Before revision:  We use a sparse regression method to fit the dynamic progression of the data (the Rt parameter) with the least number of changes , allowing us to attribute discrete change events to specific intervention events.
After revision:  We use a regularized regression to find a parsimonious model that fits the data with the least number of changes , allowing us to attribute discrete change events to specific intervention events.