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dc.creatorGonzález-Parra, Gilberto
dc.creatorDobrovolny, Hana M.
dc.date.accessioned2016-09-14T18:45:15Z
dc.date.available2016-09-14T18:45:15Z
dc.date.issued2015-09-14
dc.identifier.urihttps://doi.org/10.1155/2015/567589
dc.identifier.urihttps://repository.tcu.edu/handle/116099117/11447
dc.identifier.urihttps://www.hindawi.com/journals/cmmm/2015/567589/
dc.description.abstractRespiratory syncytial virus (RSV) is the most common cause of bronchiolitis and pneumonia in children younger than 1 year of age in the United States. Moreover, RSV is being recognized more often as a significant cause of respiratory illness in older adults. Although RSV has been studied both clinically and in vitro, a quantitative understanding of the infection dynamics is still lacking. In this paper, we study the effect of uncertainty in the main parameters of a viral kinetics model of RSV. We first characterize the RSV replication cycle and extract parameter values by fitting the mathematical model to in vivo data from eight human subjects. We then use Monte Carlo numerical simulations to determine how uncertainty in the parameter values will affect model predictions. We find that uncertainty in the infection rate, eclipse phase duration, and infectious lifespan most affect the predicted dynamics of RSV. This study provides the first estimate of in vivo RSV infection parameters, helping to quantify RSV dynamics. Our assessment of the effect of uncertainty will help guide future experimental design to obtain more precise parameter values.
dc.language.isoenen_US
dc.publisherHindawi
dc.rights.urihttps://creativecommons.org/licenses/by/3.0/
dc.sourceComputational and Mathematical Methods in Medicine
dc.subjectmathematical models
dc.subjectinfluenza virus
dc.subjectrisk factors
dc.subjectin vivo
dc.subjectinfection
dc.subjectepidemic
dc.subjecthost
dc.subjectkinetics
dc.subjectefficacy
dc.subjectinfants
dc.titleAssessing Uncertainty in A2 Respiratory Syncytial Virus Viral Dynamics
dc.typeArticle
dc.rights.holderGilberto et al.
dc.rights.licenseCC BY 3.0
local.collegeCollege of Science and Engineering
local.departmentPhysics and Astronomy
local.personsAll (PHYS)


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