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Modeling of the immune response during virus infection of the human respiratory tract

Giegold, Mikaela LU (2018) BMEM01 20182
Department of Biomedical Engineering
Abstract
In this master thesis a temporal model of the dynamics between virus and the immune system during a HRV infection was developed. The model was utilized to achieve numerical estimates for parameters governing the mechanisms in the immune system. Through a sensitivity analysis the interplay between different cells in the model was examined. The reliability of the parameter estimates were evaluated through an identifiability analysis.

The model was able to capture the dynamics of virus and the majority of the mechanisms included from the immune system. The sensitivity analysis proved that the outcome of the infection was highly sensitive for changes of the parameters governing the early immune response, production and removal of virus.... (More)
In this master thesis a temporal model of the dynamics between virus and the immune system during a HRV infection was developed. The model was utilized to achieve numerical estimates for parameters governing the mechanisms in the immune system. Through a sensitivity analysis the interplay between different cells in the model was examined. The reliability of the parameter estimates were evaluated through an identifiability analysis.

The model was able to capture the dynamics of virus and the majority of the mechanisms included from the immune system. The sensitivity analysis proved that the outcome of the infection was highly sensitive for changes of the parameters governing the early immune response, production and removal of virus. Lastly the identifiability analysis showed that the model and available data were sufficient to achieve reliable parameter estimates.

Combined with another model that takes the spatial effects into account this model could be used to simulate the infection and immune dynamics in the human lung. With such a model hypothesis regarding the differences in viral occurrence between upper and lower respiratory tract could be tested. (Less)
Popular Abstract
Development of a model of the immune dynamics during a respiratory infection can aid pharmaceutical development

The mathematical model, which was able to replicate the dynamics of virus and inflammatory cells during a virus infection, can be used as a test module for further investigation of the mechanisms between the immunological defence and virus.
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author
Giegold, Mikaela LU
supervisor
organization
course
BMEM01 20182
year
type
H2 - Master's Degree (Two Years)
subject
language
English
additional info
2018-15
id
8958554
date added to LUP
2018-09-14 10:49:45
date last changed
2018-09-14 10:49:45
@misc{8958554,
  abstract     = {In this master thesis a temporal model of the dynamics between virus and the immune system during a HRV infection was developed. The model was utilized to achieve numerical estimates for parameters governing the mechanisms in the immune system. Through a sensitivity analysis the interplay between different cells in the model was examined. The reliability of the parameter estimates were evaluated through an identifiability analysis.

The model was able to capture the dynamics of virus and the majority of the mechanisms included from the immune system. The sensitivity analysis proved that the outcome of the infection was highly sensitive for changes of the parameters governing the early immune response, production and removal of virus. Lastly the identifiability analysis showed that the model and available data were sufficient to achieve reliable parameter estimates.

Combined with another model that takes the spatial effects into account this model could be used to simulate the infection and immune dynamics in the human lung. With such a model hypothesis regarding the differences in viral occurrence between upper and lower respiratory tract could be tested.},
  author       = {Giegold, Mikaela},
  language     = {eng},
  note         = {Student Paper},
  title        = {Modeling of the immune response during virus infection of the human respiratory tract},
  year         = {2018},
}