Like many, I’m interested in identifying areas where potentially risky behaviors (ie, more physical contact with more people) are increasing–say within a single state. I’ve read the docs on normalization and correcting sampling bias, but are there different approaches necessary for different elements of the social distancing data? eg, completely_home_device_count versus full_time_work_behavior_devices versus destination_cbgs–these are very different kinds of measures built from SafeGraph data, and I imagine they have different levels of sensitivity to underlying changes in the panel