Recent advances in social network research have highlighted a variety of strategies for leveraging social networks to improve community-based interventions. Nonetheless, the role of social networks in interventions is frequently under-theorized or taken for granted. Furthermore, predicting which type of social network intervention would work best in which neighbourhood is sometimes difficult to test in practice. Therefore, in our study, we will develop an agent-based model to create an intervention planning tool called the Health in All Networks Simulator (HANS). The HANS will be developed in part in collaboration with community members and policy stakeholders, for example, through network mapping or interviews, to improve the development and adoption of social network strategies in Amsterdam health promotion initiatives. Other data would come from pre-existing data sources, such as ODISSEI and HELIUS. The HANS will enable researchers and stakeholders to virtually test the impact of different social network intervention strategies in neighbourhoods on the resilience, health, and well-being of their residents; either with observed or hypothetical network characteristics. Simultaneously, the model will account for multiscale interactions and bidirectional feedback loop interactions, such as those originating from the communities' geo-spatial environment. By making the agent-based model available for stakeholders via workshops, we hope to serve the community better and gain feedback that will help us improve the HANS for future use. Understanding the efficacy of different social network interventions across neighbourhoods may contribute to improving population health while reducing health disparities. This work is supported by ZonMW (projectnumber: 05550032110022)