Modelling Disease Dynamics

Thomas House (University of Manchester)

Frank Adams 1, Alan Turing Building,

Mathematical epidemiology is roughly a century in to its
foundation as a modern science. Non-linear models of transmission of
infectious diseases between individuals have, over that time, had
significant success in explaining facts as basic as why epidemics stop
before everyone has been infected, through to complex questions relating
to pandemic mitigation and the reemergence of vaccine-preventable
childhood diseases like measles. I will provide an introductory account of
this fascinating area of applied mathematics, as well as a selection of
methodological research directions including contact networks, extreme
heterogeneity and relating models to data.

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