  To develop public health intervention models using microsimulations,
extensive personal information about inhabitants is needed, such as
socio-demographic, economic and health figures. Data confidentiality is an
essential characteristic of such data, while the data should support realistic
scenarios. Collection of such data is possible only in secured environments and
not directly available for external micro-simulation models. The aim of this
paper is to illustrate a method for construction of synthetic data by
predicting individual features through models based on confidential data on
health and socio-economic determinants of the entire Dutch population.
