Are football games with limited in-person attendance associated with increased county-level COVID-19 cases?
This cross-sectional study of US counties that hosted National Football League and National Collegiate Athletic Association football games used a matching and difference-in-differences design to estimate the association of games with limited in-person attendance with county-level COVID-19 spread. There was no association between higher county-level COVID-19 cases and hosting football games with limited in-person attendance.
This study suggests that football games held with limited in-person attendance were not associated with increased COVID-19 cases in the counties they were held.
In 2020 and early 2021, the National Football League (NFL) and National Collegiate Athletic Association (NCAA) opted to host football games in stadiums across the country. The in-person attendance of games varied with time and from county to county. There is currently no evidence on whether limited in-person attendance of games is associated with COVID-19 case numbers on a county-level.
To assess whether NFL and NCAA football games with limited in-person attendance were associated with increased COVID-19 cases in the counties they were held compared with a matched set of counties.
Design, Setting, and Participants
In this time-series cross-sectional study, every county hosting NFL or NCAA games with in-person attendance (treated group) in 2020 and 2021 was matched with a county that that did not host a game on the corresponding day but had an identical game history for up to 14 days prior (control group). A standard matching method was used to further refine this matched set so that the treated and matched control counties had similar population size, nonpharmaceutical interventions in place, and COVID-19 trends. The association of hosting games with in-person attendance with COVID-19 cases was assessed using a difference-in-difference estimator. Data were analyzed from August 29 to December 28, 2020.
Hosting NFL or NCAA games.
Main Outcomes and Measures
The main outcome was estimation of new COVID-19 cases per 100 000 residents at the county level reported up to 14 days after a game among counties with NFL and NCAA games with in-person attendance.
A total of 528 games with in-person attendance (101 NFL games [19.1%]; 427 NCAA games [80.9%]) were included. The matching algorithm returned 361 matching sets of counties. The median (interquartile range [IQR]) number of attendance for NFL games was 9949 (6000 to 13 797) people. The median number of attendance for NCAA games was not available, and attendance was recorded as a binary variable. The median (IQR) daily new COVID-19 cases in treatment group counties hosting games was 26.14 (10.77-50.25) cases per 100 000 residents on game day. The median (IQR) daily new COVID-19 cases in control group counties where no games were played was 24.11 (9.64-48.55) cases per 100 000 residents on game day. The treatment effect size ranged from −5.17 to 4.72, with a mean (SD) of 1.21 (2.67) cases per 100 000 residents, within the 14-day period in all counties hosting the games, and the daily treatment effect trend remained relatively steady during this period.
Conclusions and Relevance
This cross-sectional study did not find a consistent increase in the daily COVID-19 cases per 100 000 residents in counties where NFL and NCAA games were held with limited in-person attendance. These findings suggest that NFL and NCAA football games hosted with limited in-person attendance were not associated with substantial risk for increased local COVID-19 cases.
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CME Disclosure Statement: Unless noted, all individuals in control of content reported no relevant financial relationships. If applicable, all relevant financial relationships have been mitigated.
Accepted for Publication: May 30, 2021.
Published: August 17, 2021. doi:10.1001/jamanetworkopen.2021.19621
Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2021 Toumi A et al. JAMA Network Open.
Corresponding Author: Turgay Ayer, PhD, Georgia Institute of Technology, 765 Ferst Dr, Atlanta, GA 30332 (email@example.com).
Author Contributions: Ms Toumi had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Ms Toumi and Ms Zhao are co–first authors.
Concept and design: Toumi, Zhao, Chhatwal, Ayer.
Acquisition, analysis, or interpretation of data: All authors.
Drafting of the manuscript: All authors.
Critical revision of the manuscript for important intellectual content: All authors.
Statistical analysis: Toumi, Zhao, Ayer.
Obtained funding: Chhatwal, Linas, Ayer.
Administrative, technical, or material support: Toumi, Zhao, Chhatwal.
Supervision: Chhatwal, Linas, Ayer.
Conflict of Interest Disclosures: Dr Chhatwal reported receiving personal fees from Value Analytics Labs outside the submitted work. Dr Ayer reported serving as a managing partner at Value Analytics Labs outside the submitted work. No other disclosures were reported.
Funding/Support: This work was supported by award Nos. 2035360 and 2035361 from the National Science Foundation, and grant No. GBMF9634 from the Gordon and Betty Moore Foundation, paid to Johns Hopkins University to support the work of the Society for Medical Decision Making COVID-19 Decision Modeling Initiative.
Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
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