How to stop restaurants from driving COVID infections

Nature:

US mobile data suggests restaurants, gyms and cafes can be COVID hotspots — and reveals strategies for limiting spread.

In cities worldwide, coronavirus outbreaks have been linked to restaurants, cafes and gyms. Now, a new model using mobile-phone data to map people’s movements suggests that these venues could account for most COVID-19 infections in US cities.

The model, published in Nature today, also reveals how reducing occupancy in venues can significantly cut the number of infections.

The model “has concrete pointers as to what may be cost-effective measures to contain the spread of the disease, while at the same time, limiting the damage to the economy”, says Thiemo Fetzer, an economist at the University of Warwick in Coventry. “This is the policy sweet spot.”

Mobility data

To predict how people’s movements might affect viral transmission, the research team input anonymized location data from mobile-phone apps into a simple epidemiological model that estimated how quickly the disease spreads. The location data, collected by SafeGraph, a company based in Denver, Colorado, came from 10 of the largest US cities, including Chicago, Illinois; New York; and Philadelphia, Pennsylvania. It mapped how people moved in and out of 57,000 neighbourhoods to points of interest, such as restaurants, churches, gyms, hotels, car dealers and sporting-goods stores for 2 months starting in March.

When the team compared the model’s number of infections in Chicago neighbourhoods between 8 March and 15 April with the number of infections officially recorded in those neighbourhoods a month later, they found that the model had accurately predicted confirmed case numbers.

“We are able to faithfully estimate the contact network between 100 million people for every hour of the day. That is the secret ingredient we have,” says Leskovec.

Venue hot spots

The team then used the model to simulate different scenarios, such as reopening some venues while keeping others closed. They found that opening restaurants at full capacity led to the largest increase in infections, followed by gyms, cafes and hotels and motels. If Chicago had reopened restaurants on 1 May, there would have been nearly 600,000 additional infections that month, while Opening gyms would have produced 149,000 extra infections. If all venues were open, the model predicts that there would have been 3.3 million additional cases.

But capping occupancy for all venues at 30% would reduce the number of additional infections to 1.1 million, the model estimated. If occupancy was capped at 20%, new infections would be reduced by more than 80% to about 650,000 cases.

“The study highlights how real-time big data on population mobility offers the potential to predict transmission dynamics at unprecedented levels of spatial granularity,” says Neil Ferguson, an epidemiologist at Imperial College London.

Read more at Nature

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