Evidence map›Paper›PMID 36962401›Full record

ArticlePLOS global public health2022

Fast Evaluation of Viral Emerging Risks (FEVER): A computational tool for biosurveillance, diagnostics, and mutation typing of emerging viral pathogens.

Zachary R Stromberg, James Theiler, Brian T Foley, Adán Myers Y Gutiérrez, Attelia Hollander, Samantha J Courtney, Jason Gans, Alina Deshpande, Ebany J Martinez-Finley, Jason Mitchell and 3 more

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In one paragraph

Article in PLOS global public health, 2022. 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. Review
  2. Review
  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

13 authors.

Zachary R StrombergPhysical Chemistry and Applied Spectroscopy, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.ORCID https://orcid.org/0000-0002-1137-1128
James TheilerSpace Data Science and Systems, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.ORCID https://orcid.org/0000-0003-1888-3684
Brian T FoleyTheoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.ORCID https://orcid.org/0000-0002-1086-0296
Adán Myers Y GutiérrezBiosecurity and Public Health, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.ORCID https://orcid.org/0000-0002-3457-1632
Attelia HollanderBiosecurity and Public Health, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.ORCID https://orcid.org/0000-0002-6347-8074
Samantha J CourtneyPhysical Chemistry and Applied Spectroscopy, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.ORCID https://orcid.org/0000-0001-9277-2937
Jason GansBiosecurity and Public Health, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.
Alina DeshpandeBiosecurity and Public Health, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.ORCID https://orcid.org/0000-0003-4541-4410
Ebany J Martinez-FinleyPresbyterian Healthcare Services, Albuquerque, New Mexico, United States of America.ORCID https://orcid.org/0000-0002-2639-9107
Jason MitchellPresbyterian Healthcare Services, Albuquerque, New Mexico, United States of America.
Harshini MukundanPhysical Chemistry and Applied Spectroscopy, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.ORCID https://orcid.org/0000-0002-0931-0545
Karina YusimTheoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.
Jessica Z Kubicek-SutherlandPhysical Chemistry and Applied Spectroscopy, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.ORCID https://orcid.org/0000-0001-6215-4871

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Viral pathogens can rapidly evolve, adapt to novel hosts, and evade human immunity. The early detection of emerging viral pathogens through biosurveillance coupled with rapid and accurate diagnostics are required to mitigate global pandemics. However, RNA viruses can mutate rapidly, hampering biosurveillance and diagnostic efforts. Here, we present a novel computational approach called FEVER (Fast Evaluation of Viral Emerging Risks) to design assays that simultaneously accomplish: 1) broad-coverage biosurveillance of an entire group of viruses, 2) accurate diagnosis of an outbreak strain, and 3) mutation typing to detect variants of public health importance. We demonstrate the application of FEVER to generate assays to simultaneously 1) detect sarbecoviruses for biosurveillance; 2) diagnose infections specifically caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); and 3) perform rapid mutation typing of the D614G SARS-CoV-2 spike variant associated with increased pathogen transmissibility. These FEVER assays had a high in silico recall (predicted positive) up to 99.7% of 525,708 SARS-CoV-2 sequences analyzed and displayed sensitivities and specificities as high as 92.4% and 100% respectively when validated in 100 clinical samples. The D614G SARS-CoV-2 spike mutation PCR test was able to identify the single nucleotide identity at position 23,403 in the viral genome of 96.6% SARS-CoV-2 positive samples without the need for sequencing. This study demonstrates the utility of FEVER to design assays for biosurveillance, diagnostics, and mutation typing to rapidly detect, track, and mitigate future outbreaks and pandemics caused by emerging viruses.

Identifiers

PMID36962401
PMCPMC10021650

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LicenceCC BY
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identifiers read7
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.