Speakers
Description
The SARS-CoV-2 pandemic highlighted that epidemic models fail to incorporate data-driven and theoretical knowledge of behavioural response to pandemics. This gap is partially driven by the lack of quantitative models that can predict the adoption of behaviours across individuals and populations, particularly in new social contexts. Hence, there is a need to improve behavioural realism in integrated "epidemiological-behavioural" models.
We will first summarise our involvement in related events around epidemiological-behavioural modelling. That includes an upcoming Isaac Newton Institute Satellite programme on ‘Maths of Human Behaviour: modelling sociality, mobility and protectionism’ taking place during 20 July – 14 August 2026 at the University of Nottingham, UK (https://www.newton.ac.uk/event/mhb/).
Ed will discuss a perspective paper \cite{hill2024} highlighting: (i) the key role of interdisciplinary collaboration for integrating dynamic human behaviour into epidemiological models; (ii) interdisciplinary challenge areas in epidemiological-behavioural modelling; (iii) recommendations to make progress in each of the challenge areas.
Matt will then present work that investigates behavioural trends in testing behaviour for COVID-like illness \cite{ryan2025}. Matt will briefly describe how dynamic testing behaviour can be included into compartmental models and highlight key results from this modelling.
Bibliography
@article{hill2024,
title={Integrating human behaviour and epidemiological modelling: unlocking the remaining challenges},
author={Hill, Edward M and Ryan, Matthew and Haw, David and Lynch, Mark P and McCabe, Ruth and Milne, Alice E and Turner, Matthew S and Vedhara, Kavita and Zeng, Fanqi and Barons, Martine J and others},
journal={Mathematics in Medical and Life Sciences},
volume={1},
number={1},
pages={2429479},
year={2024},
publisher={Taylor \& Francis}
}
@article{ryan2025,
title={A Behaviour and Disease Model of Testing and Isolation},
author={Ryan, Matthew and Hickson, Roslyn I and Hill, Edward M and House, Thomas and Isham, Valerie and Zhang, Dongni and Roberts, Mick G},
journal={arXiv preprint arXiv:2504.02488},
year={2025}
}
