Evidence map›Paper›PMID 34578396›Full record

ArticleViruses2021

Personalized Virus Load Curves for Acute Viral Infections.

Carlos Contreras, Jay M Newby, Thomas Hillen

Abstract read
In one paragraph

Article in Viruses, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. 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

3 authors.

Carlos ContrerasDepartment of Mathematical and Statistical Sciences, University of Alberta, Edmonton, AB T6G 2R3, Canada.ORCID 0000-0001-7928-607X
Jay M NewbyDepartment of Mathematical and Statistical Sciences, University of Alberta, Edmonton, AB T6G 2R3, Canada.ORCID 0000-0001-9988-2020
Thomas HillenDepartment of Mathematical and Statistical Sciences, University of Alberta, Edmonton, AB T6G 2R3, Canada.ORCID 0000-0003-0819-9520

Funding

Natural Sciences and Engineering Research Council of Canada RGPIN-2017-04158Natural Sciences and Engineering Research Council of Canada RGPIN-2019-06435
6 · The paper itself

Abstract

We introduce an explicit function that describes virus-load curves on a patient-specific level. This function is based on simple and intuitive model parameters. It allows virus load analysis of acute viral infections without solving a full virus load dynamic model. We validate our model on data from mice influenza A, human rhinovirus data, human influenza A data, and monkey and human SARS-CoV-2 data. We find wide distributions for the model parameters, reflecting large variability in the disease outcomes between individuals. Further, we compare the virus load function to an established

Indexed as

Viral LoadAcute DiseaseAlgorithmsAnimalsBiological Variation, PopulationCOVID-19HumansInfluenza, HumanMacaca mulattaMiceModels, TheoreticalRhinovirusSARS-CoV-2Virus Diseasesmathematical modelingpatient specificSARS-CoV-2viral load

Identifiers

PMID34578396
PMCPMC8472998

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.