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Isaac Newton Institute for Mathematical Sciences

Characterizing the dynamics of rubella relative to measles: the role of stochasticity

Presenter: Ganna Rozhnova (The University of Manchester and Lisbon University)

Co-authors: Jessica Metcalf (Oxford University), Bryan Grenfell (Princeton University)


Rubella is a completely immunizing and mild infection in children. Understanding its behavior is of considerable applied importance because of Congenital Rubella Syndrome, which results from infection with rubella during early pregnancy and may entail a variety of birth defects. The dynamics of rubella are relatively poorly resolved, and appear to show considerable diversity globally. Here, we investigate the behavior of a stochastic seasonally forced susceptible-infected-recovered model to characterize the determinants of these dynamics and illustrate patterns by comparison with measles. We perform a systematic analysis of spectra of stochastic fluctuations around stable attractors of the corresponding deterministic model and compare them with spectra from full stochastic simulations in large populations. This approach allows us to quantify the effects of demographic stochasticity and to give a coherent picture of measles and rubella dynamics, explaining essential difference s in the patterns exhibited by these diseases. We discuss the implications of our findings in the context of vaccination and changing birth rates as well as the persistence of these two childhood infections.

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