Capacity restrictions at highly trafficked indoor businesses could have an outsized effect on slowing the spread of COVID-19, as well as reducing the economic and racial disparities of the pandemic, according to a new study.
Certain “super-spreader” locations, such as restaurants, gyms and grocery stores, made up just 10% of all “points of interest” but accounted for 85% of infections modeled in the study published Tuesday in the Nature peer-reviewed journal and included researchers from Stanford as well as the Chan-Zuckerberg Biohub.
The researchers built a model to study the potential impact of precise public health interventions, in contrast to full-scale economic shutdowns or no measures at all, using census, business-classification and cellphone mobility data between March 1-May 2.
Full-service restaurants proved to result in three times as many infections as any other business, according to the model, and even limited-service restaurants were among the worst spreaders of disease. The other worst offenders included fitness centers, hotels, cafes and religious organizations.
The same establishments in lower-income neighborhoods also were more likely to result in infection than those in high-income areas. Grocery stores, in particular, proved to be twice as likely to spread the virus in low-income neighborhoods than their higher-income counterparts. That is because, the researchers write, those stores allowed far more shoppers inside — 59% more per square foot — and those shoppers stayed in the store for 17% longer, on average.
Overall, businesses in lower-income communities received 27% more visitors per-capita, increasing the risk of infection.
Previous research has shown COVID-19 to spread most easily in tightly packed, poorly ventilated indoor spaces. The new data, which includes 98 million people in 10 metro areas and 5.4 billion hour intervals, offers the most specific and comprehensive look yet at which type of businesses result in the highest number of infections.
As San Francisco pulls the plug on indoor dining and parts of California move backward in its tiered reopening system, the research will be just the latest data point used to determine how to keep the local economy churning without providing a vector for the virus.
A scenario where the Chicago metro area reopened its restaurants without restrictions would result in an additional 596,000 infections within a month, according to the model. Whereas a 20% limit on occupancy would result in 80% fewer infections, but only 42% fewer visits.
That is because, the researchers write, the restrictions reduce the density of the crowd inside at peak hours, dramatically lowering the risk of infection, while encouraging others to visit at other, less busy times.
“These results support earlier findings that precise interventions, like reducing maximum occupancy, may be more effective than less targeted measures, while incurring substantially lower economic costs,” the researchers write.
Targeted capacity restrictions is one of a few suggestions made by the researchers to reduce the inequity of the impact of COVID-19.
Others include emergency food distribution centers, which they say would reduce density in high-risk stores; free, widely available testing in high-risk neighborhoods; policies, such as paid leave, that allow low-income workers to stay home while sick; and upgrades to personal protective equipment and ventilation in workplaces.
“These findings highlight how fine-grained differences in mobility patterns — how often people go out and which (places) they go to — can ultimately contribute to dramatic disparities in predicted infection outcomes,” the researchers wrote.
