SimHealth: Estimating Small Area Populations Using Deterministic Spatial Microsimulation in Leeds and Bradford.

Abstract

The increasing prevalence of obesity and type 2 diabetes in recent decades is often cited as a serious public health concern, lowering life expectancy and costing the National Health Service (NHS) billions of pounds each year. However, measuring diabetes prevalence proves challenging; the best estimates are based on the annual Health Survey for England (HSE) and little is currently available at the small area level. Simulation models are increasingly used in health research to predict future prevalence, cost of treatment, provision of care and the possible outcomes of policy intervention. Previous research shows the relevance of this technique in modelling the outcomes of changes in taxation and child benefit policy, or analysing health inequalities. This paper introduces SimHealth, a small-area diabetes prevalence model for Leeds and Bradford, West Yorkshire created as part of a generic model framework. The process of configuring an optimal spatial microsimulation model, building on earlier research, is detailed with the aim of improving and extending existing simulation models