SimAlba: A Spatial Microsimulation Approach to the Analysis of Health Inequalities.
This paper presents applied geographical research based on a spatial microsimulation model,SimAlba, aimed at estimating geographically sensitive health variables in Scotland.SimAlbahas been developed in order to answer a variety of "what-if" policy questions pertaining to health policy in Scotland. Using theSimAlbamodel, it is possible to simulate the distributions of previously unknown variables at the small area level such as smoking, alcohol consumption, mental well-being, and obesity. TheSimAlbamicrodataset has been created by combining Scottish Health Survey and Census data using a deterministic reweighting spatial microsimulation algorithm developed for this purpose. The paper presentsSimAlbaoutputs for Scotland's largest city, Glasgow, and examines the spatial distribution of the simulated variables for small geographical areas in Glasgow as well as the effects on individuals of different policy scenario outcomes. In simulating previously unknown spatial data, a wealth of new perspectives can be examined and explored. This paper explores a small set of those potential avenues of research and shows the power of spatial microsimulation modeling in an urban context.
GeoHealth Laboratory, Department of Geography, University of Canterbury , Christchurch , New Zealand.
Malcolm
M
Campbell
Department of Geography, University of Sheffield, Sheffield, UK; Department of Geography, University of the Aegean, Mytilene, Greece.
Dimitris
D
Ballas
Scotland; geographic information systems; health policy; small area microdata; spatial microsimulation; urban health inequalities