A Comparison of Spatio-Temporal Disease Mapping Approaches Including an Application to Ischaemic Heart Disease in New South Wales, Australia.
The field of spatio-temporal modelling has witnessed a recent surge as a result of developments in computational power and increased data collection. These developments allow analysts to model the evolution of health outcomes in both space and time simultaneously. This paper models the trends in ischaemic heart disease (IHD) in New South Wales, Australia over an eight-year period between 2006 and 2013. A number of spatio-temporal models are considered, and we propose a novel method for determining the goodness-of-fit for these models by outlining a spatio-temporal extension of the Moran's I statistic. We identify an overall decrease in the rates of IHD, but note that the extent of this health improvement varies across the state. In particular, we identified a number of remote areas in the north and west of the state where the risk stayed constant or even increased slightly.
School of Mathematical and Physical Sciences, University of Technology Sydney, 15 Broadway, Ultimo, NSW 2007, Australia. craig.anderson@uts.edu.au.|ARC Centre of Excellence for Mathematical and Statistical Frontiers (ACEMS), Parkville, VIC 3010, Australia. craig.anderson@uts.edu.au.
Craig
C
Anderson
School of Mathematical and Physical Sciences, University of Technology Sydney, 15 Broadway, Ultimo, NSW 2007, Australia. Louise.M.Ryan@uts.edu.au.|ARC Centre of Excellence for Mathematical and Statistical Frontiers (ACEMS), Parkville, VIC 3010, Australia. Louise.M.Ryan@uts.edu.au.
Louise M
LM
Ryan
D001315:Australia / Q000453:epidemiology; D006801:Humans; D008962:Models, Theoretical; D017202:Myocardial Ischemia / Q000453:epidemiology*; D009517:New South Wales / Q000453:epidemiology; D062211:Spatio-Temporal Analysis
Bayesian; disease mapping; ischaemic heart disease, Moran’s I; spatio-temporal modelling