Efficient solution and learning of robust factored MDPs
Schnitzer, Y Abate, A Parker, D Proceedings of the 40th Annual AAAI Conference on Artificial Intelligence volume 40 issue 43 36369-36377 (14 Mar 2026) doi:10.1609/aaai.v40i43.40957
Simplified and Generalized Masked Diffusion for Discrete Data
Shi, J Han, K Wang, Z Doucet, A Titsias, M 103131-103167 (01 Jan 2024) doi:10.52202/079017-3277
Preface
Doucet, A Elvira, V Lindsten, F Miguez, J Foundations of Data Science volume 7 issue 4 i-ii (01 Jan 2025) doi:10.3934/fods.2025019
Persistent transcendental Bézout theorems
Buhovsky, L Polterovich, I Polterovich, L Shelukhin, E Stojisavljević, V Forum of Mathematics, Sigma volume 12 (27 Aug 2024) doi:10.1017/fms.2024.49
Persistence modules, symplectic Banach–Mazur distance and Riemannian metrics
Stojisavljević, V Zhang, J International Journal of Mathematics volume 32 issue 07 2150040-2150040 (25 Jun 2021) doi:10.1142/s0129167x21500403
Persistence barcodes and Laplace eigenfunctions on surfaces
Polterovich, I Polterovich, L Stojisavljević, V Geometriae Dedicata volume 201 issue 1 111-138 (14 Aug 2019) doi:10.1007/s10711-018-0383-9
Coarse nodal count and topological persistence
Buhovsky, L Payette, J Polterovich, I Polterovich, L Shelukhin, E Stojisavljević, V Journal of the European Mathematical Society volume 28 issue 7 3131-3202 (16 Sep 2024) doi:10.4171/jems/1521
Persistence Modules with Operators in Morse and Floer Theory
Polterovich, L Shelukhin, E Stojisavljević, V Moscow Mathematical Journal volume 17 issue 4 757-786 (2017) doi:10.17323/1609-4514-2017-17-4-757-786
Wed, 03 Dec 2025
17:30
Lecture Theatre 1

Understanding Infectious Disease Transmission: Insights and Uncertainty - Christl Donnelly

Christl Donnelly
Abstract

How do diseases spread and how can the analysis of data help us stop them? Quantitative modelling and statistical analysis are essential tools for understanding transmission dynamics and informing evidence-based policies for both human and animal health.

In this lecture, Christl will draw lessons from past epidemics and endemic diseases, across livestock, wildlife, and human populations, to show how mathematical frameworks and statistical inference help unravel complex transmission systems. We’ll look at recent advances that integrate novel data sources, contact network analysis, and rigorous approaches to uncertainty, and discuss current challenges for quantitative epidemiology.

Finally, we’ll highlight opportunities for statisticians and mathematicians to collaborate with other scientists (including clinicians, immunologists, veterinarians) to strengthen strategies for disease control and prevention.

Christl Donnelly CBE is Professor of Applied Statistics, University of Oxford and Professor of Statistical Epidemiology, Imperial College London.

Please email @email to register to attend in person.

The lecture will be broadcast on the Oxford Mathematics YouTube Channel on Wednesday 17 December at 5-6 pm and any time after (no need to register for the online version).

The Oxford Mathematics Public Lectures are generously supported by XTX Markets.

Banner for event


 

Understanding Infectious Disease Transmission: Insights and Uncertainty - Christl Donnelly, Professor of Applied Statistics, University of Oxford and Professor of Statistical Epidemiology, Imperial College London.

Wednesday 03 December 2025, 5.30-6.30 pm Andrew Wiles Building, Mathematical Institute, Oxford

Subscribe to