Speaker
Description
Nosocomial infections, also known as hospital-acquired infections, pose a major public health challenge, particularly due to the increase of antibiotic-resistant pathogens.\cite{edman_2025} Understanding how such infections spread within hospitals is vital for effective infection control.
Outbreak reconstruction, to infer the underlying transmission tree based on observed data, is of particular interest.\cite{duault_2024} Commonly, Markov Chain Monte Carlo methods are used to sample transmission trees consistent with the data in a Bayesian framework.\cite{campbell_2019}
In this work, we consider the problem of reconstructing transmission trees for nosocomial outbreaks. We present a stochastic model of hospital-wide outbreaks with heterogeneous infectivity and environmental transmission. Metropolis-Hastings sampling is then used to infer the posterior distribution of the transmission trees, infection times and model parameters of partially observed simulated outbreaks.
Compared to previous approaches, the model is designed specifically for nosocomial outbreaks. This allows the model to capture realistic hospital dynamics where infections may arise both through direct patient contact and indirectly via contaminated environments.
Our results show that Bayesian inference can provide useful insights into the structure of hospital outbreaks. In practice, improved outbreak reconstruction tools could support the work of infection prevention and control practitioner.
Bibliography
@article{duault_2024,
title = {Outbreak reconstruction with a slowly evolving multi-host pathogen: {A} comparative study of three existing methods on {Mycobacterium} bovis outbreaks},
volume = {49},
issn = {17554365},
shorttitle = {Outbreak reconstruction with a slowly evolving multi-host pathogen},
url = {https://linkinghub.elsevier.com/retrieve/pii/S1755436524000550},
doi = {10.1016/j.epidem.2024.100794},
language = {en},
urldate = {2026-03-14},
journal = {Epidemics},
author = {Duault, Hélène and Durand, Benoit and Canini, Laetitia},
month = dec,
year = {2024},
pages = {100794},
}
@article{edman_2025,
title = {A hospital-wide outbreak of extended-spectrum β-lactamase-producing {Klebsiella} oxytoca associated with contaminated sinks and associated plumbing: outbreak report, risk factor analysis and plasmid mapping},
volume = {162},
issn = {01956701},
shorttitle = {A hospital-wide outbreak of extended-spectrum β-lactamase-producing {Klebsiella} oxytoca associated with contaminated sinks and associated plumbing},
url = {https://linkinghub.elsevier.com/retrieve/pii/S0195670125001409},
doi = {10.1016/j.jhin.2025.05.002},
language = {en},
urldate = {2026-03-14},
journal = {Journal of Hospital Infection},
author = {Edman-Wallér, J. and Andersson, J. and Nelson, M. and Hallberg, L. and Berglund, L. and Mellström Dahlgren, H. and Lindsjö, O. and Müller, V. and Stalfors, J.},
month = aug,
year = {2025},
pages = {1--8},
}
@article{campbell_2019,
title = {Bayesian inference of transmission chains using timing of symptoms, pathogen genomes and contact data},
volume = {15},
issn = {1553-7358},
url = {https://dx.plos.org/10.1371/journal.pcbi.1006930},
doi = {10.1371/journal.pcbi.1006930},
language = {en},
number = {3},
urldate = {2026-03-14},
journal = {PLOS Computational Biology},
author = {Campbell, Finlay and Cori, Anne and Ferguson, Neil and Jombart, Thibaut},
editor = {Pitzer, Virginia E.},
month = mar,
year = {2019},
pages = {e1006930},
}
