Understanding spreading dynamics can help predict how a highly contagious disease can infect an entire population, how ideas propagate in societies, and how successful marketing campaigns emerge. In this study, we develop an agent-based model to highlight the role of individual heterogeneity in defining and shaping spreading dynamics. We select the case study of a virus spreading. The proposed model creates proximity networks in an urban environment, which is based on the city of Brussels. Various implementations of individual features and decision heterogeneity were examined. Our findings highlight the impact of individual irrationality and the size of social networks on emergent spreading and on the efficiency of local interventions.