Agent-based models tend to integrate more and more data that can deeply impact their
outcomes. Among these data, the ones that deal with agent attributes and localization are …

The presence of identical benchmark/constraint variables in both geographic and survey
datasets is a principal requirement for static spatial microsimulation models, particularly in …

Sensitive local planning is necessary to meet people's needs and to distribute scarce health
care resources best to meet government aims. This requires good quality health data, which …

We propose a framework for realistic data generation and the simulation of complex systems
and demonstrate its capabilities in a health domain example. The main use cases of the …

Cities, particularly those home of millions, are often viewed as unhealthy places. Poor air
quality, noise pollution, and scarcity of public green space are among the first few things that …

We propose a framework for realistic data generation and simulation of complex systems
and demonstrate its capabilities in the health domain. The main use cases of the framework …

In this thesis welfare is examined in a spatial context. A broader definition of welfare is taken
so that it includes more than just income. In-kind benefits, indirect costs, life-satisfaction …

Simulation modelling has become an important tool in social science research, though such
models are less commonly used in population health. Spatial microsimulation models …

Lung cancer is still at the top of the list of commonly preventable diseases, for both men and
women, and smoking is the major trigger that causes lung cancer. The Austrian Health …