Evidence map›Paper›PMID 37054986›Full record

ArticleEmerging infectious diseases2023

US National Institutes of Health Prioritization of SARS-CoV-2 Variants.

Sam Turner, Arghavan Alisoltani, Debbie Bratt, Liel Cohen-Lavi, Bethany L Dearlove, Christian Drosten, Will M Fischer, Ron A M Fouchier, Ana Silvia Gonzalez-Reiche, Lukasz Jaroszewski and 24 more

Abstract read
In one paragraph

Article in Emerging infectious diseases, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

34 authors.

Sam Turner
Arghavan Alisoltani
Debbie Bratt
Liel Cohen-Lavi
Bethany L Dearlove
Christian Drosten
Will M Fischer
Ron A M Fouchier
Ana Silvia Gonzalez-Reiche
Lukasz Jaroszewski
Zain Khalil
Eric LeGresley
Marc Johnson
Terry C Jones
Barbara Mühlemann
David O'Connor
Mayya Sedova
Maulik Shukla
James Theiler
Zachary S Wallace
Hyejin Yoon
Yun Zhang
Harm van Bakel
Marciela M Degrace
Elodie Ghedin
Adam Godzik
Tomer Hertz
Bette Korber
Jacob Lemieux
Anna M Niewiadomska
Diane J Post
Morgane Rolland
Richard Scheuermann
Derek J Smith

Funding

Viral Genomics: evolution, spread, and host interactionsU19AI110818 · NIAID · BROAD INSTITUTE, INC. · PI NEAFSEY, DANIEL E · 2014 to 2024
$66.5M
NIAID Centers of Excellence for Influenza Research and Response: Universal Influenza Vaccine Research Activities75N93021C00014 · NIAID · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI GARCIA-SASTRE, ADOLFO · 2021 to 2025
$62.6M
Conduits: Mount Sinai Health System Translational Science HubUL1TR004419 · NCATS · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI Rosalind J Wright · 2022 to 2026
$46.4M
BIOINFORMATICS RESOURCE CENTERS FOR INFECTIOUS DISEASES: SARS-CoV-2 ACTIVITIES75N93019C00076 · NIAID · UNIVERSITY OF CHICAGO · PI STEVENS, RICK · 2019 to 2023
$32.6M
IMMUNOLOGY QUALITY ASSESSMENT (IQA) PROGRAM75N93021C00010 · NIAID · DUKE UNIVERSITY · PI DENNY, THOMAS · 2021 to 2025
$9.1M
Optimizing glycan shield coverage, germline B cell receptor binding and epitope diversity of V2-apex targeted HIV-1 Env immunogensR37AI150590 · NIAID · UNIVERSITY OF PENNSYLVANIA · PI Beatrice H Hahn · 2019 to 2026
$6.9M
Wastewater Detection of COVID-19U01DA053893 · NIDA · MISSOURI STATE DEPT/ HEALTH & SENIOR SRV · PI WENZEL, JEFF · 2021 to 2022
$4.0M
Determining factors of transmission and evolution of SARS-CoV-2 in populations at risk ZIAAI001324 · NIAID · NATIONAL INSTITUTE OF ALLERGY AND INFECTIOUS DISEASES · PI GHEDIN, ELODIE · 2020 to 2025
$2.7M
COVID and Translational Science supercomputer (CATS)S10OD030463 · OD · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI KOVATCH, PATRICIA · 2021 to 2021
$2.0M
Big Omics Data Engine 2 SupercomputerS10OD026880 · OD · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI KOVATCH, PATRICIA · 2019 to 2019
$2.0M
NCATS NIH HHS UL1 TR004419NIAID NIH HHS 75N93019C00076NIAID NIH HHS 75N93021C00010NIAID NIH HHS 75N93021C00014NIAID NIH HHS HHSN272201400008CNIAID NIH HHS HHSN272201700060CNIAID NIH HHS R37 AI150590NIAID NIH HHS U19 AI110818NIDA NIH HHS U01 DA053893NIH HHS S10 OD026880NIH HHS S10 OD030463
6 · The paper itself

Abstract

Since late 2020, SARS-CoV-2 variants have regularly emerged with competitive and phenotypic differences from previously circulating strains, sometimes with the potential to escape from immunity produced by prior exposure and infection. The Early Detection group is one of the constituent groups of the US National Institutes of Health National Institute of Allergy and Infectious Diseases SARS-CoV-2 Assessment of Viral Evolution program. The group uses bioinformatic methods to monitor the emergence, spread, and potential phenotypic properties of emerging and circulating strains to identify the most relevant variants for experimental groups within the program to phenotypically characterize. Since April 2021, the group has prioritized variants monthly. Prioritization successes include rapidly identifying most major variants of SARS-CoV-2 and providing experimental groups within the National Institutes of Health program easy access to regularly updated information on the recent evolution and epidemiology of SARS-CoV-2 that can be used to guide phenotypic investigations.

Indexed as

COVID-19SARS-CoV-2HumansNational Institutes of Health (U.S.)United States2019 novel coronavirus diseasecomputational biologycoronavirus diseaseCOVID-19epidemiological monitoringepidemiologypandemic prevention and controlrespiratory infectionsSARS-CoV-2SARS-CoV-2 variantssevere acute respiratory syndrome coronavirus 2US National Institute of Allergy and Infectious DiseasesUS National Institutes of Healthviruseszoonoses

Identifiers

PMID37054986
PMCPMC10124642

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.