Optimal layout for an isolation room to contain COVID-19 revealed

By Stephen Beech via SWNS

The optimal layout for an isolation room to contain the spread of COVID-19 has been worked out following tests at a London hospital.

Researchers used a state-of-the-art computational fluid dynamics model to simulate the 3D spatial transmission of the virus within an isolation room at the Royal Brompton Hospital in Chelsea, west London, UK.

Their goal was to explore the optimal room layout to reduce the risk of infection for healthcare staff.

They used an adaptive mesh finite-element computational fluid dynamics model to simulate the 3D spatial distribution of the virus within the room — based on data collected from the room during a COVID-19 patient’s stay.

The work centered on the location of the room’s air extractor and filtration rates, the location of the patient’s bed, and the health and safety of the hospital staff working within the area.

Dr. Fangxin Fang, of Imperial College London, said: “We modeled the virus transport and spreading processes and considered the effect of the temperature and humidity on the virus decay.

“We also modeled fluid and turbulence dynamics in our study, and explored the spatial distribution of the virus, velocity field, and humidity under different air exchange rates and extractor locations.”

The research team discovered that the area of highest risk of infection is above a patient’s bed at a height of 0.7 to two meters (2.3 to 6.5 feet), where the highest concentration of COVID-19 virus is found.

After the virus was expelled from a patient’s mouth, Dr. Fang explained that it gets driven vertically by buoyancy and wind forces within the room.

Based on the group’s findings, the optimal layout for an isolation room to minimize infection risk is to use a ceiling extractor with an air exchange rate of 10 air changes per hour.

The research team said that their study, published in the journal Physics of Fluids, focused on an isolation room within a hospital and its numerical results are limited due to the omission of droplet evaporation and particle matters.

Now, the group plans to include evaporation and particle processes in models of a standard hospital patient room, intensive care unit, and waiting room.

Dr. Fang added: “Further work will also focus on artificial intelligence-based surrogate modeling for rapid simulations, uncertainty analysis, and optimal control of ventilation systems as well as efficient energy use."