Speakers
Description
The behavioural element in the transmission dynamics of infectious diseases is very influential; infection risk affects behaviour while behaviour affects individual and communal infection risk.
There are several challenges recognised amongst the epidemiology and infectious disease modelling communities on incorporating the dynamics of behaviour into models of infectious disease dynamics \cite{ funk_nine_2015,hill_integrating_2024}. Challenges arise due to a lack of readily translatable quantitative behavioural science models that might capture the changing of relevant behaviours, societal norms and policy directives across individuals and/or populations, particularly in novel social contexts. These challenges are not confined to public health; veterinary and plant health researchers also strive to integrate infectious disease and behavioural dynamics \cite{ hidano_modeling_2018,murray-watson_how_2022}. The COVID-19 pandemic highlighted the deficiencies in availability of both suitable data and of disease outbreak models to reasonably incorporate data-driven and/or theoretical knowledge regarding the behavioural response to a pandemic, including the drivers of voluntary behaviour changes \cite{brooks-pollock_voluntary_2023}.
With that motivation, we share research examples tackling interdisciplinary problems in epidemiology and infectious disease modelling that involve the dynamics of behaviour. Application areas cut across public health, veterinary health and plant health.
Bibliography
@article{funk_nine_2015,
title = {Nine challenges in incorporating the dynamics of behaviour in infectious diseases models},
volume = {10},
issn = {17554365},
url = {https://linkinghub.elsevier.com/retrieve/pii/S1755436514000541},
doi = {10.1016/j.epidem.2014.09.005},
language = {en},
urldate = {2025-11-12},
journal = {Epidemics},
author = {Funk, Sebastian and Bansal, Shweta and Bauch, Chris T. and Eames, Ken T.D. and Edmunds, W. John and Galvani, Alison P. and Klepac, Petra},
month = mar,
year = {2015},
pages = {21--25},
}
@article{hill_integrating_2024,
title = {Integrating human behaviour and epidemiological modelling: unlocking the remaining challenges},
volume = {1},
issn = {2993-7574},
shorttitle = {Integrating human behaviour and epidemiological modelling},
url = {https://www.tandfonline.com/doi/full/10.1080/29937574.2024.2429479},
doi = {10.1080/29937574.2024.2429479},
language = {en},
number = {1},
urldate = {2025-11-12},
journal = {Mathematics in Medical and Life Sciences},
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 Nixon, Emily J. and Parnell, Stephen and Bolton, Kirsty J.},
month = dec,
year = {2024},
pages = {2429479},
}
@article{hidano_modeling_2018,
title = {Modeling {Dynamic} {Human} {Behavioral} {Changes} in {Animal} {Disease} {Models}: {Challenges} and {Opportunities} for {Addressing} {Bias}},
volume = {5},
issn = {2297-1769},
shorttitle = {Modeling {Dynamic} {Human} {Behavioral} {Changes} in {Animal} {Disease} {Models}},
url = {https://www.frontiersin.org/article/10.3389/fvets.2018.00137/full},
doi = {10.3389/fvets.2018.00137},
urldate = {2025-11-12},
journal = {Frontiers in Veterinary Science},
author = {Hidano, Arata and Enticott, Gareth and Christley, Robert M. and Gates, M. Carolyn},
month = jun,
year = {2018},
pages = {137},
}
@article{murray-watson_how_2022,
title = {How growers make decisions impacts plant disease control},
volume = {18},
issn = {1553-7358},
url = {https://dx.plos.org/10.1371/journal.pcbi.1010309},
doi = {10.1371/journal.pcbi.1010309},
language = {en},
number = {8},
urldate = {2025-11-12},
journal = {PLOS Computational Biology},
author = {Murray-Watson, Rachel E. and Hamelin, Frédéric M. and Cunniffe, Nik J.},
editor = {Struchiner, Claudio José},
month = aug,
year = {2022},
pages = {e1010309},
}
@article{brooks-pollock_voluntary_2023,
title = {Voluntary risk mitigation behaviour can reduce impact of {SARS}-{CoV}-2: a real-time modelling study of the {January} 2022 {Omicron} wave in {England}},
volume = {21},
issn = {1741-7015},
shorttitle = {Voluntary risk mitigation behaviour can reduce impact of {SARS}-{CoV}-2},
url = {https://bmcmedicine.biomedcentral.com/articles/10.1186/s12916-022-02714-5},
doi = {10.1186/s12916-022-02714-5},
language = {en},
number = {1},
urldate = {2025-11-12},
journal = {BMC Medicine},
author = {Brooks-Pollock, Ellen and Northstone, Kate and Pellis, Lorenzo and Scarabel, Francesca and Thomas, Amy and Nixon, Emily and Matthews, David A. and Bowyer, Vicky and Garcia, Maria Paz and Steves, Claire J. and Timpson, Nicholas J. and Danon, Leon},
month = jan,
year = {2023},
pages = {25},
}
