Due to immature treatment and rapid transmission of COVID-19, mobility
interventions play a crucial role in containing the outbreak. Among various
non-pharmacological interventions, community infection control is considered to
be a quite promising approach. However, there is a lack of research on
improving community-level interventions based on a community's real conditions
and characteristics using real-world observations. Our paper aims to
investigate the different responses to mobility interventions between
communities in the United States with a specific focus on different income
levels. We produced six daily mobility metrics for all communities using the
mobility location data from over 100 million anonymous devices on a monthly
basis. Each metric is tabulated by three performance indicators: "best
performance," "effort," and "consistency." We found that being high-income
improves social distancing behavior after controlling multiple confounding
variables in each of the eighteen scenarios. In addition to the reality that it
is more difficult for low-income communities to comply with social distancing,
the comparisons between scenarios raise concerns on the employment status,
working condition, accessibility to life supplies, and exposure to the virus of
low-income communities