This type of data is valuable because it can help public health officials and policymakers create targeted virus response measures to improve both public health and the economy.
For example: predicting future COVID-19 hot spots.
“We hope this would be interesting to look at to potentially tie foot traffic around a particular location for virus spread,” said Justin Tyndall, a UHERO economist and assistant professor.
That’s just one possibility.
The dashboard uses anonymized cell phone location data from SafeGraph, a private company that also works with the U.S. Centers for Disease Control and Prevention, to show the percentage of people who are staying at home all day, and foot traffic to places like restaurants, retail shops and hotels.
Hawaii’s mobility data broken down at the census tract level shows that tracts near the Honolulu International Airport and Ko Olina Resort had low stay-at-home rates on Dec. 13. View the interactive dashboard on UHERO’s website here.
Screenshot-University of Hawaii Economic Research Organization
Broadly, what Hawaii’s data shows is that people have stopped staying at home as much in recent weeks and foot traffic to restaurants and retail establishments is increasing.
Much of what was previously available didn’t break down beyond the county level, which means there wasn’t a whole lot of useful insight for Hawaii. But this data can be broken down by island, zip code or census tracts, which gives researchers much more context, including that the stay-at-home rate for Waikiki residents fell to 25%, compared with the state’s 32%.
It also shows that more recently, people who live near the Honolulu airport have been out of their house more than other areas of Oahu.
Tyndall said his team has not found huge disparities in stay-at-home metrics as they relate to income levels in Hawaii, but there is more research to be done.
Foot traffic loss during the pandemic has been greater for hotels than restaurants and retail establishments, the data also showed. The places with the least amount of mobility even as the state reopened to visitors were educational institutions.
Comparing the foot traffic in certain types of places with spikes in COVID-19 cases could help identify potential virus spread, Tyndall said.
Foot traffic at retail stores in Hawaii is creeping back up, mobility data shows. But it’s still only about 60% of pre-pandemic levels.
SafeGraph’s data is among the most widely used, as it began providing data for free to researchers, journalists and government agencies responding to COVID-19 early on. It’s used by a number of entities, including the California Governor’s Office and various city governments, including Los Angeles, Memphis and Louisville.
The CDC was an early adapter of using mobility data to analyze the movement of communities that are most at risk for COVID-19, identify health care sites that are reaching capacity limits and develop tailored health care messaging.
“This is a really valuable source,” said Victoria Fan, a University of Hawaii public health economist and chair of Hawaii Pandemic Applied Modeling Work Group. It could be especially useful in crafting targeted public health messaging, she said.
But for now, the Hawaii Department of Health doesn’t seem that interested.
Earlier in the pandemic, mobility data was considered a leading indicator for transmission risk, said Brooks Baehr, a department spokesman. But as people went back to work, it became less relevant than other prevention methods, such as hand-washing, physical distancing and wearing a mask.
“It became unreasonable to expect the entire state population to aim for minimal mobility and so the Department of Health did not pursue mobility as a useful predictive indicator for transmission,” he said.
Unacast’s social distancing scorecard is now linked on the Hawaii Emergency Management Agency website.
The Hawaii Emergency Management Agency features the Unacast Social Distancing Scorecard on its website, though. Hawaii’s grade is a D, a slight upgrade from the D- last summer.
Fan said mobility data can be misused. “You don’t want this type of data to be used as a penalty when obviously, working class communities have to move more.”
The data itself may include biases that need to be taken into account; a joint audit by Stanford and Carnegie Mellon universities found that smartphone-based mobility datasets, including SafeGraph’s, aren’t so good at capturing older, nonwhite people.
As with all things COVID-19 and the data surrounding it, there are limitations, but datasets such as these can help inform not just the public, but also legislators, Fan said.
“I think it can help people make better decisions,” she said.
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