Evidence map›Paper›PMID 37968375›Full record

ArticleAmerican journal of epidemiology2024

The Landscape of Observational COVID-19 Cohort Studies Funded by the National Institute of Allergy and Infectious Diseases.

Reed S Shabman, Mason Booth, Michael Cooper, Marciela M DeGrace, Patricia C Fulkerson, Teresa Hauguel, Chelsea Lane, Alyssa Meyer, Lori Newman, Diane Post and 6 more

Abstract read
In one paragraph

Article in American journal of epidemiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

16 authors.

Reed S Shabman
Mason Booth
Michael Cooper
Marciela M DeGrace
Patricia C Fulkerson
Teresa Hauguel
Chelsea Lane
Alyssa Meyer
Lori Newman
Diane Post
Mercy Prabhudas
Rubya Qidwai
Cynthia Rojas
Claire Schuster
Carolyn Williams
Liliana Brown

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) since late 2019 represented an unprecedented public health emergency, which included a need to fully understand coronavirus disease 2019 (COVID-19) across all ages and populations. In response, the US National Institute of Allergy and Infectious Diseases (NIAID) rapidly funded epidemiology studies that monitored COVID-19. However, the diversity and breadth of the populations studied in NIAID-funded COVID-19 observational cohorts were not easy to extrapolate because of siloed approaches to collect and report data within NIAID. Here, we describe the effort to develop a harmonized cohort-study reporting tool that includes common epidemiologic data elements as well as NIAID priorities. We report its implementation to analyze metadata from 58 COVID-19 cohort studies funded from February 2020 to June 2021, and we visualize key metadata, including geographic distribution, study duration, participant demographic characteristics, sample types collected, and scientific priorities addressed. A bibliographic analysis highlights the scientific publications and citations across these funded studies and demonstrates their enormous impact on the COVID-19 field. These analyses highlight how common data elements and reporting tools can assist funding agencies to capture the landscape and potential gaps during public health responses and how they can assist in decision making.

Indexed as

COVID-19National Institute of Allergy and Infectious Diseases (U.S.)Cohort StudiesHumansMetadataObservational Studies as TopicSARS-CoV-2United Statescohort studiesCOVID-19epidemiologynatural history studiesNIAID

Identifiers

PMID37968375
PMCPMC11484646

What OpenQuestion holds

Textmetadata
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.