Researchers’ Data Analysis Shows Erratic Response to COVID-19 Restrictions
A new interactive platform from UMD researchers uses mobility data from mobile devices and elsewhere to determine Americans' level of cooperation with social distancing requirements, shown geographically in a scale from black (for least cooperation) to white (indicating more cooperation).
Most Americans were slow to follow state and federal physical distancing guidelines in March and into April, even as number of COVID-19 cases nationwide skyrocketed, new University of Maryland research shows.
The percentage of people staying home nationwide increased from 20% to 35% from the onset of COVID-19 to mid-March, but then it stagnated at 35% for three weeks. This erratic compliance by many Americans is just one of the trends registered by a new interactive analytics platform developed by researchers in the A. James Clark School of Engineering to measure the impact of COVID-19 on mobility, health, the economy and society.
“Government advisories and stay-at-home orders have reduced trip distance across the nation and in some states the percentage of people staying home, and trip rates too. However, they have not fully accomplished the expected change in mobility behavior, according to our data analysis,” said Maryland Transportation Institute (MTI) Director and Herbert Rabin Distinguished Professor Lei Zhang, who leads the project. “Those who are able to adopt social distancing practices already did so before government intervention. Those who cannot or do not want to stay at home show significant behavior inertia and render government stay-at-home orders much less effective than expected.”
Government stay-at-home orders have had a positive, but limited, impact on mobility behavior, the platform shows. The highest increase in the percentage of people staying at home during the week after a statewide order, in comparison to the week before the order, belongs to New Jersey (13%), followed by New York (11%), Illinois (11%), California (11%) and Michigan (10%). Government orders had virtually no impact on the percentage of people staying home in Kentucky, Maine, South Carolina, Pennsylvania and Missouri. On average, a government order has resulted in just a 4.3% change in mobility behavior.
The District of Columbia and New York led the nation in percentage of people staying at home (defined as making trips less than one mile from home), but stagnated for weeks around 54% for the District of Columbia and 49% for New York, even after shelter-in-place restrictions were imposed.
The total number of trips per person has dropped by 22% nationwide. Among all the trips still being taken, however, fewer than 14% are trips to and from work. The majority of the trips taken are still for non-work purposes. Meanwhile, inter-county and out-of-town trips still comprise a significant portion of all trips, at 25% nationwide, the platform shows.
The UMD researchers are making their data and findings, which are updated daily, available to the public to help officials make informed policy decisions.
“Government agencies need to improve the effectiveness of physical distancing and stay-at-home orders by educating the general public, increasing enforcement, working with employers and communities, and supporting vulnerable populations who may encounter challenges in meeting social distancing requirements,” Zhang said.
Using anonymized and aggregated location data from mobile devices and other sources, the new impact analysis platform provides daily data back to Jan. 1 on variables that include a social distancing index, percentage of people staying at home, visits to work and non-work locations, out-of-county trips, trip distance, and relationship between mobility behavior and COVID-19 cases. The results are aggregated and scaled to the entire population of each county and state.
Center for Advanced Transportation Technology (CATT) Laboratory Director Michael Pack is the project co-lead. “This is just phase one of our analysis,” Pack said. “We plan on rolling out new statistics, correlated data, information visualizations and other tools to the platform daily to enable more insights and discoveries.”
The mobility metrics are being paired with health care data, sociodemographic data, unemployment numbers and business establishment data, building a richer set of metrics to help understand how COVID-19 is affecting our society and how to design and implement necessary policies.
“COVID-19 is a complex challenge with broad-ranging impact,” said Clark School Professor Darryll J. Pines, who will become president of the university in July after 11 years as Clark School dean. “One of our strengths at UMD is our ability to bring together knowledge from varied disciplines—in this case, transportation engineering, public health, data analytics and economics—to address problems that are complex by nature.”
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