The reopening of restaurants, gyms and hotels poses the greatest risk of the spread of Covid-19. This is the result of a study in which the risk of infection at different locations was modeled using cell phone data from 98 million people.
Researchers at Stanford University and Northwestern University used data collected between March and May in cities across the United States to map the movement of people. They looked where they were going, how long they stayed, how many others were there and what parts of town they came from. They then combined this information with data on the number of cases and the spread of the virus to create infection models.
In Chicago, for example, the study model predicted that if restaurants reopened fully, they would cause nearly 600,000 new infections, three times as many as other categories. The study, published Tuesday in the journal Nature, also found that around 10% of the sites studied accounted for 85% of the predicted infections.
This kind of very detailed data “shows us where there is a vulnerability,” said Eric Topol of the Scripps Research Translational Institute, who was not involved in the study. “Then you have to focus on the areas that light up.”
Marc Lipsitch and Kevin Ma from Harvard T.H. The Chan School of Public Health wrote that there is limited epidemiological data on how interventions contain infection. Such models could serve as a starting point for policy decisions about the reopening.
The models created in the study reported Tuesday also suggested that full locks are not required to keep the virus at bay. Masks, social distancing, and reduced capacity can all play an important role in keeping things under control.
By limiting the occupancy rate to 20% at locations in the Chicago metropolitan area, the new infections forecast in the study could be reduced by more than 80%. And since the occupancy caps primarily only affected the number of visits, which normally take place during peak hours, the restaurants lost only 42% of guests overall.
Reducing the maximum occupancy numbers, the study found, may be more effective than less targeted measures to contain the virus, while also offering economic benefits.
“We need to think about strategies to reopen the economy,” said Jure Leskovec, computer scientist and lead author at Stanford University. “In this way, we can test different reopening scenarios and assess what that would mean for the spread of the virus.”
Without virus mitigation measures, they would have predicted that a third of the population could be infected with the virus. When fitting their model to publicly available data for the daily number of infections, the researchers found that it could predict epidemic trajectories better than other models.
The model also suggests how effective lockdown measures in public spaces can be by identifying infections and the use of those spaces over time as cities put lockdowns in place.
In Miami, for example, infections modeled by hotels peaked around the same time the city hit the headlines for wild beach parties during the spring break, which prevailed despite the pandemic. However, those predictions dwindled significantly when the lockdown measures went into effect.
The work also predicted an inequality in infections between income groups. Lower-income populations are more likely to be infected because they are more likely to visit smaller, crowded places and are less likely to affect their mobility overall.
The idea that restaurants may trigger a new wave of infections when they open is not unique to this study. JPMorgan Chase & Co. announced Monday that the level of personal spending in restaurants three weeks ago was the strongest indicator of where new cases would arise.
Similarly, higher spending in supermarkets indicated slower prevalence, suggesting shoppers in these regions may be more cautious, according to researchers at the bank who track the spending of 30 million Chase credit and debit card holders.
Topol said his view was that all of these layers of data could be combined into a national virus dashboard that could help policymakers develop smarter and more targeted virus reduction policies. He’s been in favor of using fitness trackers to flag potential virus hotspots.
Leskovec said his team is currently working on developing a tool that officials could use to make reopening decisions.
“More model tests are needed,” wrote Ma and Lipsitch in their opinion piece. “However, given the challenges of collecting and interpreting other relevant types of data, these results could play an important role in decision-making for safely reopening and minimizing society.” the damage caused by restricted mobility. “
(Except for the headline, this story was not edited by GossipMantri staff and posted from a syndicated feed.)