose a novel fusion model for estimating spatially aggregated pollution concentrations using both the modelled and monitored data, and relate these concentrations to respiratory disease in a new study in Scotland between 2007 and 2011.
| Item Type: | Articles |
|---|---|
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Lee, Professor Duncan and Huang, Mr Guowen |
| Authors: | Huang, G., Lee, D., and Scott, M. |
| College/School: | College of Science and Engineering > School of Mathematics and Statistics > Statistics |
| Journal Name: | Spatial and Spatio-Temporal Epidemiology |
| Publisher: | Elsevier |
| ISSN: | 1877-5845 |
| ISSN (Online): | 1877-5853 |
| Copyright Holders: | Copyright © 2015 The Authors |
| First Published: | First published in Spatial and Spatio-Temporal Epidemiology 14-15:63-74 |
| Publisher Policy: | Reproduced under a Creative Commons License |
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