title: A rigorous statistical framework for spatio-temporal pollution prediction and estimation of its long-term impact on health.
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.
authors.affiliation: School of Mathematics and Statistics, University of Glasgow, 15 University Gardens, Glasgow G12 8QW, UKduncan.lee@glasgow.ac.uk.
authors.forename: Duncan
authors.initials: D
authors.lastname: Lee
authors.affiliation: School of Mathematics, University of Southampton, Building 54, Salisbury Road, Southampton SO17 1BJ, UK.
authors.forename: Sabyasachi
authors.initials: S
authors.lastname: Mukhopadhyay
authors.affiliation: Department of Mathematics and Statistics, University of Strathclyde, Livingston Tower, 26 Richmond Street, Glasgow G1 1XH, UK.
authors.forename: Alastair
authors.initials: A
authors.lastname: Rushworth
authors.affiliation: School of Mathematics, University of Southampton, Building 54, Salisbury Road, Southampton SO17 1BJ, UK.
authors.forename: Sujit K
authors.initials: SK
authors.lastname: Sahu
mesh_terms: D000397:Air Pollution / Q000009:adverse effects* / Q000706:statistics & numerical data*; D001499:Bayes Theorem; D004739:England / Q000453:epidemiology; D004781:Environmental Exposure / Q000009:adverse effects*; D006801:Humans; D015233:Models, Statistical; D012140:Respiratory Tract Diseases / Q000453:epidemiology* / Q000209:etiology*
keywords: Air pollution estimation; Bayesian spatio-temporal modeling; Health effects analysis