London-disease-spatial-analysis

The following review is focused on annual hospital admissions for 624 electoral wards in Greater London over seven years from 2003 to 2009. With a total of 624 rows, the dataset contains six variables: observed, expected, JSA, price, PM25, and year. To estimate the impact of air pollution and socio-economic variables on the risk of admission to hospital due to respiratory disease, two spatial models were used: Possion regression and CAR model with Poisson regression. For fitting a Bayesian model using Markov chain Monte Carlo (MCMC) methods, both models were run on R with OpenBUGS.