Identifiability investigation of within-host models of acute virus infection

dc.contributor.authorLiyanage, Yuganthi R.en
dc.contributor.authorHeitzman-Breen, Noraen
dc.contributor.authorTuncer, Necibeen
dc.contributor.authorCiupe, Stanca M.en
dc.date.accessioned2025-01-09T19:28:30Zen
dc.date.available2025-01-09T19:28:30Zen
dc.date.issued2024-05-10en
dc.description.abstractUncertainty in parameter estimates from fitting within-host models to empirical data limits the model's ability to uncover mechanisms of infection, disease progression, and to guide pharmaceutical interventions. Understanding the effect of model structure and data availability on model predictions is important for informing model development and experimental design. To address sources of uncertainty in parameter estimation, we use four mathematical models of influenza A infection with increased degrees of biological realism. We test the ability of each model to reveal its parameters in the presence of unlimited data by performing structural identifiability analyses. We then refine the results by predicting practical identifiability of parameters under daily influenza A virus titers alone or together with daily adaptive immune cell data. Using these approaches, we present insight into the sources of uncertainty in parameter estimation and provide guidelines for the types of model assumptions, optimal experimental design, and biological information needed for improved predictions.en
dc.description.versionPublished versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.doihttps://doi.org/10.1101/2024.05.09.593464en
dc.identifier.eissn2692-8205en
dc.identifier.issn2692-8205en
dc.identifier.issue05-17en
dc.identifier.orcidCiupe, Mihaela [0000-0002-5386-6946]en
dc.identifier.otherPMC11100786en
dc.identifier.other2024.05.09.593464 (PII)en
dc.identifier.urihttps://hdl.handle.net/10919/124026en
dc.identifier.volume5en
dc.language.isoenen
dc.publisherAIMS Pressen
dc.relation.urihttps://www.ncbi.nlm.nih.gov/pubmed/38766177en
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.titleIdentifiability investigation of within-host models of acute virus infectionen
dc.title.serialMathematical Biosciences and Engineeringen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten
dc.type.otherJournal Articleen
dc.type.otherPreprinten
dcterms.dateAccepted2024-05-10en
pubs.organisational-groupVirginia Techen
pubs.organisational-groupVirginia Tech/Scienceen
pubs.organisational-groupVirginia Tech/Science/Mathematicsen
pubs.organisational-groupVirginia Tech/All T&R Facultyen
pubs.organisational-groupVirginia Tech/Science/COS T&R Facultyen

Files

Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
10.3934_mbe.2024325.pdf
Size:
1.74 MB
Format:
Adobe Portable Document Format
Description:
Published version
License bundle
Now showing 1 - 1 of 1
Name:
license.txt
Size:
1.5 KB
Format:
Plain Text
Description: