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Harnessing experimentally-validated mathematical models to forecast influenza-mediated pathology
Influenza viruses infect millions of individuals each year and cause a significant amount of morbidity and mortality. Understanding how the virus spreads within the lung, how efficacious host immune control is, and how each influences acute lung injury and disease severity is critical to combat the infection. We used an integrative model-experiment exchange to establish the dynamical connections between viral loads, infected cells, CD8+ T cells, lung injury, and disease severity. Our model predicts that infection resolution is sensitive to CD8+ T cell expansion, that there is a critical T cell magnitude needed for efficient resolution, and that the rate of T cell-mediated clearance is dependent on infected cell density.
We validated the model through a series of experiments, including CD8 depletion and whole lung histomorphometry. This showed that the infected area of the lung matches the model-predicted infected cell dynamics, and that the resolved area of the lung parallels the relative CD8 dynamics. Additional analysis revealed a nonlinear relation between disease severity, inflammation, and lung injury. These novel links between important host-pathogen kinetics and pathology enhance our ability to forecast disease progression.
Date:
30 October 2020, 14:00
Venue:
Mathematical Institute, Woodstock Road OX2 6GG
Venue Details:
Virtual
Speaker:
Professor Amber Smith (Department of Pediatrics University of Tennessee Health Science Center)
Organising department:
Mathematical Institute
Organiser:
Sara Jolliffe (University of Oxford)
Organiser contact email address:
sara.jolliffe@maths.ox.ac.uk
Host:
Dr Ruth Baker (University of Oxford)
Part of:
Mathematical Biology and Ecology
Booking required?:
Not required
Audience:
Members of the University only
Editor:
Sara Jolliffe
