A hybrid individual-based mathematical model to study bladder infections

Anas Lasri Doukkali, Tommaso Lorenzi, Benjamin J. Parcell, Jennifer L. Rohn, Ruth Bowness (Lead / Corresponding author)

    Research output: Contribution to journalArticlepeer-review

    2 Citations (Scopus)
    42 Downloads (Pure)


    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 languageEnglish
    Article number1090334
    JournalFrontiers in Applied Mathematics and Statistics
    Publication statusPublished - 3 Feb 2023


    • bladder
    • Escherichia coli
    • individual-based
    • infection
    • mathematical
    • model
    • simulation

    ASJC Scopus subject areas

    • Statistics and Probability
    • Applied Mathematics


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