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Evolutionary Determinants of Influenza Virus Pathogenesis and Tissue Tropism (Influenza tropism)
Start date: Nov 1, 2012, End date: Oct 31, 2014 PROJECT  FINISHED 

Influenza A virus bears high morbidity and mortality burdens in humans following yearly seasonal epidemics and occasional yet potentially devastating pandemics. These burdens are a result of disease severity following infection in individual hosts, and the size of influenza epidemics/pandemics at the population level. The relationships and feedbacks between influenza virus pathogenesis at the individual host level and influenza virus epidemiology at the population level are ill understood. Influenza virus tissue tropism contributes to determining which regions of the respiratory tract (from nasal cavity to deep lungs) are infected. The spatial location of influenza virus infection along the human respiratory tract is a determinant of the virus’ pathogenicity and transmissibility. While disease severity increases deeper down the respiratory tract, transmissibility appears favoured higher up. Both pathogenicity and transmissibility, associated with tissue tropism, contribute to the virus reproductive fitness, defining the size of the epidemic or pandemic. Therefore, strong selective pressures acting within hosts and at the population level likely shape tissue tropism to maximize influenza virus reproductive fitness. The aim of the project is to characterize these selective pressures and their interplay at the interface of within- and between-host dynamics, by combining experimental work and mathematical modelling. Key objectives are to determine the selective pressures associated with transmission and pre-existing immunity on influenza virus tissue tropism in an experimental setting; and determine the mutual interactions of these selective pressures by use of combined within- and between-host mathematical models. Modelling skills and knowledge will be transferred by the candidate to the European host. This project intends to clarify the cross-scale dynamics of influenza virus to better characterize and predict influenza morbidity and mortality burdens.

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