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A Model of Bacterial Superinfection in an Influenza-Infected Host

Linn, Sherry (2011) A Model of Bacterial Superinfection in an Influenza-Infected Host. Master's Thesis, University of Pittsburgh.

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    Abstract

    Bacterial pneumonia is a common complication of influenza A infection. We create an ODE model of bacterial infection with state variables representing the respective levels of bacteria, impaired and active neutrophils, and the anti-inflammatory molecule interleukin 10 (IL-10). After fitting the parameters, we obtain a model that demonstrates bistability between states of health and chronic bacterial infection. The fitted model also closely reproduces IL-10 data obtained from a model of mice inoculated with a strain of influenza A virus. Additionally, we develop a different model similar to the first but with stochastic intake of bacteria to represent the inhalation of small amounts of bacteria into the lungs many times daily. We find a set of parameters for which the second model produces a fit to the IAV IL-10 data.


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    Details

    Item Type: University of Pittsburgh ETD
    ETD Committee:
    ETD Committee TypeCommittee MemberEmail
    Committee ChairSwigon, Davidswigon@pitt.edu
    Committee MemberErmentrout, G Bardbard@pitt.edu
    Committee MemberClermont, Gillesclermontg@ccm.upmc.edu
    Committee MemberRubin, Jonathanjonrubin@pitt.edu
    Title: A Model of Bacterial Superinfection in an Influenza-Infected Host
    Status: Unpublished
    Abstract: Bacterial pneumonia is a common complication of influenza A infection. We create an ODE model of bacterial infection with state variables representing the respective levels of bacteria, impaired and active neutrophils, and the anti-inflammatory molecule interleukin 10 (IL-10). After fitting the parameters, we obtain a model that demonstrates bistability between states of health and chronic bacterial infection. The fitted model also closely reproduces IL-10 data obtained from a model of mice inoculated with a strain of influenza A virus. Additionally, we develop a different model similar to the first but with stochastic intake of bacteria to represent the inhalation of small amounts of bacteria into the lungs many times daily. We find a set of parameters for which the second model produces a fit to the IAV IL-10 data.
    Date: 06 June 2011
    Date Type: Completion
    Defense Date: 18 March 2011
    Approval Date: 06 June 2011
    Submission Date: 11 April 2011
    Access Restriction: No restriction; Release the ETD for access worldwide immediately.
    Patent pending: No
    Institution: University of Pittsburgh
    Thesis Type: Master's Thesis
    Refereed: Yes
    Degree: MS - Master of Science
    URN: etd-04112011-115917
    Uncontrolled Keywords: inflammation; mathematical model
    Schools and Programs: Dietrich School of Arts and Sciences > Mathematics
    Date Deposited: 10 Nov 2011 14:35
    Last Modified: 27 Apr 2012 13:08
    Other ID: http://etd.library.pitt.edu/ETD/available/etd-04112011-115917/, etd-04112011-115917

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