Tracking the Spread

New tool can detect COVID-19 outbreaks in U.S. counties that host in-person football events

Photo of a football field with a ball, mask, sanitizer

Using an AI-based tool, researchers noted that 17 of 33 NFL and NCAA games played by late September with fans in attendance were located in counties with rising COVID-19 cases at the time of the game.  Image: ronniechua/iStock

This article is part of Harvard Medical School’s continuing coverage of medicine, biomedical research, medical education and policy related to the SARS-CoV-2 pandemic and the disease COVID-19.

Recent U.S. outbreaks of COVID-19 have been detected following in-person attendance at football games, which have the potential to become “super spreader” events, according to research using artificial intelligence tools.  

Using an AI-based COVID-19 Outbreak Detection Tool, researchers at Massachusetts General Hospital, Harvard Medical School, Georgia Tech and Boston Medical Center noted that 17 of 33 NFL and NCAA games played by late September with fans in attendance were located in counties with rising COVID-19 cases at the time of the game.

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One of those games, the Denver Broncos vs. the Tampa Bay Buccaneers at Empower Field in Denver, took place on Sept. 27.

“Our model indicated that the county where the game was played had a COVID-19 doubling time of two to three weeks and nearly 700 total new cases in the county during the week before the game was played,” said Jagpreet Chhatwal, assistant professor of radiology at HMS and associate director of the MGH Institute for Technology Assessment.

“This example highlights how officials may use this tool to make informed decisions on the safety of future in-person attendance by taking into account both past week trends as well as predicted trends,” Chhatwal said.

Because the National Football League and the National Collegiate Athletic Association have made the decision to play games amid the ongoing COVID-19 pandemic, the researchers have extended the use of the COVID-19 Outbreak Detection Tool to incorporate NFL and NCAA football games. The model can help public officials and team owners in their decision-making regarding in-person attendance.

The tool provides predicted trends such as the COVID-19 doubling time, or the number of days it takes for COVID-19 cases to double, and how fast COVID-19 cases are increasing in counties with NFL or NCAA stadiums that have hosted games or might host games in the future.

The investigators will add information on the attendance numbers for each game, which can indicate the potential risk of infection spread in surrounding communities. 

“Public health officials can work alongside team executives to continuously assess the situation of the county where the games are being played, along with neighboring counties, to guide their decision-making with respect to when to allow fans back in the stadiums, whether to allow fans from other counties and states to attend and when to discontinue fan attendance,” said Asmae Toumi, a data analyst at the MGH Institute for Technology Assessment.

“Officials can also view the individual stadium capacity as well as the total stadium capacity of the county or state, which can inform decisions on how many fans can attend,” Toumi said.

Collaborators include Zhaowei She, Zilong Wang and Turgay Ayer from Georgia Tech; Madeline Adee and Mary Ann Ladd from Mass General and Benjamin Linas from Boston Medical Center.