What is Stay-at-Home Order

Exploring human mobility changes and spatial dynamic patterns is crucial for assisting the policy-making process of non-pharmaceutical interventions. Examining the actual degree of practicing stay-at-home orders or travel restrictions becomes an underlying question that can be answered by tracking the human mobility within a target area over time. In this chapter, several visual mining tools have been performed with results of uncovering the reason why the United States fails the stay-at-home policy. The pandemic-mobility management system architecture has been illustrated with an example of its usage, which can be applied to monitor medical risks and pandemic-mobility indicators per region. Such a spatiotemporally hyperconnected resolution of human movements and pandemic information may assist public authorities to monitor the pandemic-mobility patterns, guide the health policymaking, and deepen the understanding of human behaviors in the context of COVID-19.