Abstract
This chapter details a deterministic method of spatial microsimulation modelling, which uses a set of algorithms based on combinatorial optimisation. This model, called SimObesity, was developed within the School of Geography, University of Leeds. An application of this model to estimate adult obesity prevalence is demonstrated. The chapter discusses the value of adopting a spatial microsimulation procedure and briefly debates the pros and cons of probabilistic and deterministic techniques for data imputation. Having chosen the latter, the chapter discusses the data and methodology used to estimate small-area prevalence of obesity in northern England. The results are discussed both in terms of the reliability of the model outputs (validation) and in terms of the spatial variation in estimated patterns.
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Edwards, K.L., Clarke, G. (2012). SimObesity: Combinatorial Optimisation (Deterministic) Model. In: Tanton, R., Edwards, K. (eds) Spatial Microsimulation: A Reference Guide for Users. Understanding Population Trends and Processes, vol 6. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-4623-7_5
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DOI: https://doi.org/10.1007/978-94-007-4623-7_5
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