Are Americans Following COVID-19 Movement Restrictions?

The COVID-19 pandemic rapidly altered everyday life across the United States, disrupting routines on a scale few had ever experienced. Within weeks, stay-at-home advisories, business closures, and social distancing rules reshaped how and when people moved outside their homes. These measures were widely recognized as essential for slowing virus transmission—but an important question remained: were Americans actually complying?

To explore this, Environics Analytics analyzed anonymized mobile movement data collected between early February and late April 2020. The results reveal that compliance with movement restrictions varied significantly across regions and population groups, influenced by income, occupation, and where people live.

Movement Before and During Restrictions

In early February, before any major COVID-19 restrictions were introduced, movement levels across the country reflected typical patterns. Rural residents were more likely to travel farther and more frequently, often due to longer distances to workplaces, grocery stores, and essential services. Urban and suburban populations, by contrast, generally traveled shorter distances and left home less often.

By mid-to-late April, the situation had changed dramatically. As awareness of the pandemic intensified and restrictions became widespread, movement levels dropped sharply—especially in large coastal metropolitan areas. While rural and small-town regions also reduced their activity, the decline was less pronounced, highlighting regional differences in how restrictions played out on the ground.

Why Mobility Data Alone Isn’t Enough

While mobile movement data provides valuable insights, it does not fully explain why people behave differently. To add context, Environics Analytics combined movement data with privacy-compliant demographic, socioeconomic, and lifestyle information. This approach made it possible to examine how different population segments responded to stay-at-home guidance.

Using the Claritas PRIZM® Premier segmentation system, which groups Americans into lifestyle-based segments, the analysis compared populations with similar characteristics but contrasting mobility patterns.

Income and Work Conditions Drive Movement

One clear pattern emerged: lower-income populations were significantly more likely to leave home. For example, higher-income professionals living in small cities were often able to work remotely and rely on delivery services, resulting in movement levels well below the national average.

In contrast, lower-income residents working in service roles—such as retail, food service, and frontline occupations—had far fewer options. Many were required to travel for work or essential supplies, leading to substantially higher movement rates. Notably, both groups shared a belief in the value of active government, suggesting that clear, targeted public messaging could still resonate across income levels.

Age Is Less Important Than You Might Think

Early in the pandemic, younger Americans received disproportionate attention for perceived non-compliance. However, the data suggests that age alone was not a reliable predictor of movement behavior.

In urban areas, both younger and older high-income, highly educated segments showed similarly low levels of movement, largely because their jobs allowed remote work. These groups also consumed similar news media, indicating effective channels for reinforcing public health messaging.

In rural areas, however, both younger and older low-income groups exhibited significantly higher movement rates. Limited access to nearby services, fewer remote work opportunities, and economic necessity all contributed. In some cases, elevated movement was particularly concerning due to underlying health conditions common within these populations.

Urban Density Changes the Risk Equation

Comparisons between urban and rural low-income populations further highlighted the role of geography. Urban residents with modest incomes tended to leave home slightly more often than average, but they typically traveled shorter distances due to proximity to services. However, higher population density meant that even limited outings increased the likelihood of close contact with others.

Rural residents, on the other hand, traveled more frequently and over longer distances, but with fewer interpersonal interactions per trip. Each group required different public health strategies to reduce risk effectively.

Tailoring Messages to Different Communities

The analysis also revealed stark differences in media consumption and values. Urban low-income populations spent significantly more time on social media and expressed strong concern for social responsibility and global issues—making digital campaigns framed around protecting others more effective.

Rural populations were less engaged online, relying more on radio and television, particularly country music and traditional programming. These groups tended to value authority and local identity, suggesting that direct, unambiguous messaging from trusted officials would be more effective than generalized guidance.

Data-Driven Insights for Public Health Strategy

The findings underscore a critical reality: Americans are not a homogeneous population. Differences in income, occupation, geography, and values strongly influence the ability—and willingness—to comply with movement restrictions.

Improving compliance during public health emergencies requires more than blanket policies. Targeted communication strategies, support mechanisms such as home delivery of essentials, and an understanding of local constraints are essential for reducing risk and protecting vulnerable populations.

Methodology

The analysis was based on Environics Analytics’ MobileScapes dataset, derived from aggregated and anonymized mobile device movement data. “Going out” was defined as a device moving more than 300 feet from its inferred home location at least three times per day, for ten minutes or more, during daytime hours on weekends.

About Environics Analytics

Environics Analytics is a leading North American provider of data analytics and location intelligence. The company helps organizations gain deeper insights into consumer behavior, demographics, and movement patterns to support informed decision-making across public and private sectors.