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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Bibliographic Details
Published in:PloS one 2013-05, Vol.8 (5), p.e64098-e64098
Main Authors: Petrie, Stephen M, Guarnaccia, Teagan, Laurie, Karen L, Hurt, Aeron C, McVernon, Jodie, McCaw, James M
Format: Article
Language:English
Subjects:
Animals
Assaying
Biology
Cell death
Comparative analysis
Computer Science
Consistency
Estimates
Experiments
Ferrets
Health aspects
Host-Pathogen Interactions
In vivo methods and tests
Infections
Infectious diseases
Infectivity
Influenza
Influenza viruses
Laboratory animals
Mathematical models
Mathematics
Measurement
Medical research
Medicine
Medicine, Experimental
Models, Biological
Orthomyxoviridae Infections - virology
Parameter estimation
Parameter sensitivity
Parameter uncertainty
Polymerase chain reaction
Real-Time Polymerase Chain Reaction
Reverse Transcriptase Polymerase Chain Reaction
Reverse transcription
Studies
Tissue culture
Uncertainty
Vaccines
Viral Load
Virions
Virology
Viruses
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Summary: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.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0064098