Challenges in modeling the transmission dynamics of childhood diseases
Mathematical models of childhood diseases are often fitted using deterministic methods under the assumption of homogeneous contact rates within populations. Such models can provide good agreement with data in the absence of significant changes in population demography or transmission, such as in the case of pre-vaccine era measles. However, accurate modeling and forecasting after the start of mass vaccination has proved more challenging. This is true even in the case of measles which has a well understood natural history and a very effective vaccine. We demonstrate how the dynamics of homogeneous and age-structured models can be similar in the absence of vaccination, but diverge after vaccine roll-out. We also present some fundamental differences in deterministic and stochastic methods to fit models to data, and propose techniques to fit long term time series with imperfect covariate information. The methods we develop can be applied to many types of complex systems beyond those in disease ecology.
Date: 3 February 2023, 14:00 (Friday, 3rd week, Hilary 2023)
Venue: Mathematical Institute, Woodstock Road OX2 6GG
Venue Details: L3
Speaker: Prof Felicia Magpantay (Dept of Math and Stats Queen’s University Kingston)
Organising department: Mathematical Institute
Organiser: Sara Jolliffe (University of Oxford)
Organiser contact email address:
Host: Philip Maini (University of Oxford)
Part of: Mathematical Biology and Ecology
Booking required?: Not required
Audience: Members of the University only
Editor: Sara Jolliffe