SimAlba: A Spatial Microsimulation Approach to the Analysis of Health Inequalities

Malcolm Campbell*, Dimitris Ballas

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

6 Citations (Scopus)
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Abstract

This paper presents applied geographical research based on a spatial microsimulation model, SimAlba, aimed at estimating geographically sensitive health variables in Scotland. SimAlba has been developed in order to answer a variety of "what-if" policy questions pertaining to health policy in Scotland. Using the SimAlba model, 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. The SimAlba micro-dataset has been created by combining Scottish Health Survey and Census data using a deterministic reweighting spatial microsimulation algorithm developed for this purpose. The paper presents SimAlba outputs 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.

Original languageEnglish
Article number230
Number of pages9
JournalFrontiers in public health
Volume4
DOIs
Publication statusPublished - 21-Oct-2016
Externally publishedYes

Keywords

  • spatial microsimulation
  • urban health inequalities
  • health policy
  • Scotland
  • geographic information systems
  • small area microdata
  • SCOTLAND
  • OBESITY
  • DEPRIVATION
  • MORTALITY
  • WORLDWIDE
  • POVERTY
  • GLASGOW
  • ALCOHOL
  • ENGLAND
  • LEGISLATION

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