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Infection Risk Modelling

Infection Risk Modelling

Predicting cross-transmission is critical in linking the hospital environment with patient well-being. We are developing novel mathematical and computational codes to assess the effect of cleaning regimes, improving hand hygiene and ventilation on infection transmission.

What-if Scenarios

We will use computational models to create thousands of scenarios where we can query the effects of cleaning, ventilation and hand hygiene.

Exposure Risk

We will be able to calculate the risk of exposure for a variety of different pathogens harmful to hospital patients with depleted immune systems.

Building Blocks

These models will form the building blocks of an integrated platform that links experimental, computational and mathematical models of infection risk.

Models We Have Developed

Machine Learning for Human Behaviour

We used observations of healthcare workers during clinical practices touching surfaces and fed them into pattern recognition algorithms to predict the order in which surfaces are touched during patient care for 10,000 nurses. With this we can predict the contamination level on hands and assess the risk associated with different types of care. Download the article from the White Rose repository here.

 

Surfaces And Air Contamination

We are investigating the relationship between the microbial burden of the air and how much of that lands on the surfaces. Relating patient care activities to contamination levels can help inform cleaning schedules and therefore the risk of healthcare workers picking germs up on their hands.

Quantitative Microbial Risk Assessment

Depending on how and how much of an organism a susceptible patient receives, will dictate how they respond. We have developed a methodology framework for investigating the effect of when a inoculum dose is received.

Modelling the Effect of the Air on Infection Risk

We have created models that relates the ventilation rate of a multi-bed and the risk of infection from an airborne pathogen. This is a stochastic model that also considers how the rooms are ventilated and simulates the mixing between rooms. Read more here.

Infection, Ventilation Cost Benefit Analysis

We have investigated the trade-off between the cost of energy for increasing ventilation and the benefit for reduced infection. This queries the effect of increasing the HTM 03-01 guidelines of 6 air changes per hour. Read more here.