In the absence of effective treatments or a vaccine, social distancing has been the only public health measure available to combat the COVID-19 pandemic to date. In the US, implementing this response has been left to state, county, and city officials, and many localities have issued some form of a stay-at-home order. Without existing tools and with limited resources, localities struggled to understand how their orders changed behavior. In response, several technology companies opened access to their users' location data. As part of the COVID-19 Data Mobility Data Network, we obtained access to Facebook User data and developed four key metrics and visualizations to monitor various aspects of adherence to stay at home orders. These metrics were carefully incorporated into static and interactive visualizations for dissemination to local officials. All code is open source and freely available at https://github.com/ryanlayer/COvid19
Case Study: Using Facebook Data to Monitor Adherence to Stay-at-home Orders in Colorado and Utah