Investigating trends in asthma and COPD through multiple data sources: A small area study

TitleInvestigating trends in asthma and COPD through multiple data sources: A small area study
Publication TypeJournal Article
Year of Publication2016
AuthorsBoulieri A., Hansell A., Blangiardo M.
JournalSpat Spatiotemporal EpidemiolSpatial and Spatio-temporal EpidemiologySpatial and Spatio-temporal Epidemiology
Volume19
Pagination28-36
Date PublishedNov
ISBN Number1877-5845
Accession Number27839578
KeywordsAsthma and COPD, Detection, Space-time analysis
Abstract

This paper investigates trends in asthma and COPD by using multiple data sources to help understanding the relationships between disease prevalence, morbidity and mortality. GP drug prescriptions, hospital admissions, and deaths are analysed at clinical commissioning group (CCG) level in England from August 2010 to March 2011. A Bayesian hierarchical model is used for the analysis, which takes into account the complex space and time dependencies of asthma and COPD, while it is also able to detect unusual areas. Main findings show important discrepancies across the different data sources, reflecting the different groups of patients that are represented. In addition, the detection mechanism that is provided by the model, together with inference on the spatial, and temporal variation, provide a better picture of the respiratory health problem.

Short TitleSpat Spatiotemporal EpidemiolSpat Spatiotemporal Epidemiol
Alternate JournalSpatial and spatio-temporal epidemiology