A hybrid individual-based mathematical model to study bladder infections

Anas Lasri Doukkali, Tommaso Lorenzi, Benjamin J. Parcell, Jennifer L. Rohn, Ruth Bowness*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


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
Number of pages15
JournalFrontiers in Applied Mathematics and Statistics
Publication statusPublished - 3 Feb 2023


  • Mathematical
  • Model
  • Individual-based
  • Simulation
  • Bladder
  • Infection
  • Escherichia coli

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