Evidence map›Paper›PMID 35316127›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2022

Public health implications of opening National Football League stadiums during the COVID-19 pandemic.

Bernardo García Bulle, Dennis Shen, Devavrat Shah, Anette E Hosoi

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Bernardo García BulleInstitute for Data, Systems and Society, Massachusetts Institute of Technology, Cambridge, MA 02139.
Dennis ShenSimons Institute for the Theory of Computing, Melvin Calvin Laboratory, University of California, Berkeley, CA 94720.
Devavrat ShahInstitute for Data, Systems and Society, Massachusetts Institute of Technology, Cambridge, MA 02139.ORCID 0000-0003-0737-3259
Anette E HosoiInstitute for Data, Systems and Society, Massachusetts Institute of Technology, Cambridge, MA 02139.ORCID 0000-0003-4940-7496

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

SignificanceUsing data from 2020, we measure the public health impact of allowing fans into sports stadiums during the COVID-19 pandemic; these results may inform future policy decisions regarding large outdoor gatherings during public health crises. Second, we demonstrate the utility of robust synthetic control in this context. Synthetic control and other statistical approaches may be used to exploit the underlying low-dimensional structure of the COVID-19 data and serve as useful instruments in analyzing the impact of mitigation strategies adopted by different communities. As with all statistical methods, reliable outcomes depend on proper implementation strategies and well-established robustness tests; in the absence of these safeguards, these statistical methods are likely to produce specious or misleading conclusions.

Indexed as

FootballPandemicsPublic HealthCOVID-19HumansPublic Health SurveillanceCOVID-19pandemic policiessports stadiumssynthetic control

Identifiers

PMID35316127
PMCPMC9168482

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.