Evidence map›Paper›PMID 38617994›Full record

ArticleJAMIA open2024

The Pandemic Response Commons.

Matthew Trunnell, Casey Frankenberger, Bala Hota, Troy Hughes, Plamen Martinov, Urmila Ravichandran, Nirav S Shah, Robert L Grossman, Pandemic Response Commons Consortium

Abstract read
In one paragraph

Article in JAMIA open, 2024. 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

9 authors.

Matthew TrunnellOpen Commons Consortium, Chicago, IL 60607, United States.
Casey FrankenbergerRush University Medical Center, Chicago, IL 60612, United States.
Bala HotaRush University Medical Center, Chicago, IL 60612, United States.
Troy HughesCenter for Translational Data Science, University of Chicago, Chicago, IL 60615, United States.
Plamen MartinovOpen Commons Consortium, Chicago, IL 60607, United States.
Urmila RavichandranNorthShore University HealthSystem, Evanston, IL 60201, United States.
Nirav S ShahNorthShore University HealthSystem, Evanston, IL 60201, United States.ORCID https://orcid.org/0000-0002-9107-7788
Robert L GrossmanCenter for Translational Data Science, University of Chicago, Chicago, IL 60615, United States.ORCID https://orcid.org/0000-0003-3741-5739
Pandemic Response Commons Consortium

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: A data commons is a software platform for managing, curating, analyzing, and sharing data with a community. The Pandemic Response Commons (PRC) is a data commons designed to provide a data platform for researchers studying an epidemic or pandemic. Methods: The PRC was developed using the open source Gen3 data platform and is based upon consortium, data, and platform agreements developed by the not-for-profit Open Commons Consortium. A formal consortium of Chicagoland area organizations was formed to develop and operate the PRC. Results: The consortium developed a general PRC and an instance of it for the Chicagoland region called the Chicagoland COVID-19 Commons. A Gen3 data platform was set up and operated with policies, procedures, and controls for a NIST SP 800-53 revision 4 Moderate system. A consensus data model for the commons was developed, and a variety of datasets were curated, harmonized and ingested, including statistical summary data about COVID cases, patient level clinical data, and SARS-CoV-2 viral variant data. Discussion and conclusions: Given the various legal and data agreements required to operate a data commons, a PRC is designed to be in place and operating at a low level prior to the occurrence of an epidemic, with the activities increasing as required during an epidemic. A regional instance of a PRC can also be part of a broader data ecosystem or data mesh consisting of multiple regional commons supporting pandemic response through sharing regional data.

Indexed as

data commonsdata sharingdata systemspandemicregional data commons

Identifiers

PMID38617994
PMCPMC11009464

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.