The reopening of restaurants, gyms and hotels carries the highest risk of spreading Covid-19, according to a study that used mobile phone data from 98 million people to model the risks of infection at different locations.
Researchers at Stanford University and Northwestern University used data collected between March and May in cities across the U.S. to map the movement of people. They looked at where they went, how long they stayed, how many others were there and what neighbourhoods they were visiting from. They then combined that information with data on the number of cases and how the virus spreads to create infection models.
In Chicago, for instance, the study’s model predicted that if restaurants were reopened at full capacity, they would generate almost 600,000 new infections, three times as many as with other categories. The study, published Tuesday in the journal Nature, also found that about 10% of the locations examined accounted for 85% of predicted infections.
This type of very granular data “shows us where there is vulnerability,” said Eric Topol, of the Scripps Research Translational Institute, which wasn’t involved in the study. “Then what you need to do is concentrate on the areas that light up.”
In a concurrent opinion piece published in Nature, Marc Lipsitch and Kevin Ma at the Harvard T.H. Chan School of Public Health, wrote that there is limited epidemiological data on how interventions curb infection. Such models, they said, can act as a starting point to guide policy decisions about reopening.
The models produced in the study reported Tuesday also suggested that full-blown lockdowns aren’t necessary to hold the virus at bay. Masks, social distancing and reduced capacity all can play a major role in keeping things under control.
Capping occupancy at 20% in locations in the Chicago metro area cut down on predicted new infections in the study by more than 80%. And because the occupancy caps primarily only impacted the number of visits that typically occur during peak hours, the restaurants only lost 42% of patrons overall.
Reducing maximum occupancy numbers, the study suggested, may be more effective than less targeted measures at curbing the virus, while also offering economic benefit.
“We need to be thinking about strategies for reopening the economy,” said Jure Leskovec, a Stanford University computer scientist and lead author on the paper. “This allows us to test different reopening scenarios and assess what that would mean for the spread of the virus.”
Without virus mitigation measures, he said, they predicted that a third of the population might be infected with the virus. When they fit their model to publicly available data for the daily number of infections, the researchers found it could predict epidemic trajectories better than other models.
The model also suggests just how effective lock-down measures can be in public spaces by noting infections and the use of those spaces over time as cities put lockdowns into effect.
In Miami, for example, infections modeled from hotels peaked around the same time the city was grabbing headlines for wild spring-break beach parties that prevailed despite the pandemic. But those predictions shrunk significantly as lock-down measures went into effect.
The work also predicted a disparity in infections among income groups. Lower-income populations are more likely to become infected, they found, because they are more likely to visit smaller, more crowded places and less likely to reduce their mobility overall.
The idea that restaurants may be feeding a new wave of infections as they open up isn’t unique to this study. JPMorgan Chase & Co. on Monday said they found the level of in-person spending in restaurants three weeks ago was the strongest predictor of where new cases would emerge.
Similarly, higher spending in supermarkets indicated a slower spread, suggesting shoppers in those regions may be living more cautiously, according to researchers at the bank, which tracks spending of 30 million Chase credit and debit cardholders.
Topol said his view is that all of these layers of data could be combined to create a national virus dashboard that could go far in helping policy makers create smarter, more targeted policies for virus mitigation. He has advocated using fitness trackers as another way to flag potential virus hot spots.
Leskovec said that his team is currently at work building a tool that public officials could use to make reopening decisions.
“Further model testing is needed,” Ma and Lipsitch wrote in their opinion piece, “but given the challenges in gathering and interpreting other relevant data types, these findings could have a valuable role in guiding policy decisions on how to reopen society safely and minimize the harm caused by movement restrictions.”
(This story has been published from a wire agency feed without modifications to the text.)
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