Reducing uncertainty in within-host parameter estimates of influenza infection by measuring both infectious and total viral load.

For in vivo studies of influenza dynamics where within-host measurements are fit with a mathematical model, infectivity assays (e.g. 50% tissue culture infectious dose; TCID50) are often used to estimate the infectious virion concentration over time. Less frequently, measurements of the total (infec...

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Autores principales:	Stephen M Petrie, Teagan Guarnaccia, Karen L Laurie, Aeron C Hurt, Jodie McVernon, James M McCaw
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2013
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/3f887a85c800406bacc3e6f5cdb407ea
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spelling	oai:doaj.org-article:3f887a85c800406bacc3e6f5cdb407ea2021-11-18T07:45:37ZReducing uncertainty in within-host parameter estimates of influenza infection by measuring both infectious and total viral load.1932-620310.1371/journal.pone.0064098https://doaj.org/article/3f887a85c800406bacc3e6f5cdb407ea2013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23691157/?tool=EBIhttps://doaj.org/toc/1932-6203For in vivo studies of influenza dynamics where within-host measurements are fit with a mathematical model, infectivity assays (e.g. 50% tissue culture infectious dose; TCID50) are often used to estimate the infectious virion concentration over time. Less frequently, measurements of the total (infectious and non-infectious) viral particle concentration (obtained using real-time reverse transcription-polymerase chain reaction; rRT-PCR) have been used as an alternative to infectivity assays. We investigated the degree to which measuring both infectious (via TCID50) and total (via rRT-PCR) viral load allows within-host model parameters to be estimated with greater consistency and reduced uncertainty, compared with fitting to TCID50 data alone. We applied our models to viral load data from an experimental ferret infection study. Best-fit parameter estimates for the "dual-measurement" model are similar to those from the TCID50-only model, with greater consistency in best-fit estimates across different experiments, as well as reduced uncertainty in some parameter estimates. Our results also highlight how variation in TCID50 assay sensitivity and calibration may hinder model interpretation, as some parameter estimates systematically vary with known uncontrolled variations in the assay. Our techniques may aid in drawing stronger quantitative inferences from in vivo studies of influenza virus dynamics.Stephen M PetrieTeagan GuarnacciaKaren L LaurieAeron C HurtJodie McVernonJames M McCawPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 8, Iss 5, p e64098 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Stephen M Petrie Teagan Guarnaccia Karen L Laurie Aeron C Hurt Jodie McVernon James M McCaw Reducing uncertainty in within-host parameter estimates of influenza infection by measuring both infectious and total viral load.
description	For in vivo studies of influenza dynamics where within-host measurements are fit with a mathematical model, infectivity assays (e.g. 50% tissue culture infectious dose; TCID50) are often used to estimate the infectious virion concentration over time. Less frequently, measurements of the total (infectious and non-infectious) viral particle concentration (obtained using real-time reverse transcription-polymerase chain reaction; rRT-PCR) have been used as an alternative to infectivity assays. We investigated the degree to which measuring both infectious (via TCID50) and total (via rRT-PCR) viral load allows within-host model parameters to be estimated with greater consistency and reduced uncertainty, compared with fitting to TCID50 data alone. We applied our models to viral load data from an experimental ferret infection study. Best-fit parameter estimates for the "dual-measurement" model are similar to those from the TCID50-only model, with greater consistency in best-fit estimates across different experiments, as well as reduced uncertainty in some parameter estimates. Our results also highlight how variation in TCID50 assay sensitivity and calibration may hinder model interpretation, as some parameter estimates systematically vary with known uncontrolled variations in the assay. Our techniques may aid in drawing stronger quantitative inferences from in vivo studies of influenza virus dynamics.
format	article
author	Stephen M Petrie Teagan Guarnaccia Karen L Laurie Aeron C Hurt Jodie McVernon James M McCaw
author_facet	Stephen M Petrie Teagan Guarnaccia Karen L Laurie Aeron C Hurt Jodie McVernon James M McCaw
author_sort	Stephen M Petrie
title	Reducing uncertainty in within-host parameter estimates of influenza infection by measuring both infectious and total viral load.
title_short	Reducing uncertainty in within-host parameter estimates of influenza infection by measuring both infectious and total viral load.
title_full	Reducing uncertainty in within-host parameter estimates of influenza infection by measuring both infectious and total viral load.
title_fullStr	Reducing uncertainty in within-host parameter estimates of influenza infection by measuring both infectious and total viral load.
title_full_unstemmed	Reducing uncertainty in within-host parameter estimates of influenza infection by measuring both infectious and total viral load.
title_sort	reducing uncertainty in within-host parameter estimates of influenza infection by measuring both infectious and total viral load.
publisher	Public Library of Science (PLoS)
publishDate	2013
url	https://doaj.org/article/3f887a85c800406bacc3e6f5cdb407ea
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Reducing uncertainty in within-host parameter estimates of influenza infection by measuring both infectious and total viral load.

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