Human-to-human communicable diseases can be devastating in urban areas where large heterogeneous population groups are living in restricted spaces, causing serious concerns for public health, especially during epidemic outbreaks. Even though Geographic Information Systems (GIS) have been used to study a variety of public health issues in the last decade, their use to study human communicable diseases has been limited to the development of disease clustering, mapping and surveillance systems. These systems don't provide ways to understand and predict the dynamics of diseases spread across an urban region, taking into account the dynamics of human contacts and mobility, which are the main widely recognized mechanisms responsible for diseases' spread. In this paper we address such limits by presenting a GIS-based spatial-temporal simulation approach and software to support public health decision making in the context of communicable diseases in urban areas. The approach fully integrates epidemiological, mobility and GIS-data models at an aggregate population level in order to support spatialized interventions.