A mathematical model for assessing transient airborne infection risks in a multi-zone hospital ward

Quantification of the parameters influencing airborne infection risks associated with indoor activities in different settings can help in understanding outbreak dynamics and the effective implementation of mitigation strategies. This is particularly important in hospitals, where the consequence of infections amongst vulnerable individuals can be significant. Despite the transient occupancy and inter-connected nature of hospital wards, the majority of airborne risk models assume steady-state conditions and well-mixed air in a single zone. We propose a multi-zone model with both a fixed and time-varying infectious person. We use an adapted version of the Wells–Riley model to estimate transient airborne virus concentration, and account for time-varying behaviour in the indoor setting. Through a coupling with a CONTAM airflow network model, we incorporate the effects of ventilation patterns on inter-zonal flow rates to represent likely airflow in a realistic hospital ward. We use this approach to explore the difference in predictions from transient versus steady-state models across several scenarios. Results suggest that a steady-state approach could lead to an overestimation of infection risk or underestimation of quanta emission, especially when the infectious person is only present for a short period of time. The difference between models is most apparent in poorly ventilated spaces, illustrating how risks can build over time when infectious occupant movement is more frequent than the removal rate due to ventilation. The model highlights the importance of considering transient factors when assessing infection risks to ensure that the most effective mitigation strategies are implemented to address long and short timescale risks.