An open-source framework for the detailed simulation of epidemics on the basis of social interactions in a virtual population constructed from geographically granular census data, reflecting age, sex, ethnicity, and socio-economic indicators. Interactions between individuals are modelled in groups of various sizes and properties, such as households, schools and work-places, and other social activities using social mixing matrices. The individual-based model provides a suite of flexible parameterisations that describe infectious diseases, how they are transmitted and affect contaminated individuals. So far it has been applied to the modelling the spread of COVID-19 in England and to the Kutupalong refugee camp.