Abstract
Introduction: Bladder infections are common, affecting millions each year, and are often recurrent problems.
Methods: We have developed a spatial mathematical framework consisting of a hybrid individual-based model to simulate these infections in order to understand more about the bacterial mechanisms and immune dynamics. We integrate a varying bacterial replication rate and model bacterial shedding as an immune mechanism.
Results: We investigate the effect that varying the initial bacterial load has on infection outcome, where we find that higher bacterial burden leads to poorer outcomes, but also find that only a single bacterium is needed to establish infection in some cases. We also simulate an immunocompromised environment, confirming the intuitive result that bacterial spread typically progresses at a higher rate.
Conclusions: With future model developments, this framework is capable of providing new clinical insight into bladder infections.
Original language | English |
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Article number | 1090334 |
Number of pages | 15 |
Journal | Frontiers in Applied Mathematics and Statistics |
Volume | 9 |
DOIs | |
Publication status | Published - 3 Feb 2023 |
Data Availability Statement
The original contributions presented in the study are publiclyavailable. This data can be found at: https://github.com/RuthBowness-Group/UTImodel, https://doi.org/10.5281/zenodo.7293870.
Funding
RB was supported by a fellowship funded by the Medical Research Council, MR/P014704/1, and also acknowledges funding from the Academy of Medical Sciences (London), the Wellcome Trust (London), the UK Government Department of Business, Energy and Industrial Strategy (London), the British Heart Foundation (London), and the Global Challenges Research Fund (Swindon, UK; grant number SBF003\1052). TL gratefully acknowledges support from the Italian Ministry of University and Research (MUR) through the grant Dipartimenti di Eccellenza 2018-2022 (Project no. E11G18000350001) and the PRIN 2020 project (No. 2020JLWP23) Integrated Mathematical Approaches to Socio-Epidemiological Dynamics (CUP: E15F21005420006).
Keywords
- Escherichia coli
- bladder
- individual-based
- infection
- mathematical
- model
- simulation
ASJC Scopus subject areas
- Applied Mathematics
- Statistics and Probability