A Hybrid Individual-based Mathematical Model to study Bladder Infections

Anas Lasri Doukkali; Tommaso Lorenzi; Benjamin Parcell; Jennifer Rohn; Ruth Bowness

doi:10.3389/fams.2023.1090334

A Hybrid Individual-based Mathematical Model to study Bladder Infections

Anas Lasri Doukkali, Tommaso Lorenzi, Benjamin Parcell, Jennifer Rohn, Ruth Bowness

Research output: Contribution to journal › Article › peer-review

3 Citations (SciVal)

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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
Article number	1090334
Number of pages	15
Journal	Frontiers in Applied Mathematics and Statistics
Volume	9
DOIs	https://doi.org/10.3389/fams.2023.1090334
Publication status	Published - 3 Feb 2023

Data Availability Statement

The original contributions presented in the study are publicly
available. 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

Access to Document

10.3389/fams.2023.1090334Licence: CC BY

Cite this

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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.",

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AU - Lasri Doukkali, Anas

AU - Lorenzi, Tommaso

AU - Parcell, Benjamin

AU - Rohn, Jennifer

AU - Bowness, Ruth

PY - 2023/2/3

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AB - 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.

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A Hybrid Individual-based Mathematical Model to study Bladder Infections

Abstract

Data Availability Statement

Funding

Keywords

ASJC Scopus subject areas

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