Seminars in Mathematical Sciences

Jul 21 (Tue)

14:00 MCS2068 StatLam Ho (Dalhousie University): Efficient Bayesian Methods for Detecting Trajectory Shifts in Stochastic Models of Infectious Disease

The trajectory of an infectious disease epidemic may change over time due to policy interventions, the emergence of new strains, or accumulating population immunity. In this talk, I will present our ongoing project on developing Efficient Bayesian Methods for Detecting Trajectory Shifts in Stochastic Models of Infectious Disease. A primary challenge of stochastic models is that likelihood calculations for prevalence count data have traditionally been considered computationally intractable, rendering these models difficult to scale for large outbreaks like the COVID-19 pandemic. To overcome this limitation, our method introduces a Poisson approximation scheme that significantly reduces computational cost. Crucially, we demonstrate that this approximation scheme preserves information, maintaining accuracy comparable to scenarios where the data are continuously observed.

Venue: MCS2068

15:00 MCS2068 StatDenise Lievesley (University of Oxford): Protecting the integrity of official statistics

Denise will draw on her experience as Director of Statistics in UNESCO, working in many countries of the world, and also on her more recent appointment to review the UK Statistical system, in order to discuss threats to the integrity of official statistics. She will talk about the various codes and principles which exist to protect the independence of the National Statistics Institutes and will consider how those of us outside of the public service can act as critical friends.

Venue: MCS2068

Jul 22 (Wed)

12:00 MJC2006 ApplCath Noakes (Durham): Creating an Infection Resilient Environment

The pandemic highlighted how important the indoor environment is for transmission of infection. Airborne transmission is now accepted as the dominant mode for COVID-19, but there are multiple questions that remain around the specific mechanisms for pathogen transmission and how to determine which mitigations are most effective.

Modelling is an important strategy for understanding the factors that influence risks. Simple models such as the Wells-Riley approach are widely used to make the case for interventions such as ventilation. However, transmission involves a complex chain of events that such models struggle to capture. The transmission process is determined by spatial and transient interactions of physics, biology and chemistry as well as human behaviours. Measuring real-world infection outcomes is challenging, and even where it is possible, it is difficult to unpick the relative importance of different components.

Despite all of this complexity, policy makers and practitioners need evidence that can be easily translated into advice. This talk considers how we can model the processes involved in transmission, where we have evidence and where there are gaps. It considers the challenge of trading off simple advice with complex realities and explores how much we can provide effective and practical protection from transmission in the built environment.

Professor Cath Noakes OBE is the Deputy Pro Vice Chancellor Research and Innovation and Professor of Environmental Engineering for Buildings at the University of Leeds, UK. She is a chartered engineer with substantial experience leading research into buildings and health, particularly around ventilation, air quality and infection control. She has worked closely with policy particularly during the COVID-19 pandemic, including contributing to UK SAGE committee, NHS guidance on healthcare environments, WHO groups, and work with the Royal Academy of Engineering.

Venue: MJC2006

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