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Title: Mathematical modelling of coinfection with important respiratory pathogens
Author: Nicoli, Emily
Awarding Body: University of Bristol
Current Institution: University of Bristol
Date of Award: 2013
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Although much research in infectious disease epidemiology focuses on a single pathogen and its host, there are many interesting biological examples of coinfections with multiple strains or pathogens. The human upper respiratory tract provides a habitat for a large number of different viral and bacterial species. The overall aim of this PhD thesis is to investigate the epidemiology of a range of respiratory coinfections in humans by developing and applying mathematical models and statistical techniques. I have performed statistical analyses to determine associations between rhinitis and bacterial and viral infections in both cross-sectional and time-series data. Despite variation in results depending on the technique applied, I found a moderate association between invasive pneumococcal disease (IPD) and influenza and between IPD and respiratory syncytial virus (RSV), after adjusted for their common seasonality. Mathematical modelling is a valuable tool in the prediction of the effectiveness of different interventions, such as vaccination. However, for some dynamic transmission models with coinfection, the model structure applied implicitly promotes coexistence between the strains, when in fact one of the strains would be expected to die out as a result of competition. Thus, the model structure is implicitly controlling the degree of competition and independence between the strains, potentially leading to misinterpretation. I have studied coinfection model structures that will not promote coexistence where it is not expected. A model of meningococcal carriage, incorporating age-structure and vaccination has been developed, examining potential replacement scenarios following the introduction of a new vaccine. The model was developed further to explicitly control competition between the strains and include immunity, with the aim of looking at the effect of pertussis vaccine on the relative prevalences of Bordetella pertussis and a vaccine escape strain, Bordetella parapertussis.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available