This line of inquiry seeks to utilize spatial interaction models (SIM) to study urban mobility. Specifically, this work utilizes the high temporal frequency of new transport datasets, such as automatically collected taxi trips and bike-share trips, to study the impacts of disruptions upon urban mobility. Ongoing research includes an application to extreme weather events and the Covid-19 pandemic in New York City and the development of an open source Python implementation of SIMs that scale to accommodate a large number of origin-destination pairs.