Social factors moderate the impacts of natural hazards, which means that households are affected differently when exposed to the same hazard. This differential impact of hazards can be explained by the concept of social vulnerability, which is commonly assessed to inform disaster preparedness and response action. Most of these assessments, however, focus their analyses on large administrative units and, consequently, neglect the heterogeneity of households within these units. This thesis leverages data from Malawi’s social registry (the UBR) to construct a Household Social Vulnerability Index for Nsanje – one of the most disaster-prone districts in Malawi. In Nsanje, geocoded socio-economic data was collected using a census-sweep approach with the goal of registering 100% of the district’s residents. From this dataset, indicators are deductively selected and analyzed using Principal Component Analysis to produce a social vulnerability score for each household. These index scores are mapped at a spatial resolution of 0,01°. By repurposing a social registry to inform a new set of actors, including humanitarian and disaster risk management practitioners, the thesis highlights the considerable scope for collaboration within the realm of data and information by actors and policy fields that traditionally largely have operated in isolation from one another.