| Abstract: |
| We present a mathematical framework for modelling patient colonisation by multidrug-resistant bacteria across a healthcare system structured as a network of care units. The model incorporates patient movements between units, including direct hospital-to-hospital transfers and indirect transfers via home stays. Patients are stratified into three groups: low-risk, high-risk, and rare one-time visitors. Using this framework, we evaluate the effectiveness of targeted intervention strategies designed to reduce colonisation levels within the network. Interventions can be directed at specific patient groups or applied selectively in chosen care units. Each strategy is also assessed in terms of the costs it generates, allowing comparison of both epidemiological impact and resource use. The model is informed and calibrated using real-world patient movement data, enabling realistic evaluation of potential outcomes. By accounting for patient heterogeneity, movement patterns, and cost-effectiveness, the framework provides a flexible and practical tool for optimising infection control strategies in interconnected healthcare settings. This approach supports data-driven decision-making for managing multidrug-resistant bacteria while balancing intervention efficiency and resource allocation. |
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